Raspberry Pi Min-Grant project - User contributions [en]

File:SigCommLab1.pdf

2015-10-20T20:01:17Z

Cmaina:

Signals and Communication

2015-10-20T19:59:55Z

Cmaina:

'''Signals and Communication'''

This course is taught in the third year of the electrical engineering curriculum. After an introduction to the classification and mathematical analysis of signals in both the time and frequency domains, the course introduces analogue modulation schemes such as amplitude modulation (AM) and frequency modulation (FM). We propose to enhance the laboratory exercises in this course by introducing the students to the concept of software defined radio (SDR) using the Raspberry Pi and designing two laboratory exercises that implement SDR on a Raspberry Pi. We first briefly introduce SDR and then describe the two laboratory exercises.

'''Software Defined Radio'''

 SDR is a communication system framework that moves all the signal processing in current radio systems from dedicated hardware modules to software. Therefore the same hardware system is capable of implementing several modulation schemes by simply changing the controlling software. An SDR system consists of an antenna, an analogue-to-digital converter which converts the radio frequency (RF) signal to digital samples and software which manipulates these samples to retrieve the information 

 SDR has become popular with electronics hobbyists because it was discovered that cheap USB receivers (also known as dongles) designed to receive digital TV broadcasts could be turned into SDR receivers allowing access to samples of analogue RF signals. These samples could then be processed using appropriate software. A popular dongle is the DVB-T TV tuner dongle based on the RTL2832U chipset which retails for about $20.

[[File:Sdr1.jpg|thumb|SDR Dongle connected to a Raspberry Pi Model B+.]]

With one of these cheap dongles, it is possible to implement different communication systems. In fact a large community of hobbyists has emerged and a number of their projects are freely available online (see [http://www.rtl-sdr.com/about-rtl-sdr/} http://www.rtl-sdr.com/about-rtl-sdr/]). An open source driver rtl-sdr is also available for linux based systems. This software allows the user to tune to a particular frequency in the range of the dongle's tuner (27-1700 MHz for the DVB-T TV tuner) and to obtain samples of the in-phase and quadrature components of the RF signal. These samples can then be appropriately processed to recover the message signal.

'''Software Setup'''

In order to run the laboratory exercises, we will need to install the rtl-sdr driver which turns the DVB-T TV tuner dongle into a software defined radio. You can obtain the source for the driver here [[https://github.com/steve-m/librtlsdr https://github.com/steve-m/librtlsdr]]. To check out the repository type

<code>git clone [git://github.com/steve-m/librtlsdr.git git://github.com/steve-m/librtlsdr.git]</code>

Once the code is downloaded. Follow these instructions [http://sdr.osmocom.org/trac/wiki/rtl-sdr [1]]. You will need to have installed cmake and libusb1.0. You can do this by typing

<code>sudo apt-get install cmake</code>

and

<code>sudo apt-get install libusb-1.0-0-dev</code>

'''Laboratory Exercises'''

There will be three laboratory exercises in this course. The labs are listed below with 

'''1. Introduction to python'''

In this lab, students will be introduced to python. This knowledge will be useful for the subsequent labs. Download the manual here [[File:SigCommLab1.pdf]]

 '''2. FM Signal Demodulation'''

In FM systems, a baseband message signal modifies the instantaneous frequency of the carrier signal. This laboratory exercise will expose the students to FM demodulation using SDR.

Department of Electrical Engineering, Dedan Kimathi University of Technology (DeKUT)

2015-09-11T22:19:22Z

Cmaina:

'''Project Title: Re-imagining Electrical Engineering Education Using The Raspberry Pi'''

'''Abstract'''

The current generation of microprocessors and microcontrollers have the potential to revolutionize electrical engineering education due to their low cost, small size and increased computing power. The Raspberry Pi is a cheap and powerful microprocessor with much of the functionality of a modern personal computer. In this project we plan to develop and implement laboratory exercises based on the Raspberry Pi for four electrical engineering courses at the Dedan Kimathi University of Technology. The courses are 1) Signals and Communication 2) Digital Signal Processing 3) Instrumentation and 4) Control Engineering. These laboratory exercises will expose the students to important areas in these courses using the Raspberry Pi as a computing platform and encourage them to use the device in their own projects outside the classroom. We will design detailed laboratory manuals and assess the value of the labs via student feedback and quantitative measures such as test scores. It is hoped that the laboratory exercises will be adopted by our institution and other universities offering electrical engineering.

[[File:Pi card.JPG|thumb|A Raspberry Pi Model B+. A Kenyan bank card is shown for comparison.]]

'''Personnel'''

#Dr. Ciira Maina[https://sites.google.com/site/cwamainadekut/ [1]], DeKUT
#Mr. Asaph Mbugua, DeKUT
#Dr. Kamau Gachigi, Gearbox and University of Nairobi[http://www.gearbox.co.ke/ [2]]
#Mr. James Abuogo, DeKUT

'''Project Description'''

In the following pages, we document the current state of work on the laboratory exercises in the four courses mentioned in the abstract.

#[[Signals and Communication|Signals and Communication]]
#[[Digital Signal Processing|Digital Signal Processing]]
#[[Instrumentation|Instrumentation]]
#[[Control Engineering|Control Engineering]]

'''Robotics and Outreach'''

One of the aims of the project is to expose primary and secondary school students to technology. We demonstrated a Raspberry Pi based robot at the Central Kenya ASK show. In addition, we introduced the young showgoers to computer programming using the Scratch programming language [https://scratch.mit.edu/about/ [1]]. 

<gallery widths="300px" heights="300px">
File:Ask3.JPG|Raspberry Pi Robot
File:Ask2.JPG|Demonstrating the Scratch programming language
File:Ask2.jpg|Demonstrating the robot to Primary school pupils
</gallery>

 '''General System Setup'''

To effectively use the Raspberry pi, we must set up a number of systems and use a number of tools:

#[[Setting up internet access|Setting up internet access]]
#[[Audio setup|Audio setup]]
#[[Keyboard configuration|Keyboard configuration]]
#[[Remote login and file transfer|Remote login and file transfer]]

'''Important Tools'''

We have found the following tools useful so far during this project. We will update this list as often as possible

#Google forms 
#Bitbucket repository for collaboration
#Surveymonkey for anonymous online surveys

Department of Electrical Engineering, Dedan Kimathi University of Technology (DeKUT)

2015-09-11T22:18:20Z

Cmaina:

'''Project Title: Re-imagining Electrical Engineering Education Using The Raspberry Pi'''

'''Abstract'''

The current generation of microprocessors and microcontrollers have the potential to revolutionize electrical engineering education due to their low cost, small size and increased computing power. The Raspberry Pi is a cheap and powerful microprocessor with much of the functionality of a modern personal computer. In this project we plan to develop and implement laboratory exercises based on the Raspberry Pi for four electrical engineering courses at the Dedan Kimathi University of Technology. The courses are 1) Signals and Communication 2) Digital Signal Processing 3) Instrumentation and 4) Control Engineering. These laboratory exercises will expose the students to important areas in these courses using the Raspberry Pi as a computing platform and encourage them to use the device in their own projects outside the classroom. We will design detailed laboratory manuals and assess the value of the labs via student feedback and quantitative measures such as test scores. It is hoped that the laboratory exercises will be adopted by our institution and other universities offering electrical engineering.

[[File:Pi card.JPG|thumb|A Raspberry Pi Model B+. A Kenyan bank card is shown for comparison.]]

'''Personnel'''

#Dr. Ciira Maina[https://sites.google.com/site/cwamainadekut/ [1]], DeKUT
#Mr. Asaph Mbugua, DeKUT
#Dr. Kamau Gachigi, Gearbox and University of Nairobi[http://www.gearbox.co.ke/ [2]]
#Mr. James Abuogo, DeKUT

'''Project Description'''

In the following pages, we document the current state of work on the laboratory exercises in the four courses mentioned in the abstract.

#[[Signals and Communication|Signals and Communication]]
#[[Digital Signal Processing|Digital Signal Processing]]
#[[Instrumentation|Instrumentation]]
#[[Control Engineering|Control Engineering]]

'''Robotics and Outreach'''

One of the aims of the project is to expose primary and secondary school students to technology. We demonstrated a Raspberry Pi based robot at the Central Kenya ASK show. In addition, we introduced the young showgoers to computer programming using the Scratch programming language [https://scratch.mit.edu/about/ [1]]. 

<gallery widths=200px heights=200px>
File:Ask3.JPG|Raspberry Pi Robot
File:Ask2.JPG|Demonstrating the Scratch programming language
File:Ask2.jpg|Demonstrating the robot to Primary school pupils
</gallery>

 '''General System Setup'''

To effectively use the Raspberry pi, we must set up a number of systems and use a number of tools:

#[[Setting up internet access|Setting up internet access]]
#[[Audio setup|Audio setup]]
#[[Keyboard configuration|Keyboard configuration]]
#[[Remote login and file transfer|Remote login and file transfer]]

'''Important Tools'''

We have found the following tools useful so far during this project. We will update this list as often as possible

#Google forms 
#Bitbucket repository for collaboration
#Surveymonkey for anonymous online surveys

Department of Electrical Engineering, Dedan Kimathi University of Technology (DeKUT)

2015-09-11T22:15:47Z

Cmaina:

'''Project Title: Re-imagining Electrical Engineering Education Using The Raspberry Pi'''

'''Abstract'''

The current generation of microprocessors and microcontrollers have the potential to revolutionize electrical engineering education due to their low cost, small size and increased computing power. The Raspberry Pi is a cheap and powerful microprocessor with much of the functionality of a modern personal computer. In this project we plan to develop and implement laboratory exercises based on the Raspberry Pi for four electrical engineering courses at the Dedan Kimathi University of Technology. The courses are 1) Signals and Communication 2) Digital Signal Processing 3) Instrumentation and 4) Control Engineering. These laboratory exercises will expose the students to important areas in these courses using the Raspberry Pi as a computing platform and encourage them to use the device in their own projects outside the classroom. We will design detailed laboratory manuals and assess the value of the labs via student feedback and quantitative measures such as test scores. It is hoped that the laboratory exercises will be adopted by our institution and other universities offering electrical engineering.

[[File:Pi card.JPG|thumb|A Raspberry Pi Model B+. A Kenyan bank card is shown for comparison.]]

'''Personnel'''

#Dr. Ciira Maina[https://sites.google.com/site/cwamainadekut/ [1]], DeKUT
#Mr. Asaph Mbugua, DeKUT
#Dr. Kamau Gachigi, Gearbox and University of Nairobi[http://www.gearbox.co.ke/ [2]]
#Mr. James Abuogo, DeKUT

'''Project Description'''

In the following pages, we document the current state of work on the laboratory exercises in the four courses mentioned in the abstract.

#[[Signals and Communication|Signals and Communication]]
#[[Digital Signal Processing|Digital Signal Processing]]
#[[Instrumentation|Instrumentation]]
#[[Control Engineering|Control Engineering]]

'''Robotics and Outreach'''

One of the aims of the project is to expose primary and secondary school students to technology. We demonstrated a Raspberry Pi based robot at the Central Kenya ASK show. In addition, we introduced the young showgoers to computer programming using the Scratch programming language [https://scratch.mit.edu/about/ [1]]. 

<gallery>
File:Ask3.JPG|Raspberry Pi Robot
File:Ask2.JPG|Demonstrating the Scratch programming language
File:Ask2.jpg|Demonstrating the robot to Primary school pupils
</gallery>

 '''General System Setup'''

To effectively use the Raspberry pi, we must set up a number of systems and use a number of tools:

#[[Setting up internet access|Setting up internet access]]
#[[Audio setup|Audio setup]]
#[[Keyboard configuration|Keyboard configuration]]
#[[Remote login and file transfer|Remote login and file transfer]]

'''Important Tools'''

We have found the following tools useful so far during this project. We will update this list as often as possible

#Google forms 
#Bitbucket repository for collaboration
#Surveymonkey for anonymous online surveys

Department of Electrical Engineering, Dedan Kimathi University of Technology (DeKUT)

2015-09-11T22:15:02Z

Cmaina:

'''Project Title: Re-imagining Electrical Engineering Education Using The Raspberry Pi'''

'''Abstract'''

The current generation of microprocessors and microcontrollers have the potential to revolutionize electrical engineering education due to their low cost, small size and increased computing power. The Raspberry Pi is a cheap and powerful microprocessor with much of the functionality of a modern personal computer. In this project we plan to develop and implement laboratory exercises based on the Raspberry Pi for four electrical engineering courses at the Dedan Kimathi University of Technology. The courses are 1) Signals and Communication 2) Digital Signal Processing 3) Instrumentation and 4) Control Engineering. These laboratory exercises will expose the students to important areas in these courses using the Raspberry Pi as a computing platform and encourage them to use the device in their own projects outside the classroom. We will design detailed laboratory manuals and assess the value of the labs via student feedback and quantitative measures such as test scores. It is hoped that the laboratory exercises will be adopted by our institution and other universities offering electrical engineering.

[[File:Pi card.JPG|thumb|A Raspberry Pi Model B+. A Kenyan bank card is shown for comparison.]]

'''Personnel'''

#Dr. Ciira Maina[https://sites.google.com/site/cwamainadekut/ [1]], DeKUT
#Mr. Asaph Mbugua, DeKUT
#Dr. Kamau Gachigi, Gearbox and University of Nairobi[http://www.gearbox.co.ke/ [2]]
#Mr. James Abuogo, DeKUT

'''Project Description'''

In the following pages, we document the current state of work on the laboratory exercises in the four courses mentioned in the abstract.

#[[Signals and Communication|Signals and Communication]]
#[[Digital Signal Processing|Digital Signal Processing]]
#[[Instrumentation|Instrumentation]]
#[[Control Engineering|Control Engineering]]

'''Robotics and Outreach'''

One of the aims of the project is to expose primary and secondary school students to technology. We demonstrated a Raspberry Pi based robot at the Central Kenya ASK show. In addition, we introduced the young showgoers to computer programming using the Scratch programming language [https://scratch.mit.edu/about/ [1]]. 

<gallery>
File:Ask3.JPG|Raspberry Pi Robot
File:Ask2.JPG|Demonstrating the Scratch programming language
File:Ask2.jpg|Demonstrating the robot to Primary school pupils
</gallery>

 '''General System Setup'''

To effectively use the Raspberry pi, we must set up a number of systems and use a number of tools:

#[[Setting up internet access|Setting up internet access]]
#[[Audio setup|Audio setup]]
#[[Keyboard configuration|Keyboard configuration]]
#[[Remote login and file transfer|Remote login and file transfer]]

'''Important Tools'''

We have found the following tools useful so far during this project. We will update this list as often as possible

#Google forms 
#Bitbucket repository for collaboration
#Surveymonkey for anonymous online surveys

Department of Electrical Engineering, Dedan Kimathi University of Technology (DeKUT)

2015-09-11T22:13:13Z

Cmaina:

'''Project Title: Re-imagining Electrical Engineering Education Using The Raspberry Pi'''

'''Abstract'''

The current generation of microprocessors and microcontrollers have the potential to revolutionize electrical engineering education due to their low cost, small size and increased computing power. The Raspberry Pi is a cheap and powerful microprocessor with much of the functionality of a modern personal computer. In this project we plan to develop and implement laboratory exercises based on the Raspberry Pi for four electrical engineering courses at the Dedan Kimathi University of Technology. The courses are 1) Signals and Communication 2) Digital Signal Processing 3) Instrumentation and 4) Control Engineering. These laboratory exercises will expose the students to important areas in these courses using the Raspberry Pi as a computing platform and encourage them to use the device in their own projects outside the classroom. We will design detailed laboratory manuals and assess the value of the labs via student feedback and quantitative measures such as test scores. It is hoped that the laboratory exercises will be adopted by our institution and other universities offering electrical engineering.

[[File:Pi card.JPG|thumb|A Raspberry Pi Model B+. A Kenyan bank card is shown for comparison.]]

'''Personnel'''

#Dr. Ciira Maina[https://sites.google.com/site/cwamainadekut/ [1]], DeKUT
#Mr. Asaph Mbugua, DeKUT
#Dr. Kamau Gachigi, Gearbox and University of Nairobi[http://www.gearbox.co.ke/ [2]]
#Mr. James Abuogo, DeKUT

'''Project Description'''

In the following pages, we document the current state of work on the laboratory exercises in the four courses mentioned in the abstract.

#[[Signals and Communication|Signals and Communication]]
#[[Digital Signal Processing|Digital Signal Processing]]
#[[Instrumentation|Instrumentation]]
#[[Control Engineering|Control Engineering]]

'''Robotics and Outreach'''

One of the aims of the project is to expose primary and secondary school students to technology. We demonstrated a Raspberry Pi based robot at the Central Kenya ASK show. In addition, we introduced the young showgoers to computer programming using the Scratch programming language [https://scratch.mit.edu/about/ [1]]. 

<gallery>
[[File:Ask2.JPG|thumb|center|Demonstrating the Scratch programming language]] [[File:Ask2.jpg|thumb|right|Demonstrating the robot to Primary school pupils]] [[File:Ask3.JPG|thumb|left|Raspberry Pi Robot]]
</gallery>

 '''General System Setup'''

To effectively use the Raspberry pi, we must set up a number of systems and use a number of tools:

#[[Setting up internet access|Setting up internet access]]
#[[Audio setup|Audio setup]]
#[[Keyboard configuration|Keyboard configuration]]
#[[Remote login and file transfer|Remote login and file transfer]]

'''Important Tools'''

We have found the following tools useful so far during this project. We will update this list as often as possible

#Google forms 
#Bitbucket repository for collaboration
#Surveymonkey for anonymous online surveys

Department of Electrical Engineering, Dedan Kimathi University of Technology (DeKUT)

2015-09-11T22:10:39Z

Cmaina:

'''Project Title: Re-imagining Electrical Engineering Education Using The Raspberry Pi'''

'''Abstract'''

The current generation of microprocessors and microcontrollers have the potential to revolutionize electrical engineering education due to their low cost, small size and increased computing power. The Raspberry Pi is a cheap and powerful microprocessor with much of the functionality of a modern personal computer. In this project we plan to develop and implement laboratory exercises based on the Raspberry Pi for four electrical engineering courses at the Dedan Kimathi University of Technology. The courses are 1) Signals and Communication 2) Digital Signal Processing 3) Instrumentation and 4) Control Engineering. These laboratory exercises will expose the students to important areas in these courses using the Raspberry Pi as a computing platform and encourage them to use the device in their own projects outside the classroom. We will design detailed laboratory manuals and assess the value of the labs via student feedback and quantitative measures such as test scores. It is hoped that the laboratory exercises will be adopted by our institution and other universities offering electrical engineering.

[[File:Pi card.JPG|thumb|A Raspberry Pi Model B+. A Kenyan bank card is shown for comparison.]]

'''Personnel'''

#Dr. Ciira Maina[https://sites.google.com/site/cwamainadekut/ [1]], DeKUT
#Mr. Asaph Mbugua, DeKUT
#Dr. Kamau Gachigi, Gearbox and University of Nairobi[http://www.gearbox.co.ke/ [2]]
#Mr. James Abuogo, DeKUT

'''Project Description'''

In the following pages, we document the current state of work on the laboratory exercises in the four courses mentioned in the abstract.

#[[Signals and Communication|Signals and Communication]]
#[[Digital Signal Processing|Digital Signal Processing]]
#[[Instrumentation|Instrumentation]]
#[[Control Engineering|Control Engineering]]

'''Robotics and Outreach'''

One of the aims of the project is to expose primary and secondary school students to technology. We demonstrated a Raspberry Pi based robot at the Central Kenya ASK show. In addition, we introduced the young showgoers to computer programming using the Scratch programming language [https://scratch.mit.edu/about/ [1]]. 

[[File:Ask2.JPG|thumb|center|Demonstrating the Scratch programming language]] [[File:Ask2.jpg|thumb|right|Demonstrating the robot to Primary school pupils]] [[File:Ask3.JPG|thumb|left|Raspberry Pi Robot]]

'''General System Setup'''

To effectively use the Raspberry pi, we must set up a number of systems and use a number of tools:

#[[Setting up internet access|Setting up internet access]]
#[[Audio setup|Audio setup]]
#[[Keyboard configuration|Keyboard configuration]]
#[[Remote login and file transfer|Remote login and file transfer]]

'''Important Tools'''

We have found the following tools useful so far during this project. We will update this list as often as possible

#Google forms 
#Bitbucket repository for collaboration
#Surveymonkey for anonymous online surveys

Department of Electrical Engineering, Dedan Kimathi University of Technology (DeKUT)

2015-09-11T22:09:59Z

Cmaina:

'''Project Title: Re-imagining Electrical Engineering Education Using The Raspberry Pi'''

'''Abstract'''

The current generation of microprocessors and microcontrollers have the potential to revolutionize electrical engineering education due to their low cost, small size and increased computing power. The Raspberry Pi is a cheap and powerful microprocessor with much of the functionality of a modern personal computer. In this project we plan to develop and implement laboratory exercises based on the Raspberry Pi for four electrical engineering courses at the Dedan Kimathi University of Technology. The courses are 1) Signals and Communication 2) Digital Signal Processing 3) Instrumentation and 4) Control Engineering. These laboratory exercises will expose the students to important areas in these courses using the Raspberry Pi as a computing platform and encourage them to use the device in their own projects outside the classroom. We will design detailed laboratory manuals and assess the value of the labs via student feedback and quantitative measures such as test scores. It is hoped that the laboratory exercises will be adopted by our institution and other universities offering electrical engineering.

[[File:Pi card.JPG|thumb|A Raspberry Pi Model B+. A Kenyan bank card is shown for comparison.]]

'''Personnel'''

#Dr. Ciira Maina[https://sites.google.com/site/cwamainadekut/ [1]], DeKUT
#Mr. Asaph Mbugua, DeKUT
#Dr. Kamau Gachigi, Gearbox and University of Nairobi[http://www.gearbox.co.ke/ [2]]
#Mr. James Abuogo, DeKUT

'''Project Description'''

In the following pages, we document the current state of work on the laboratory exercises in the four courses mentioned in the abstract.

#[[Signals and Communication|Signals and Communication]]
#[[Digital Signal Processing|Digital Signal Processing]]
#[[Instrumentation|Instrumentation]]
#[[Control Engineering|Control Engineering]]

'''Robotics and Outreach'''

One of the aims of the project is to expose primary and secondary school students to technology. We demonstrated a Raspberry Pi based robot at the Central Kenya ASK show. In addition, we introduced the young showgoers to computer programming using the Scratch programming language [https://scratch.mit.edu/about/ [1]]. 

[[File:Ask2.JPG|thumb|center|Demonstrating the Scratch programming language]] [[File:Ask2.jpg|thumb|right|Demonstrating the robot to Primary school pupils]] [[File:Ask3.JPG|thumb|left|Raspberry Pi Robot]]

'''General System Setup'''

To effectively use the Raspberry pi, we must set up a number of systems and use a number of tools:

#[[Setting up internet access|Setting up internet access]]
#[[Audio setup|Audio setup]]
#[[Keyboard configuration|Keyboard configuration]]
#[[Remote login and file transfer|Remote login and file transfer]]

'''Important Tools'''

We have found the following tools useful so far during this project. We will update this list as often as possible

#Google forms 
#Bitbucket repository for collaboration
#Surveymonkey for anonymous online surveys

Department of Electrical Engineering, Dedan Kimathi University of Technology (DeKUT)

2015-09-11T22:08:05Z

Cmaina:

'''Project Title: Re-imagining Electrical Engineering Education Using The Raspberry Pi'''

'''Abstract'''

The current generation of microprocessors and microcontrollers have the potential to revolutionize electrical engineering education due to their low cost, small size and increased computing power. The Raspberry Pi is a cheap and powerful microprocessor with much of the functionality of a modern personal computer. In this project we plan to develop and implement laboratory exercises based on the Raspberry Pi for four electrical engineering courses at the Dedan Kimathi University of Technology. The courses are 1) Signals and Communication 2) Digital Signal Processing 3) Instrumentation and 4) Control Engineering. These laboratory exercises will expose the students to important areas in these courses using the Raspberry Pi as a computing platform and encourage them to use the device in their own projects outside the classroom. We will design detailed laboratory manuals and assess the value of the labs via student feedback and quantitative measures such as test scores. It is hoped that the laboratory exercises will be adopted by our institution and other universities offering electrical engineering.

[[File:Pi card.JPG|thumb|A Raspberry Pi Model B+. A Kenyan bank card is shown for comparison.]]

'''Personnel'''

#Dr. Ciira Maina[https://sites.google.com/site/cwamainadekut/ [1]], DeKUT
#Mr. Asaph Mbugua, DeKUT
#Dr. Kamau Gachigi, Gearbox and University of Nairobi[http://www.gearbox.co.ke/ [2]]
#Mr. James Abuogo, DeKUT

'''Project Description'''

In the following pages, we document the current state of work on the laboratory exercises in the four courses mentioned in the abstract.

#[[Signals and Communication|Signals and Communication]]
#[[Digital Signal Processing|Digital Signal Processing]]
#[[Instrumentation|Instrumentation]]
#[[Control Engineering|Control Engineering]]

'''Robotics and Outreach'''

One of the aims of the project is to expose primary and secondary school students to technology. We demonstrated a Raspberry Pi based robot at the Central Kenya ASK show. In addition, we introduced the young showgoers to computer programming using the Scratch programming language [https://scratch.mit.edu/about/ [1]]. 

[[File:Ask2.JPG|thumb|center|Demonstrating the Scratch programming language]] [[File:Ask2.jpg|thumb|right|Demonstrating the robot to Primary school pupils]] [[File:Ask3.JPG|thumb|left|Raspberry Pi Robot]]

 ''''''

''''''

''''''

''''''

''''''

'''General System Setup'''

To effectively use the Raspberry pi, we must set up a number of systems and use a number of tools:

#[[Setting up internet access|Setting up internet access]]
#[[Audio setup|Audio setup]]
#[[Keyboard configuration|Keyboard configuration]]
#[[Remote login and file transfer|Remote login and file transfer]]

'''Important Tools'''

We have found the following tools useful so far during this project. We will update this list as often as possible

#Google forms 
#Bitbucket repository for collaboration
#Surveymonkey for anonymous online surveys

Department of Electrical Engineering, Dedan Kimathi University of Technology (DeKUT)

2015-09-11T22:05:31Z

Cmaina:

'''Project Title: Re-imagining Electrical Engineering Education Using The Raspberry Pi'''

'''Abstract'''

The current generation of microprocessors and microcontrollers have the potential to revolutionize electrical engineering education due to their low cost, small size and increased computing power. The Raspberry Pi is a cheap and powerful microprocessor with much of the functionality of a modern personal computer. In this project we plan to develop and implement laboratory exercises based on the Raspberry Pi for four electrical engineering courses at the Dedan Kimathi University of Technology. The courses are 1) Signals and Communication 2) Digital Signal Processing 3) Instrumentation and 4) Control Engineering. These laboratory exercises will expose the students to important areas in these courses using the Raspberry Pi as a computing platform and encourage them to use the device in their own projects outside the classroom. We will design detailed laboratory manuals and assess the value of the labs via student feedback and quantitative measures such as test scores. It is hoped that the laboratory exercises will be adopted by our institution and other universities offering electrical engineering.

[[File:Pi card.JPG|thumb|A Raspberry Pi Model B+. A Kenyan bank card is shown for comparison.]]

'''Personnel'''

#Dr. Ciira Maina[https://sites.google.com/site/cwamainadekut/ [1]], DeKUT
#Mr. Asaph Mbugua, DeKUT
#Dr. Kamau Gachigi, Gearbox and University of Nairobi[http://www.gearbox.co.ke/ [2]]
#Mr. James Abuogo, DeKUT

'''Project Description'''

In the following pages, we document the current state of work on the laboratory exercises in the four courses mentioned in the abstract.

#[[Signals and Communication|Signals and Communication]]
#[[Digital Signal Processing|Digital Signal Processing]]
#[[Instrumentation|Instrumentation]]
#[[Control Engineering|Control Engineering]]

'''Robotics and Outreach'''

One of the aims of the project is to expose primary and secondary school students to technology. We demonstrated a Raspberry Pi based robot at the Central Kenya ASK show. In addition, we introduced the young showgoers to computer programming using the Scratch programming language [https://scratch.mit.edu/about/ [1]]. 

[[File:Ask2.JPG|thumb|center|Demonstrating the Scratch programming language]]
[[File:Ask2.jpg|thumb|right|Demonstrating the robot to Primary school pupils]]
[[File:Ask3.JPG|thumb|left|Raspberry Pi Robot]]

'''General System Setup'''

To effectively use the Raspberry pi, we must set up a number of systems and use a number of tools:

#[[Setting up internet access|Setting up internet access]]
#[[Audio setup|Audio setup]]
#[[Keyboard configuration|Keyboard configuration]]
#[[Remote login and file transfer|Remote login and file transfer]]

'''Important Tools'''

We have found the following tools useful so far during this project. We will update this list as often as possible

#Google forms 
#Bitbucket repository for collaboration
#Surveymonkey for anonymous online surveys

Department of Electrical Engineering, Dedan Kimathi University of Technology (DeKUT)

2015-09-11T21:58:50Z

Cmaina:

'''Project Title: Re-imagining Electrical Engineering Education Using The Raspberry Pi'''

'''Abstract'''

The current generation of microprocessors and microcontrollers have the potential to revolutionize electrical engineering education due to their low cost, small size and increased computing power. The Raspberry Pi is a cheap and powerful microprocessor with much of the functionality of a modern personal computer. In this project we plan to develop and implement laboratory exercises based on the Raspberry Pi for four electrical engineering courses at the Dedan Kimathi University of Technology. The courses are 1) Signals and Communication 2) Digital Signal Processing 3) Instrumentation and 4) Control Engineering. These laboratory exercises will expose the students to important areas in these courses using the Raspberry Pi as a computing platform and encourage them to use the device in their own projects outside the classroom. We will design detailed laboratory manuals and assess the value of the labs via student feedback and quantitative measures such as test scores. It is hoped that the laboratory exercises will be adopted by our institution and other universities offering electrical engineering.

[[File:Pi card.JPG|thumb|A Raspberry Pi Model B+. A Kenyan bank card is shown for comparison.]]

'''Personnel'''

#Dr. Ciira Maina[https://sites.google.com/site/cwamainadekut/ [1]], DeKUT
#Mr. Asaph Mbugua, DeKUT
#Dr. Kamau Gachigi, Gearbox and University of Nairobi[http://www.gearbox.co.ke/ [2]]
#Mr. James Abuogo, DeKUT

'''Project Description'''

In the following pages, we document the current state of work on the laboratory exercises in the four courses mentioned in the abstract.

#[[Signals and Communication|Signals and Communication]]
#[[Digital Signal Processing|Digital Signal Processing]]
#[[Instrumentation|Instrumentation]]
#[[Control Engineering|Control Engineering]]

'''Robotics and Outreach'''

One of the aims of the project is to expose primary and secondary school students to technology. We demonstrated a Raspberry Pi based robot at the Central Kenya ASK show. In addition, we introduced the young showgoers to computer programming using the Scratch programming language [https://scratch.mit.edu/about/ [1]]. 

[[File:Ask2.JPG|thumb|center|Demonstrating the robot to Primary school pupils]]

[[File:Ask2.jpg|thumb|right|Demonstrating the robot to Primary school pupils]]

[[File:Ask3.JPG|thumb|left|Raspberry Pi Robot]]

'''General System Setup'''

To effectively use the Raspberry pi, we must set up a number of systems and use a number of tools:

#[[Setting up internet access|Setting up internet access]]
#[[Audio setup|Audio setup]]
#[[Keyboard configuration|Keyboard configuration]]
#[[Remote login and file transfer|Remote login and file transfer]]

'''Important Tools'''

We have found the following tools useful so far during this project. We will update this list as often as possible

#Google forms 
#Bitbucket repository for collaboration
#Surveymonkey for anonymous online surveys

Department of Electrical Engineering, Dedan Kimathi University of Technology (DeKUT)

2015-09-11T21:55:08Z

Cmaina:

'''Project Title: Re-imagining Electrical Engineering Education Using The Raspberry Pi'''

'''Abstract'''

The current generation of microprocessors and microcontrollers have the potential to revolutionize electrical engineering education due to their low cost, small size and increased computing power. The Raspberry Pi is a cheap and powerful microprocessor with much of the functionality of a modern personal computer. In this project we plan to develop and implement laboratory exercises based on the Raspberry Pi for four electrical engineering courses at the Dedan Kimathi University of Technology. The courses are 1) Signals and Communication 2) Digital Signal Processing 3) Instrumentation and 4) Control Engineering. These laboratory exercises will expose the students to important areas in these courses using the Raspberry Pi as a computing platform and encourage them to use the device in their own projects outside the classroom. We will design detailed laboratory manuals and assess the value of the labs via student feedback and quantitative measures such as test scores. It is hoped that the laboratory exercises will be adopted by our institution and other universities offering electrical engineering.

[[File:Pi card.JPG|thumb|A Raspberry Pi Model B+. A Kenyan bank card is shown for comparison.]]

'''Personnel'''

#Dr. Ciira Maina[https://sites.google.com/site/cwamainadekut/ [1]], DeKUT
#Mr. Asaph Mbugua, DeKUT
#Dr. Kamau Gachigi, Gearbox and University of Nairobi[http://www.gearbox.co.ke/ [2]]
#Mr. James Abuogo, DeKUT

'''Project Description'''

In the following pages, we document the current state of work on the laboratory exercises in the four courses mentioned in the abstract.

#[[Signals and Communication|Signals and Communication]]
#[[Digital Signal Processing|Digital Signal Processing]]
#[[Instrumentation|Instrumentation]]
#[[Control Engineering|Control Engineering]]

'''Robotics and Outreach'''

One of the aims of the project is to expose primary and secondary school students to technology. We demonstrated a Raspberry Pi based robot at the Central Kenya ASK show. In addition, we introduced the young showgoers to computer programming using the Scratch programming language [https://scratch.mit.edu/about/ [1]]. 

[[File:Ask2.JPG]]

[[File:Ask2.jpg|thumb|right|Demonstrating the robot to Primary school pupils]]

[[File:Ask3.JPG|thumb|left|Raspberry Pi Robot]]

'''General System Setup'''

To effectively use the Raspberry pi, we must set up a number of systems and use a number of tools:

#[[Setting up internet access|Setting up internet access]]
#[[Audio setup|Audio setup]]
#[[Keyboard configuration|Keyboard configuration]]
#[[Remote login and file transfer|Remote login and file transfer]]

'''Important Tools'''

We have found the following tools useful so far during this project. We will update this list as often as possible

#Google forms 
#Bitbucket repository for collaboration
#Surveymonkey for anonymous online surveys

File:Ask2.JPG

2015-09-11T21:53:04Z

Cmaina: Cmaina uploaded a new version of File:Ask2.JPG

Department of Electrical Engineering, Dedan Kimathi University of Technology (DeKUT)

2015-09-11T21:49:11Z

Cmaina:

'''Project Title: Re-imagining Electrical Engineering Education Using The Raspberry Pi'''

'''Abstract'''

The current generation of microprocessors and microcontrollers have the potential to revolutionize electrical engineering education due to their low cost, small size and increased computing power. The Raspberry Pi is a cheap and powerful microprocessor with much of the functionality of a modern personal computer. In this project we plan to develop and implement laboratory exercises based on the Raspberry Pi for four electrical engineering courses at the Dedan Kimathi University of Technology. The courses are 1) Signals and Communication 2) Digital Signal Processing 3) Instrumentation and 4) Control Engineering. These laboratory exercises will expose the students to important areas in these courses using the Raspberry Pi as a computing platform and encourage them to use the device in their own projects outside the classroom. We will design detailed laboratory manuals and assess the value of the labs via student feedback and quantitative measures such as test scores. It is hoped that the laboratory exercises will be adopted by our institution and other universities offering electrical engineering.

[[File:Pi card.JPG|thumb|A Raspberry Pi Model B+. A Kenyan bank card is shown for comparison.]]

'''Personnel'''

#Dr. Ciira Maina[https://sites.google.com/site/cwamainadekut/ [1]], DeKUT
#Mr. Asaph Mbugua, DeKUT
#Dr. Kamau Gachigi, Gearbox and University of Nairobi[http://www.gearbox.co.ke/ [2]]
#Mr. James Abuogo, DeKUT

'''Project Description'''

In the following pages, we document the current state of work on the laboratory exercises in the four courses mentioned in the abstract.

#[[Signals and Communication|Signals and Communication]]
#[[Digital Signal Processing|Digital Signal Processing]]
#[[Instrumentation|Instrumentation]]
#[[Control Engineering|Control Engineering]]

'''Robotics and Outreach'''

One of the aims of the project is to expose primary and secondary school students to technology. We demonstrated a Raspberry Pi based robot at the Central Kenya ASK show. In addition, we introduced the young showgoers to computer programming using the Scratch programming language [https://scratch.mit.edu/about/ [1]]. 

[[File:Ask2.jpg]]

[[File:Ask2.jpg|thumb|right|Demonstrating the robot to Primary school pupils]]

[[File:Ask3.JPG|thumb|left|Raspberry Pi Robot]]

''''''

''''''

''''''

''''''

'''General System Setup'''

To effectively use the Raspberry pi, we must set up a number of systems and use a number of tools:

#[[Setting up internet access|Setting up internet access]]
#[[Audio setup|Audio setup]]
#[[Keyboard configuration|Keyboard configuration]]
#[[Remote login and file transfer|Remote login and file transfer]]

'''Important Tools'''

We have found the following tools useful so far during this project. We will update this list as often as possible

#Google forms 
#Bitbucket repository for collaboration
#Surveymonkey for anonymous online surveys

Department of Electrical Engineering, Dedan Kimathi University of Technology (DeKUT)

2015-09-11T21:45:19Z

Cmaina:

'''Project Title: Re-imagining Electrical Engineering Education Using The Raspberry Pi'''

'''Abstract'''

The current generation of microprocessors and microcontrollers have the potential to revolutionize electrical engineering education due to their low cost, small size and increased computing power. The Raspberry Pi is a cheap and powerful microprocessor with much of the functionality of a modern personal computer. In this project we plan to develop and implement laboratory exercises based on the Raspberry Pi for four electrical engineering courses at the Dedan Kimathi University of Technology. The courses are 1) Signals and Communication 2) Digital Signal Processing 3) Instrumentation and 4) Control Engineering. These laboratory exercises will expose the students to important areas in these courses using the Raspberry Pi as a computing platform and encourage them to use the device in their own projects outside the classroom. We will design detailed laboratory manuals and assess the value of the labs via student feedback and quantitative measures such as test scores. It is hoped that the laboratory exercises will be adopted by our institution and other universities offering electrical engineering.

[[File:Pi card.JPG|thumb|A Raspberry Pi Model B+. A Kenyan bank card is shown for comparison.]]

'''Personnel'''

#Dr. Ciira Maina[https://sites.google.com/site/cwamainadekut/ [1]], DeKUT
#Mr. Asaph Mbugua, DeKUT
#Dr. Kamau Gachigi, Gearbox and University of Nairobi[http://www.gearbox.co.ke/ [2]]
#Mr. James Abuogo, DeKUT

'''Project Description'''

In the following pages, we document the current state of work on the laboratory exercises in the four courses mentioned in the abstract.

#[[Signals and Communication|Signals and Communication]]
#[[Digital Signal Processing|Digital Signal Processing]]
#[[Instrumentation|Instrumentation]]
#[[Control Engineering|Control Engineering]]

'''Robotics and Outreach'''

One of the aims of the project is to expose primary and secondary school students to technology. We demonstrated a Raspberry Pi based robot at the Central Kenya ASK show. In addition, we introduced the young showgoers to computer programming using the Scratch programming language [https://scratch.mit.edu/about/ [1]]. 

[[File:Ask2.jpg|thumb|right|Demonstrating the robot to Primary school pupils]]

[[File:Ask3.JPG|thumb|left|Raspberry Pi Robot]]

'''General System Setup'''

To effectively use the Raspberry pi, we must set up a number of systems and use a number of tools:

#[[Setting up internet access|Setting up internet access]]
#[[Audio setup|Audio setup]]
#[[Keyboard configuration|Keyboard configuration]]
#[[Remote login and file transfer|Remote login and file transfer]]

'''Important Tools'''

We have found the following tools useful so far during this project. We will update this list as often as possible

#Google forms 
#Bitbucket repository for collaboration
#Surveymonkey for anonymous online surveys

Department of Electrical Engineering, Dedan Kimathi University of Technology (DeKUT)

2015-09-11T21:43:43Z

Cmaina:

'''Project Title: Re-imagining Electrical Engineering Education Using The Raspberry Pi'''

'''Abstract'''

The current generation of microprocessors and microcontrollers have the potential to revolutionize electrical engineering education due to their low cost, small size and increased computing power. The Raspberry Pi is a cheap and powerful microprocessor with much of the functionality of a modern personal computer. In this project we plan to develop and implement laboratory exercises based on the Raspberry Pi for four electrical engineering courses at the Dedan Kimathi University of Technology. The courses are 1) Signals and Communication 2) Digital Signal Processing 3) Instrumentation and 4) Control Engineering. These laboratory exercises will expose the students to important areas in these courses using the Raspberry Pi as a computing platform and encourage them to use the device in their own projects outside the classroom. We will design detailed laboratory manuals and assess the value of the labs via student feedback and quantitative measures such as test scores. It is hoped that the laboratory exercises will be adopted by our institution and other universities offering electrical engineering.

[[File:Pi card.JPG|thumb|A Raspberry Pi Model B+. A Kenyan bank card is shown for comparison.]]

'''Personnel'''

#Dr. Ciira Maina[https://sites.google.com/site/cwamainadekut/ [1]], DeKUT
#Mr. Asaph Mbugua, DeKUT
#Dr. Kamau Gachigi, Gearbox and University of Nairobi[http://www.gearbox.co.ke/ [2]]
#Mr. James Abuogo, DeKUT

'''Project Description'''

In the following pages, we document the current state of work on the laboratory exercises in the four courses mentioned in the abstract.

#[[Signals and Communication|Signals and Communication]]
#[[Digital Signal Processing|Digital Signal Processing]]
#[[Instrumentation|Instrumentation]]
#[[Control Engineering|Control Engineering]]

'''Robotics and Outreach'''

One of the aims of the project is to expose primary and secondary school students to technology. We demonstrated a Raspberry Pi based robot at the Central Kenya ASK show. In addition, we introduced the young showgoers to computer programming using the Scratch programming language [https://scratch.mit.edu/about/ [1]]. 

[[File:Ask2.jpg]]

[[File:Ask3.JPG|thumb|Raspberry Pi Robot]]

'''General System Setup'''

To effectively use the Raspberry pi, we must set up a number of systems and use a number of tools:

#[[Setting up internet access|Setting up internet access]]
#[[Audio setup|Audio setup]]
#[[Keyboard configuration|Keyboard configuration]]
#[[Remote login and file transfer|Remote login and file transfer]]

'''Important Tools'''

We have found the following tools useful so far during this project. We will update this list as often as possible

#Google forms 
#Bitbucket repository for collaboration
#Surveymonkey for anonymous online surveys

File:Ask2.jpg

2015-09-11T21:41:55Z

Cmaina:

Department of Electrical Engineering, Dedan Kimathi University of Technology (DeKUT)

2015-09-11T21:39:14Z

Cmaina:

'''Project Title: Re-imagining Electrical Engineering Education Using The Raspberry Pi'''

'''Abstract'''

The current generation of microprocessors and microcontrollers have the potential to revolutionize electrical engineering education due to their low cost, small size and increased computing power. The Raspberry Pi is a cheap and powerful microprocessor with much of the functionality of a modern personal computer. In this project we plan to develop and implement laboratory exercises based on the Raspberry Pi for four electrical engineering courses at the Dedan Kimathi University of Technology. The courses are 1) Signals and Communication 2) Digital Signal Processing 3) Instrumentation and 4) Control Engineering. These laboratory exercises will expose the students to important areas in these courses using the Raspberry Pi as a computing platform and encourage them to use the device in their own projects outside the classroom. We will design detailed laboratory manuals and assess the value of the labs via student feedback and quantitative measures such as test scores. It is hoped that the laboratory exercises will be adopted by our institution and other universities offering electrical engineering.

[[File:Pi card.JPG|thumb|A Raspberry Pi Model B+. A Kenyan bank card is shown for comparison.]]

'''Personnel'''

#Dr. Ciira Maina[https://sites.google.com/site/cwamainadekut/ [1]], DeKUT
#Mr. Asaph Mbugua, DeKUT
#Dr. Kamau Gachigi, Gearbox and University of Nairobi[http://www.gearbox.co.ke/ [2]]
#Mr. James Abuogo, DeKUT

'''Project Description'''

In the following pages, we document the current state of work on the laboratory exercises in the four courses mentioned in the abstract.

#[[Signals and Communication|Signals and Communication]]
#[[Digital Signal Processing|Digital Signal Processing]]
#[[Instrumentation|Instrumentation]]
#[[Control Engineering|Control Engineering]]

'''Robotics and Outreach'''

One of the aims of the project is to expose primary and secondary school students to technology. We demonstrated a Raspberry Pi based robot at the Central Kenya ASK show. In addition, we introduced the young showgoers to computer programming using the Scratch programming language [https://scratch.mit.edu/about/ [1]]. 

[[File:Ask3.JPG|thumb|Raspberry Pi Robot]]

'''General System Setup'''

To effectively use the Raspberry pi, we must set up a number of systems and use a number of tools:

#[[Setting up internet access|Setting up internet access]]
#[[Audio setup|Audio setup]]
#[[Keyboard configuration|Keyboard configuration]]
#[[Remote login and file transfer|Remote login and file transfer]]

'''Important Tools'''

We have found the following tools useful so far during this project. We will update this list as often as possible

#Google forms 
#Bitbucket repository for collaboration
#Surveymonkey for anonymous online surveys

Department of Electrical Engineering, Dedan Kimathi University of Technology (DeKUT)

2015-09-11T21:38:05Z

Cmaina:

'''Project Title: Re-imagining Electrical Engineering Education Using The Raspberry Pi'''

'''Abstract'''

The current generation of microprocessors and microcontrollers have the potential to revolutionize electrical engineering education due to their low cost, small size and increased computing power. The Raspberry Pi is a cheap and powerful microprocessor with much of the functionality of a modern personal computer. In this project we plan to develop and implement laboratory exercises based on the Raspberry Pi for four electrical engineering courses at the Dedan Kimathi University of Technology. The courses are 1) Signals and Communication 2) Digital Signal Processing 3) Instrumentation and 4) Control Engineering. These laboratory exercises will expose the students to important areas in these courses using the Raspberry Pi as a computing platform and encourage them to use the device in their own projects outside the classroom. We will design detailed laboratory manuals and assess the value of the labs via student feedback and quantitative measures such as test scores. It is hoped that the laboratory exercises will be adopted by our institution and other universities offering electrical engineering.

[[File:Pi card.JPG|thumb|A Raspberry Pi Model B+. A Kenyan bank card is shown for comparison.]]

'''Personnel'''

#Dr. Ciira Maina[https://sites.google.com/site/cwamainadekut/ [1]], DeKUT
#Mr. Asaph Mbugua, DeKUT
#Dr. Kamau Gachigi, Gearbox and University of Nairobi[http://www.gearbox.co.ke/ [2]]
#Mr. James Abuogo, DeKUT

'''Project Description'''

In the following pages, we document the current state of work on the laboratory exercises in the four courses mentioned in the abstract.

#[[Signals and Communication|Signals and Communication]]
#[[Digital Signal Processing|Digital Signal Processing]]
#[[Instrumentation|Instrumentation]]
#[[Control Engineering|Control Engineering]]

'''Robotics and Outreach'''

One of the aims of the project is to expose primary and secondary school students to technology. We demonstrated a Raspberry Pi based robot at the Central Kenya ASK show. In addition, we introduced the young showgoers to computer programming using the Scratch programming language [https://scratch.mit.edu/about/ [1]]. 

[[File:Ask3.JPG]]

'''General System Setup'''

To effectively use the Raspberry pi, we must set up a number of systems and use a number of tools:

#[[Setting up internet access|Setting up internet access]]
#[[Audio setup|Audio setup]]
#[[Keyboard configuration|Keyboard configuration]]
#[[Remote login and file transfer|Remote login and file transfer]]

'''Important Tools'''

We have found the following tools useful so far during this project. We will update this list as often as possible

#Google forms 
#Bitbucket repository for collaboration
#Surveymonkey for anonymous online surveys

Department of Electrical Engineering, Dedan Kimathi University of Technology (DeKUT)

2015-09-11T21:36:42Z

Cmaina:

'''Project Title: Re-imagining Electrical Engineering Education Using The Raspberry Pi'''

'''Abstract'''

The current generation of microprocessors and microcontrollers have the potential to revolutionize electrical engineering education due to their low cost, small size and increased computing power. The Raspberry Pi is a cheap and powerful microprocessor with much of the functionality of a modern personal computer. In this project we plan to develop and implement laboratory exercises based on the Raspberry Pi for four electrical engineering courses at the Dedan Kimathi University of Technology. The courses are 1) Signals and Communication 2) Digital Signal Processing 3) Instrumentation and 4) Control Engineering. These laboratory exercises will expose the students to important areas in these courses using the Raspberry Pi as a computing platform and encourage them to use the device in their own projects outside the classroom. We will design detailed laboratory manuals and assess the value of the labs via student feedback and quantitative measures such as test scores. It is hoped that the laboratory exercises will be adopted by our institution and other universities offering electrical engineering.

[[File:Pi card.JPG|thumb|A Raspberry Pi Model B+. A Kenyan bank card is shown for comparison.]]

'''Personnel'''

#Dr. Ciira Maina[https://sites.google.com/site/cwamainadekut/ [1]], DeKUT
#Mr. Asaph Mbugua, DeKUT
#Dr. Kamau Gachigi, Gearbox and University of Nairobi[http://www.gearbox.co.ke/ [2]]
#Mr. James Abuogo, DeKUT

'''Project Description'''

In the following pages, we document the current state of work on the laboratory exercises in the four courses mentioned in the abstract.

#[[Signals and Communication|Signals and Communication]]
#[[Digital Signal Processing|Digital Signal Processing]]
#[[Instrumentation|Instrumentation]]
#[[Control Engineering|Control Engineering]]

'''Robotics and Outreach'''

One of the aims of the project is to expose primary and secondary school students to technology. We demonstrated a Raspberry Pi based robot at the Central Kenya ASK show. In addition, we introduced the young showgoers to computer programming using the Scratch programming language [https://scratch.mit.edu/about/ [1]]. 

[[File:Ask1.JPG|thumb|Ask3.JPG]]

'''General System Setup'''

To effectively use the Raspberry pi, we must set up a number of systems and use a number of tools:

#[[Setting up internet access|Setting up internet access]]
#[[Audio setup|Audio setup]]
#[[Keyboard configuration|Keyboard configuration]]
#[[Remote login and file transfer|Remote login and file transfer]]

'''Important Tools'''

We have found the following tools useful so far during this project. We will update this list as often as possible

#Google forms 
#Bitbucket repository for collaboration
#Surveymonkey for anonymous online surveys

File:Ask3.JPG

2015-09-11T21:35:08Z

Cmaina:

File:Ask2.JPG

2015-09-11T21:31:15Z

Cmaina:

File:Ask1.jpg

2015-09-11T21:27:11Z

Cmaina:

Department of Electrical Engineering, Dedan Kimathi University of Technology (DeKUT)

2015-09-11T21:25:42Z

Cmaina:

'''Project Title: Re-imagining Electrical Engineering Education Using The Raspberry Pi'''

'''Abstract'''

The current generation of microprocessors and microcontrollers have the potential to revolutionize electrical engineering education due to their low cost, small size and increased computing power. The Raspberry Pi is a cheap and powerful microprocessor with much of the functionality of a modern personal computer. In this project we plan to develop and implement laboratory exercises based on the Raspberry Pi for four electrical engineering courses at the Dedan Kimathi University of Technology. The courses are 1) Signals and Communication 2) Digital Signal Processing 3) Instrumentation and 4) Control Engineering. These laboratory exercises will expose the students to important areas in these courses using the Raspberry Pi as a computing platform and encourage them to use the device in their own projects outside the classroom. We will design detailed laboratory manuals and assess the value of the labs via student feedback and quantitative measures such as test scores. It is hoped that the laboratory exercises will be adopted by our institution and other universities offering electrical engineering.

[[File:Pi card.JPG|thumb|A Raspberry Pi Model B+. A Kenyan bank card is shown for comparison.]]

'''Personnel'''

#Dr. Ciira Maina[https://sites.google.com/site/cwamainadekut/ [1]], DeKUT
#Mr. Asaph Mbugua, DeKUT
#Dr. Kamau Gachigi, Gearbox and University of Nairobi[http://www.gearbox.co.ke/ [2]]
#Mr. James Abuogo, DeKUT

'''Project Description'''

In the following pages, we document the current state of work on the laboratory exercises in the four courses mentioned in the abstract.

#[[Signals and Communication|Signals and Communication]]
#[[Digital Signal Processing|Digital Signal Processing]]
#[[Instrumentation|Instrumentation]]
#[[Control Engineering|Control Engineering]]

'''Robotics and Outreach'''

One of the aims of the project is to expose primary and secondary school students to technology. We demonstrated a Raspberry Pi based robot at the Central Kenya ASK show. In addition, we introduced the young showgoers to computer programming using the Scratch programming language [https://scratch.mit.edu/about/]. 

[[File:Ask1.JPG|thumb]]

'''General System Setup'''

To effectively use the Raspberry pi, we must set up a number of systems and use a number of tools:

#[[Setting up internet access|Setting up internet access]]
#[[Audio setup|Audio setup]]
#[[Keyboard configuration|Keyboard configuration]]
#[[Remote login and file transfer|Remote login and file transfer]]

'''Important Tools'''

We have found the following tools useful so far during this project. We will update this list as often as possible

#Google forms 
#Bitbucket repository for collaboration
#Surveymonkey for anonymous online surveys

Department of Electrical Engineering, Dedan Kimathi University of Technology (DeKUT)

2015-09-11T21:20:17Z

Cmaina:

'''Project Title: Re-imagining Electrical Engineering Education Using The Raspberry Pi'''

'''Abstract'''

The current generation of microprocessors and microcontrollers have the potential to revolutionize electrical engineering education due to their low cost, small size and increased computing power. The Raspberry Pi is a cheap and powerful microprocessor with much of the functionality of a modern personal computer. In this project we plan to develop and implement laboratory exercises based on the Raspberry Pi for four electrical engineering courses at the Dedan Kimathi University of Technology. The courses are 1) Signals and Communication 2) Digital Signal Processing 3) Instrumentation and 4) Control Engineering. These laboratory exercises will expose the students to important areas in these courses using the Raspberry Pi as a computing platform and encourage them to use the device in their own projects outside the classroom. We will design detailed laboratory manuals and assess the value of the labs via student feedback and quantitative measures such as test scores. It is hoped that the laboratory exercises will be adopted by our institution and other universities offering electrical engineering.

[[File:Pi card.JPG|thumb|A Raspberry Pi Model B+. A Kenyan bank card is shown for comparison.]]

'''Personnel'''

#Dr. Ciira Maina[https://sites.google.com/site/cwamainadekut/ [1]], DeKUT
#Mr. Asaph Mbugua, DeKUT
#Dr. Kamau Gachigi, Gearbox and University of Nairobi[http://www.gearbox.co.ke/ [2]]
#Mr. James Abuogo, DeKUT

'''Project Description'''

In the following pages, we document the current state of work on the laboratory exercises in the four courses mentioned in the abstract.

#[[Signals and Communication|Signals and Communication]]
#[[Digital Signal Processing|Digital Signal Processing]]
#[[Instrumentation|Instrumentation]]
#[[Control Engineering|Control Engineering]]

'''Robotics and Outreach'''

One of the aims of the project is to expose primary and secondary school students to technology. We demonstrated a Raspberry Pi based robot at the Central Kenya ASK show. In addition, we introduced the young showgoers to computer programming using the Scratch programming language. 

[[File:Ask1.JPG]]

'''General System Setup'''

To effectively use the Raspberry pi, we must set up a number of systems and use a number of tools:

#[[Setting up internet access|Setting up internet access]]
#[[Audio setup|Audio setup]]
#[[Keyboard configuration|Keyboard configuration]]
#[[Remote login and file transfer|Remote login and file transfer]]

'''Important Tools'''

We have found the following tools useful so far during this project. We will update this list as often as possible

#Google forms 
#Bitbucket repository for collaboration
#Surveymonkey for anonymous online surveys

File:Ask1.JPG

2015-09-11T21:18:03Z

Cmaina: Cmaina uploaded a new version of File:Ask1.JPG

File:Ask1.JPG

2015-09-11T21:14:59Z

Cmaina: Cmaina uploaded a new version of File:Ask1.JPG

File:Ask1.JPG

2015-09-11T21:12:15Z

Cmaina:

Department of Electrical Engineering, Dedan Kimathi University of Technology (DeKUT)

2015-09-11T21:09:51Z

Cmaina:

'''Project Title: Re-imagining Electrical Engineering Education Using The Raspberry Pi'''

'''Abstract'''

The current generation of microprocessors and microcontrollers have the potential to revolutionize electrical engineering education due to their low cost, small size and increased computing power. The Raspberry Pi is a cheap and powerful microprocessor with much of the functionality of a modern personal computer. In this project we plan to develop and implement laboratory exercises based on the Raspberry Pi for four electrical engineering courses at the Dedan Kimathi University of Technology. The courses are 1) Signals and Communication 2) Digital Signal Processing 3) Instrumentation and 4) Control Engineering. These laboratory exercises will expose the students to important areas in these courses using the Raspberry Pi as a computing platform and encourage them to use the device in their own projects outside the classroom. We will design detailed laboratory manuals and assess the value of the labs via student feedback and quantitative measures such as test scores. It is hoped that the laboratory exercises will be adopted by our institution and other universities offering electrical engineering.

[[File:Pi card.JPG|thumb|A Raspberry Pi Model B+. A Kenyan bank card is shown for comparison.]]

'''Personnel'''

#Dr. Ciira Maina[https://sites.google.com/site/cwamainadekut/ [1]], DeKUT
#Mr. Asaph Mbugua, DeKUT
#Dr. Kamau Gachigi, Gearbox and University of Nairobi[http://www.gearbox.co.ke/ [2]]
#Mr. James Abuogo, DeKUT

'''Project Description'''

In the following pages, we document the current state of work on the laboratory exercises in the four courses mentioned in the abstract.

#[[Signals and Communication|Signals and Communication]]
#[[Digital Signal Processing|Digital Signal Processing]]
#[[Instrumentation|Instrumentation]]
#[[Control Engineering|Control Engineering]]

'''Robotics and Outreach'''

One of the aims of the project is to expose primary and secondary school students to technology. We demonstrated a Raspberry Pi based robot at the Central Kenya ASK show. In addition, we introduced the young showgoers to computer programming using the Scratch programming language. 

'''General System Setup'''

To effectively use the Raspberry pi, we must set up a number of systems and use a number of tools:

#[[Setting up internet access|Setting up internet access]]
#[[Audio setup|Audio setup]]
#[[Keyboard configuration|Keyboard configuration]]
#[[Remote login and file transfer|Remote login and file transfer]]

'''Important Tools'''

We have found the following tools useful so far during this project. We will update this list as often as possible

#Google forms 
#Bitbucket repository for collaboration
#Surveymonkey for anonymous online surveys

File:DSP lab3.pdf

2015-08-19T12:41:48Z

Cmaina:

Digital Signal Processing

2015-08-19T12:40:39Z

Cmaina:

Students at DeKUT are currently taught digital signal processing (DSP) in the final year of their five year program. The aim of the course is to introduce the student to a number of fundamental DSP concepts including:

[[File:Boot.JPG|thumb|Raspberry Pi and accessories.]]

#Discrete time signals and systems
#Linear time invariant (LTI) systems
#Frequency-domain representation of discrete time systems
#z-transform
#Sampling of continuous time signals
#Filter design
#The discrete Fourier transform

Currently, the laboratory exercises in this course are Matlab based and focus on learning how to manipulate discrete signals, plot frequency responses of digital LTI systems and design digital filters. These exercises are designed to ensure the students understand the theory of DSP. 

We propose to design a Raspberry Pi based DSP laboratory which will further enhance the understanding of these concepts by exposing the students to the processing of the human voice. A large number of DSP applications deal with speech processing and are now found in modern day electronics. These include speaker identification and speech identification. We aim to introduce the students to speech processing using a simple example, the estimation of fundamental frequency in a speech segment. It is hoped that this will motivate the students to explore more advanced applications such as speech recognition.

'''Background'''

Human speech is arguably one of the most important signals encountered in engineering applications. Numerous devices record and manipulate speech signals to achieve different ends. To properly manipulate the signal, it is important to have an understanding of the speech production process. The lungs, vocal tract and vocal cords all play an important role in speech production. The speech production model consists of an input signal from the lungs and a linear filter.  In this model, the input is a white noise process which is spectrally flat. This input is then spectrally shaped by a filter which models the properties of the vocal tract. Since the properties of the vocal tract are constantly changing as different sounds are produced, the filter is time varying. However, the filter is often modelled as quasi-stationary with filter parameters constant over a period of approximately 32ms. When the vocal cords vibrate as is the case when pronouncing the sound /a/ in cat, we say that the sound is voiced and in this case the signal is seen to be exhibit some periodicity. When the vocal cords do not vibrate the sound is unvoiced.

[[File:Mic.JPG|thumb|USB Microphone.]] [[File:Monitor.JPG|thumb|7 inch HDMI monitor.]]

'''Estimation of Fundamental Frequency'''

When speech is voiced, it is seen to exhibit periodicity and it is often important in speech applications to estimate the pitch of these signals. To achieve this, we estimate the ''fundamental frequency'' of this signal also refered to as ''F0''. A popular method for estimation of ''F0'' is based on the autocorrelation function (ACF). This function measures the similarity between samples at particular times and those obtained at particular time lags. If the signal is periodic we expect this function to have peaks at lags equivalent to integer multiples of the signal period in addition to a peak at zero lag. If we form a finite duration signal and compute the ACF, we notice that it has peaks at lags corresponding to integer multiples of the period. To apply this method to a speech signal, we compute the ACF of a finite duration signal corresponding to a speech segment 32ms long. Over this short segment the characteristics of the signal can be assumed to be stationary.

'''Preliminary Lab Development''' [[File:Spec.JPG|thumb|Complete experimental setup. A spectrogram of a recorded utterance is shown on the monitor.]]

Initial work has been done to test the proposed lab. Since the Raspberry Pi runs a linux OS, we tested the lab by organising a voluntary workshop which required students to bring their own laptops running linux (Ubuntu). In addition, the computers were loaded with

#Octave- A high level language suitable for numerical computations that is quite similar to Matlab. We will also require the signals package.
#SoX - Sound eXchange, the Swiss Army knife of audio manipulation  

Fourth year students were invited to attend the workshop and 27 students registered (we used google forms). Of these, 15 students attended the workshop which was held on 24th January, 2015.

A worksheet was prepared for use by the students and to guide them through the lab. It was designed to be hands on with students making recordings of their own voice and manipulating the recorded audio on Octave. 

After the workshop, an anonymous online survey [https://www.surveymonkey.com/s/JD7JTJ5 [1]] was conducted using surveymonkey to get feedback and help improve future workshops. The results of the survey were used to  fine tune the Raspberry Pi labs.

 '''Raspberry Pi Based Laboratory'''

Here we give a general description of the raspberry pi based laboratory exercise aimed at estimating fundamental frequency of a recorded speech segment.

'''Equipment'''

#Raspberry Pi Model B+
#USB Microphone 
#HDMI Monitor 
#Raspberry Pi Compatible Keyboard and Mouse

'''Set-up'''

To run the lab, we must install the following software (these will require an internet connection which can be achieved using a WiFi dongle)

#Octave: Type sudo apt-get install octave
#Octave signals package: Type sudo apt-get install octave-signal
#SoX: Type sudo apt-get install sox

'''Laboratory Exercises'''

There will be three laboratory exercises. They are

'''1. Introduction to Octave.''' 

Here the students will be introduced to the Octave programming language. The laboratory manual can be downloaded here [[File:DSP lab1.pdf|RTENOTITLE]]

'''2. Speech in the time and frequency domain'''

This is an introduction to speech processing  in the time and frequency domains. The laboratory manual can be downloaded here [[File:DSP lab2.pdf|RTENOTITLE]]

'''3.  Estimation of Fundamental Frequency'''

In this lab, students will be introduced to extraction of parameters from a speech signal. The laboratory manual can be downloaded here [[File:DSP lab3.pdf|RTENOTITLE]]
[[Category:Pages with broken file links]]

File:DSP lab2.pdf

2015-07-27T13:43:25Z

Cmaina:

Digital Signal Processing

2015-07-27T13:41:55Z

Cmaina:

Students at DeKUT are currently taught digital signal processing (DSP) in the final year of their five year program. The aim of the course is to introduce the student to a number of fundamental DSP concepts including:

[[File:Boot.JPG|thumb|Raspberry Pi and accessories.]]

#Discrete time signals and systems
#Linear time invariant (LTI) systems
#Frequency-domain representation of discrete time systems
#z-transform
#Sampling of continuous time signals
#Filter design
#The discrete Fourier transform

Currently, the laboratory exercises in this course are Matlab based and focus on learning how to manipulate discrete signals, plot frequency responses of digital LTI systems and design digital filters. These exercises are designed to ensure the students understand the theory of DSP. 

We propose to design a Raspberry Pi based DSP laboratory which will further enhance the understanding of these concepts by exposing the students to the processing of the human voice. A large number of DSP applications deal with speech processing and are now found in modern day electronics. These include speaker identification and speech identification. We aim to introduce the students to speech processing using a simple example, the estimation of fundamental frequency in a speech segment. It is hoped that this will motivate the students to explore more advanced applications such as speech recognition.

'''Background'''

Human speech is arguably one of the most important signals encountered in engineering applications. Numerous devices record and manipulate speech signals to achieve different ends. To properly manipulate the signal, it is important to have an understanding of the speech production process. The lungs, vocal tract and vocal cords all play an important role in speech production. The speech production model consists of an input signal from the lungs and a linear filter.  In this model, the input is a white noise process which is spectrally flat. This input is then spectrally shaped by a filter which models the properties of the vocal tract. Since the properties of the vocal tract are constantly changing as different sounds are produced, the filter is time varying. However, the filter is often modelled as quasi-stationary with filter parameters constant over a period of approximately 32ms. When the vocal cords vibrate as is the case when pronouncing the sound /a/ in cat, we say that the sound is voiced and in this case the signal is seen to be exhibit some periodicity. When the vocal cords do not vibrate the sound is unvoiced.

[[File:Mic.JPG|thumb|USB Microphone.]] [[File:Monitor.JPG|thumb|7 inch HDMI monitor.]]

'''Estimation of Fundamental Frequency'''

When speech is voiced, it is seen to exhibit periodicity and it is often important in speech applications to estimate the pitch of these signals. To achieve this, we estimate the ''fundamental frequency'' of this signal also refered to as ''F0''. A popular method for estimation of ''F0'' is based on the autocorrelation function (ACF). This function measures the similarity between samples at particular times and those obtained at particular time lags. If the signal is periodic we expect this function to have peaks at lags equivalent to integer multiples of the signal period in addition to a peak at zero lag. If we form a finite duration signal and compute the ACF, we notice that it has peaks at lags corresponding to integer multiples of the period. To apply this method to a speech signal, we compute the ACF of a finite duration signal corresponding to a speech segment 32ms long. Over this short segment the characteristics of the signal can be assumed to be stationary.

'''Preliminary Lab Development''' [[File:Spec.JPG|thumb|Complete experimental setup. A spectrogram of a recorded utterance is shown on the monitor.]]

Initial work has been done to test the proposed lab. Since the Raspberry Pi runs a linux OS, we tested the lab by organising a voluntary workshop which required students to bring their own laptops running linux (Ubuntu). In addition, the computers were loaded with

#Octave- A high level language suitable for numerical computations that is quite similar to Matlab. We will also require the signals package.
#SoX - Sound eXchange, the Swiss Army knife of audio manipulation  

Fourth year students were invited to attend the workshop and 27 students registered (we used google forms). Of these, 15 students attended the workshop which was held on 24th January, 2015.

A worksheet was prepared for use by the students and to guide them through the lab. It was designed to be hands on with students making recordings of their own voice and manipulating the recorded audio on Octave. 

After the workshop, an anonymous online survey [https://www.surveymonkey.com/s/JD7JTJ5 [1]] was conducted using surveymonkey to get feedback and help improve future workshops. The results of the survey were used to  fine tune the Raspberry Pi labs.

 '''Raspberry Pi Based Laboratory'''

Here we give a general description of the raspberry pi based laboratory exercise aimed at estimating fundamental frequency of a recorded speech segment.

'''Equipment'''

#Raspberry Pi Model B+
#USB Microphone 
#HDMI Monitor 
#Raspberry Pi Compatible Keyboard and Mouse

'''Set-up'''

To run the lab, we must install the following software (these will require an internet connection which can be achieved using a WiFi dongle)

#Octave: Type sudo apt-get install octave
#Octave signals package: Type sudo apt-get install octave-signal
#SoX: Type sudo apt-get install sox

'''Laboratory Exercises'''

There will be three laboratory exercises. They are

'''1. Introduction to Octave.''' 

Here the students will be introduced to the Octave programming language. The laboratory manual can be downloaded here [[File:DSP lab1.pdf|RTENOTITLE]]

'''2. Speech in the time and frequency domain'''

This is an introduction to speech processing  in the time and frequency domains. The laboratory manual can be downloaded here [[File:DSP lab2.pdf|RTENOTITLE]]

'''3.  Estimation of Fundamental Frequency'''

In this lab, students will be introduced to extraction of parameters from a speech signal. The laboratory manual can be downloaded here [[File:DSP lab1.pdf|RTENOTITLE]]
[[Category:Pages with broken file links]]

Digital Signal Processing

2015-06-29T14:25:34Z

Cmaina:

Students at DeKUT are currently taught digital signal processing (DSP) in the final year of their five year program. The aim of the course is to introduce the student to a number of fundamental DSP concepts including:

[[File:Boot.JPG|thumb|Raspberry Pi and accessories.]]

#Discrete time signals and systems
#Linear time invariant (LTI) systems
#Frequency-domain representation of discrete time systems
#z-transform
#Sampling of continuous time signals
#Filter design
#The discrete Fourier transform

Currently, the laboratory exercises in this course are Matlab based and focus on learning how to manipulate discrete signals, plot frequency responses of digital LTI systems and design digital filters. These exercises are designed to ensure the students understand the theory of DSP. 

We propose to design a Raspberry Pi based DSP laboratory which will further enhance the understanding of these concepts by exposing the students to the processing of the human voice. A large number of DSP applications deal with speech processing and are now found in modern day electronics. These include speaker identification and speech identification. We aim to introduce the students to speech processing using a simple example, the estimation of fundamental frequency in a speech segment. It is hoped that this will motivate the students to explore more advanced applications such as speech recognition.

'''Background'''

Human speech is arguably one of the most important signals encountered in engineering applications. Numerous devices record and manipulate speech signals to achieve different ends. To properly manipulate the signal, it is important to have an understanding of the speech production process. The lungs, vocal tract and vocal cords all play an important role in speech production. The speech production model consists of an input signal from the lungs and a linear filter.  In this model, the input is a white noise process which is spectrally flat. This input is then spectrally shaped by a filter which models the properties of the vocal tract. Since the properties of the vocal tract are constantly changing as different sounds are produced, the filter is time varying. However, the filter is often modelled as quasi-stationary with filter parameters constant over a period of approximately 32ms. When the vocal cords vibrate as is the case when pronouncing the sound /a/ in cat, we say that the sound is voiced and in this case the signal is seen to be exhibit some periodicity. When the vocal cords do not vibrate the sound is unvoiced.

[[File:Mic.JPG|thumb|USB Microphone.]] [[File:Monitor.JPG|thumb|7 inch HDMI monitor.]]

'''Estimation of Fundamental Frequency'''

When speech is voiced, it is seen to exhibit periodicity and it is often important in speech applications to estimate the pitch of these signals. To achieve this, we estimate the ''fundamental frequency'' of this signal also refered to as ''F0''. A popular method for estimation of ''F0'' is based on the autocorrelation function (ACF). This function measures the similarity between samples at particular times and those obtained at particular time lags. If the signal is periodic we expect this function to have peaks at lags equivalent to integer multiples of the signal period in addition to a peak at zero lag. If we form a finite duration signal and compute the ACF, we notice that it has peaks at lags corresponding to integer multiples of the period. To apply this method to a speech signal, we compute the ACF of a finite duration signal corresponding to a speech segment 32ms long. Over this short segment the characteristics of the signal can be assumed to be stationary.

'''Preliminary Lab Development''' [[File:Spec.JPG|thumb|Complete experimental setup. A spectrogram of a recorded utterance is shown on the monitor.]]

Initial work has been done to test the proposed lab. Since the Raspberry Pi runs a linux OS, we tested the lab by organising a voluntary workshop which required students to bring their own laptops running linux (Ubuntu). In addition, the computers were loaded with

#Octave- A high level language suitable for numerical computations that is quite similar to Matlab. We will also require the signals package.
#SoX - Sound eXchange, the Swiss Army knife of audio manipulation  

Fourth year students were invited to attend the workshop and 27 students registered (we used google forms). Of these, 15 students attended the workshop which was held on 24th January, 2015.

A worksheet was prepared for use by the students and to guide them through the lab. It was designed to be hands on with students making recordings of their own voice and manipulating the recorded audio on Octave. 

After the workshop, an anonymous online survey [https://www.surveymonkey.com/s/JD7JTJ5 [1]] was conducted using surveymonkey to get feedback and help improve future workshops. The results of the survey were used to  fine tune the Raspberry Pi labs.

 '''Raspberry Pi Based Laboratory'''

Here we give a general description of the raspberry pi based laboratory exercise aimed at estimating fundamental frequency of a recorded speech segment.

'''Equipment'''

#Raspberry Pi Model B+
#USB Microphone 
#HDMI Monitor 
#Raspberry Pi Compatible Keyboard and Mouse

'''Set-up'''

To run the lab, we must install the following software (these will require an internet connection which can be achieved using a WiFi dongle)

#Octave: Type sudo apt-get install octave
#Octave signals package: Type sudo apt-get install octave-signal
#SoX: Type sudo apt-get install sox

'''Laboratory Exercises'''

There will be three laboratory exercises. They are

'''1. Introduction to Octave.''' 

Here the students will be introduced to the Octave programming language. The laboratory manual can be downloaded here [[File:DSP lab1.pdf|RTENOTITLE]]

'''2. Speech in the time and frequency domain'''

This is an introduction to speech processing  in the time and frequency domains. The laboratory manual can be downloaded here [[File:DSP lab1.pdf|RTENOTITLE]]

'''3.  Estimation of Fundamental Frequency'''

In this lab, students will be introduced to extraction of parameters from a speech signal. The laboratory manual can be downloaded here [[File:DSP lab1.pdf|RTENOTITLE]]
[[Category:Pages with broken file links]]

Signals and Communication

2015-06-29T10:46:14Z

Cmaina:

'''Signals and Communication'''

This course is taught in the third year of the electrical engineering curriculum. After an introduction to the classification and mathematical analysis of signals in both the time and frequency domains, the course introduces analogue modulation schemes such as amplitude modulation (AM) and frequency modulation (FM). We propose to enhance the laboratory exercises in this course by introducing the students to the concept of software defined radio (SDR) using the Raspberry Pi and designing two laboratory exercises that implement SDR on a Raspberry Pi. We first briefly introduce SDR and then describe the two laboratory exercises.

'''Software Defined Radio'''

 SDR is a communication system framework that moves all the signal processing in current radio systems from dedicated hardware modules to software. Therefore the same hardware system is capable of implementing several modulation schemes by simply changing the controlling software. An SDR system consists of an antenna, an analogue-to-digital converter which converts the radio frequency (RF) signal to digital samples and software which manipulates these samples to retrieve the information 

 SDR has become popular with electronics hobbyists because it was discovered that cheap USB receivers (also known as dongles) designed to receive digital TV broadcasts could be turned into SDR receivers allowing access to samples of analogue RF signals. These samples could then be processed using appropriate software. A popular dongle is the DVB-T TV tuner dongle based on the RTL2832U chipset which retails for about $20.

[[File:Sdr1.jpg|thumb|SDR Dongle connected to a Raspberry Pi Model B+.]]

With one of these cheap dongles, it is possible to implement different communication systems. In fact a large community of hobbyists has emerged and a number of their projects are freely available online (see [http://www.rtl-sdr.com/about-rtl-sdr/} http://www.rtl-sdr.com/about-rtl-sdr/]). An open source driver rtl-sdr is also available for linux based systems. This software allows the user to tune to a particular frequency in the range of the dongle's tuner (27-1700 MHz for the DVB-T TV tuner) and to obtain samples of the in-phase and quadrature components of the RF signal. These samples can then be appropriately processed to recover the message signal.

'''Software Setup'''

In order to run the laboratory exercises, we will need to install the rtl-sdr driver which turns the DVB-T TV tuner dongle into a software defined radio. You can obtain the source for the driver here [[https://github.com/steve-m/librtlsdr https://github.com/steve-m/librtlsdr]]. To check out the repository type

<code>git clone [git://github.com/steve-m/librtlsdr.git git://github.com/steve-m/librtlsdr.git]</code>

Once the code is downloaded. Follow these instructions [http://sdr.osmocom.org/trac/wiki/rtl-sdr [1]]. You will need to have installed cmake and libusb1.0. You can do this by typing

<code>sudo apt-get install cmake</code>

and

<code>sudo apt-get install libusb-1.0-0-dev</code>

'''Laboratory Exercises'''

There will be three laboratory exercises in this course. The labs are listed below with 

'''1. Introduction to python'''

In this lab, students will be introduced to python. This knowledge will be useful for the subsequent labs. Download the manual here [[:media:SigCommLab1.pdf]]

 '''2. FM Signal Demodulation'''

In FM systems, a baseband message signal modifies the instantaneous frequency of the carrier signal. This laboratory exercise will expose the students to FM demodulation using SDR.

File:DSP lab1.pdf

2015-06-29T09:29:15Z

Cmaina:

Digital Signal Processing

2015-06-29T09:26:17Z

Cmaina:

Students at DeKUT are currently taught digital signal processing (DSP) in the final year of their five year program. The aim of the course is to introduce the student to a number of fundamental DSP concepts including:

[[File:Boot.JPG|thumb|Raspberry Pi and accessories.]]

#Discrete time signals and systems
#Linear time invariant (LTI) systems
#Frequency-domain representation of discrete time systems
#z-transform
#Sampling of continuous time signals
#Filter design
#The discrete Fourier transform

Currently, the laboratory exercises in this course are Matlab based and focus on learning how to manipulate discrete signals, plot frequency responses of digital LTI systems and design digital filters. These exercises are designed to ensure the students understand the theory of DSP. 

We propose to design a Raspberry Pi based DSP laboratory which will further enhance the understanding of these concepts by exposing the students to the processing of the human voice. A large number of DSP applications deal with speech processing and are now found in modern day electronics. These include speaker identification and speech identification. We aim to introduce the students to speech processing using a simple example, the estimation of fundamental frequency in a speech segment. It is hoped that this will motivate the students to explore more advanced applications such as speech recognition.

'''Background'''

Human speech is arguably one of the most important signals encountered in engineering applications. Numerous devices record and manipulate speech signals to achieve different ends. To properly manipulate the signal, it is important to have an understanding of the speech production process. The lungs, vocal tract and vocal cords all play an important role in speech production. The speech production model consists of an input signal from the lungs and a linear filter.  In this model, the input is a white noise process which is spectrally flat. This input is then spectrally shaped by a filter which models the properties of the vocal tract. Since the properties of the vocal tract are constantly changing as different sounds are produced, the filter is time varying. However, the filter is often modelled as quasi-stationary with filter parameters constant over a period of approximately 32ms. When the vocal cords vibrate as is the case when pronouncing the sound /a/ in cat, we say that the sound is voiced and in this case the signal is seen to be exhibit some periodicity. When the vocal cords do not vibrate the sound is unvoiced.

[[File:Mic.JPG|thumb|USB Microphone.]] [[File:Monitor.JPG|thumb|7 inch HDMI monitor.]]

'''Estimation of Fundamental Frequency'''

When speech is voiced, it is seen to exhibit periodicity and it is often important in speech applications to estimate the pitch of these signals. To achieve this, we estimate the ''fundamental frequency'' of this signal also refered to as ''F0''. A popular method for estimation of ''F0'' is based on the autocorrelation function (ACF). This function measures the similarity between samples at particular times and those obtained at particular time lags. If the signal is periodic we expect this function to have peaks at lags equivalent to integer multiples of the signal period in addition to a peak at zero lag. If we form a finite duration signal and compute the ACF, we notice that it has peaks at lags corresponding to integer multiples of the period. To apply this method to a speech signal, we compute the ACF of a finite duration signal corresponding to a speech segment 32ms long. Over this short segment the characteristics of the signal can be assumed to be stationary.

'''Preliminary Lab Development''' [[File:Spec.JPG|thumb|Complete experimental setup. A spectrogram of a recorded utterance is shown on the monitor.]] Initial work has been done to test the proposed lab. Since the Raspberry Pi runs a linux OS, we tested the lab by organising a voluntary workshop which required students to bring their own laptops running linux (Ubuntu). In addition, the computers were loaded with

#Octave- A high level language suitable for numerical computations that is quite similar to Matlab. We will also require the signals package.
#SoX - Sound eXchange, the Swiss Army knife of audio manipulation  

Fourth year students were invited to attend the workshop and 27 students registered (we used google forms). Of these, 15 students attended the workshop which was held on 24th January, 2015.

A worksheet was prepared for use by the students and to guide them through the lab. It was designed to be hands on with students making recordings of their own voice and manipulating the recorded audio on Octave. 

After the workshop, an anonymous online survey [https://www.surveymonkey.com/s/JD7JTJ5 [1]] was conducted using surveymonkey to get feedback and help improve future workshops. The results of the survey were used to  fine tune the Raspberry Pi labs.

 '''Raspberry Pi Based Laboratory'''

Here we give a general description of the raspberry pi based laboratory exercise aimed at estimating fundamental frequency of a recorded speech segment.

'''Equipment'''

#Raspberry Pi Model B+
#USB Microphone 
#HDMI Monitor 
#Raspberry Pi Compatible Keyboard and Mouse

'''Set-up'''

To run the lab, we must install the following software (these will require an internet connection which can be achieved using a WiFi dongle)

#Octave: Type sudo apt-get install octave
#Octave signals package: Type sudo apt-get install octave-signal
#SoX: Type sudo apt-get install sox

'''Laboratory Exercises'''

There will be three laboratory exercises. They are

'''1. Introduction to Octave.''' 

Here the students will be introduced to the Octave programming language. The laboratory manual can be downloaded here [[File:DSP lab1.pdf|RTENOTITLE]]

'''2. Speech in the time and frequency domain'''

This is an introduction to speech processing  in the time and frequency domains. The laboratory manual can be downloaded here [[File:DSP lab1.pdf|RTENOTITLE]]

'''3.  Estimation of Fundamental Frequency'''

In this lab, students will be introduced to extraction of parameters from a speech signal. The laboratory manual can be downloaded here [[File:DSP lab1.pdf|RTENOTITLE]]
[[Category:Pages with broken file links]]

Digital Signal Processing

2015-06-29T09:25:33Z

Cmaina:

Students at DeKUT are currently taught digital signal processing (DSP) in the final year of their five year program. The aim of the course is to introduce the student to a number of fundamental DSP concepts including:

[[File:Boot.JPG|thumb|Raspberry Pi and accessories.]]

#Discrete time signals and systems
#Linear time invariant (LTI) systems
#Frequency-domain representation of discrete time systems
#z-transform
#Sampling of continuous time signals
#Filter design
#The discrete Fourier transform

Currently, the laboratory exercises in this course are Matlab based and focus on learning how to manipulate discrete signals, plot frequency responses of digital LTI systems and design digital filters. These exercises are designed to ensure the students understand the theory of DSP. 

We propose to design a Raspberry Pi based DSP laboratory which will further enhance the understanding of these concepts by exposing the students to the processing of the human voice. A large number of DSP applications deal with speech processing and are now found in modern day electronics. These include speaker identification and speech identification. We aim to introduce the students to speech processing using a simple example, the estimation of fundamental frequency in a speech segment. It is hoped that this will motivate the students to explore more advanced applications such as speech recognition.

'''Background'''

Human speech is arguably one of the most important signals encountered in engineering applications. Numerous devices record and manipulate speech signals to achieve different ends. To properly manipulate the signal, it is important to have an understanding of the speech production process. The lungs, vocal tract and vocal cords all play an important role in speech production. The speech production model consists of an input signal from the lungs and a linear filter.  In this model, the input is a white noise process which is spectrally flat. This input is then spectrally shaped by a filter which models the properties of the vocal tract. Since the properties of the vocal tract are constantly changing as different sounds are produced, the filter is time varying. However, the filter is often modelled as quasi-stationary with filter parameters constant over a period of approximately 32ms. When the vocal cords vibrate as is the case when pronouncing the sound /a/ in cat, we say that the sound is voiced and in this case the signal is seen to be exhibit some periodicity. When the vocal cords do not vibrate the sound is unvoiced.

[[File:Mic.JPG|thumb|USB Microphone.]] [[File:Monitor.JPG|thumb|7 inch HDMI monitor.]]

'''Estimation of Fundamental Frequency'''

When speech is voiced, it is seen to exhibit periodicity and it is often important in speech applications to estimate the pitch of these signals. To achieve this, we estimate the ''fundamental frequency'' of this signal also refered to as ''F0''. A popular method for estimation of ''F0'' is based on the autocorrelation function (ACF). This function measures the similarity between samples at particular times and those obtained at particular time lags. If the signal is periodic we expect this function to have peaks at lags equivalent to integer multiples of the signal period in addition to a peak at zero lag. If we form a finite duration signal and compute the ACF, we notice that it has peaks at lags corresponding to integer multiples of the period. To apply this method to a speech signal, we compute the ACF of a finite duration signal corresponding to a speech segment 32ms long. Over this short segment the characteristics of the signal can be assumed to be stationary.

'''Preliminary Lab Development''' [[File:Spec.JPG|thumb|Complete experimental setup. A spectrogram of a recorded utterance is shown on the monitor.]] Initial work has been done to test the proposed lab. Since the Raspberry Pi runs a linux OS, we tested the lab by organising a voluntary workshop which required students to bring their own laptops running linux (Ubuntu). In addition, the computers were loaded with

#Octave- A high level language suitable for numerical computations that is quite similar to Matlab. We will also require the signals package.
#SoX - Sound eXchange, the Swiss Army knife of audio manipulation  

Fourth year students were invited to attend the workshop and 27 students registered (we used google forms). Of these, 15 students attended the workshop which was held on 24th January, 2015.

A worksheet was prepared for use by the students and to guide them through the lab. It was designed to be hands on with students making recordings of their own voice and manipulating the recorded audio on Octave. 

After the workshop, an anonymous online survey [https://www.surveymonkey.com/s/JD7JTJ5 [1]] was conducted using surveymonkey to get feedback and help improve future workshops. The results of the survey were used to  fine tune the Raspberry Pi labs.

 '''Raspberry Pi Based Laboratory'''

Here we give a general description of the raspberry pi based laboratory exercise aimed at estimating fundamental frequency of a recorded speech segment.

'''Equipment'''

#Raspberry Pi Model B+
#USB Microphone 
#HDMI Monitor 
#Raspberry Pi Compatible Keyboard and Mouse

'''Set-up'''

To run the lab, we must install the following software (these will require an internet connection which can be achieved using a WiFi dongle)

#Octave: Type sudo apt-get install octave
#Octave signals package: Type sudo apt-get install octave-signal
#SoX: Type sudo apt-get install sox

'''Laboratory Exercises'''

There will be three laboratory exercises. They are

1. Introduction to Octave. 

Here the students will be introduced to the Octave programming language. The laboratory manual can be downloaded here [[File:DSP_lab1.pdf]]

2. Speech in the time and frequency domain

This is an introduction to speech processing  in the time and frequency domains. The laboratory manual can be downloaded here [[File:DSP_lab1.pdf]]

3.  Estimation of Fundamental Frequency

In this lab, students will be introduced to extraction of parameters from a speech signal. The laboratory manual can be downloaded here [[File:DSP_lab1.pdf]]

Digital Signal Processing

2015-06-29T09:24:05Z

Cmaina:

Students at DeKUT are currently taught digital signal processing (DSP) in the final year of their five year program. The aim of the course is to introduce the student to a number of fundamental DSP concepts including:

[[File:Boot.JPG|thumb|Raspberry Pi and accessories.]]

#Discrete time signals and systems
#Linear time invariant (LTI) systems
#Frequency-domain representation of discrete time systems
#z-transform
#Sampling of continuous time signals
#Filter design
#The discrete Fourier transform

Currently, the laboratory exercises in this course are Matlab based and focus on learning how to manipulate discrete signals, plot frequency responses of digital LTI systems and design digital filters. These exercises are designed to ensure the students understand the theory of DSP. 

We propose to design a Raspberry Pi based DSP laboratory which will further enhance the understanding of these concepts by exposing the students to the processing of the human voice. A large number of DSP applications deal with speech processing and are now found in modern day electronics. These include speaker identification and speech identification. We aim to introduce the students to speech processing using a simple example, the estimation of fundamental frequency in a speech segment. It is hoped that this will motivate the students to explore more advanced applications such as speech recognition.

'''Background'''

Human speech is arguably one of the most important signals encountered in engineering applications. Numerous devices record and manipulate speech signals to achieve different ends. To properly manipulate the signal, it is important to have an understanding of the speech production process. The lungs, vocal tract and vocal cords all play an important role in speech production. The speech production model consists of an input signal from the lungs and a linear filter.  In this model, the input is a white noise process which is spectrally flat. This input is then spectrally shaped by a filter which models the properties of the vocal tract. Since the properties of the vocal tract are constantly changing as different sounds are produced, the filter is time varying. However, the filter is often modelled as quasi-stationary with filter parameters constant over a period of approximately 32ms. When the vocal cords vibrate as is the case when pronouncing the sound /a/ in cat, we say that the sound is voiced and in this case the signal is seen to be exhibit some periodicity. When the vocal cords do not vibrate the sound is unvoiced.

[[File:Mic.JPG|thumb|USB Microphone.]] [[File:Monitor.JPG|thumb|7 inch HDMI monitor.]]

'''Estimation of Fundamental Frequency'''

When speech is voiced, it is seen to exhibit periodicity and it is often important in speech applications to estimate the pitch of these signals. To achieve this, we estimate the ''fundamental frequency'' of this signal also refered to as ''F0''. A popular method for estimation of ''F0'' is based on the autocorrelation function (ACF). This function measures the similarity between samples at particular times and those obtained at particular time lags. If the signal is periodic we expect this function to have peaks at lags equivalent to integer multiples of the signal period in addition to a peak at zero lag. If we form a finite duration signal and compute the ACF, we notice that it has peaks at lags corresponding to integer multiples of the period. To apply this method to a speech signal, we compute the ACF of a finite duration signal corresponding to a speech segment 32ms long. Over this short segment the characteristics of the signal can be assumed to be stationary.

'''Preliminary Lab Development''' [[File:Spec.JPG|thumb|Complete experimental setup. A spectrogram of a recorded utterance is shown on the monitor.]] Initial work has been done to test the proposed lab. Since the Raspberry Pi runs a linux OS, we tested the lab by organising a voluntary workshop which required students to bring their own laptops running linux (Ubuntu). In addition, the computers were loaded with

#Octave- A high level language suitable for numerical computations that is quite similar to Matlab. We will also require the signals package.
#SoX - Sound eXchange, the Swiss Army knife of audio manipulation  

Fourth year students were invited to attend the workshop and 27 students registered (we used google forms). Of these, 15 students attended the workshop which was held on 24th January, 2015.

A worksheet was prepared for use by the students and to guide them through the lab. It was designed to be hands on with students making recordings of their own voice and manipulating the recorded audio on Octave. 

After the workshop, an anonymous online survey [https://www.surveymonkey.com/s/JD7JTJ5 [1]] was conducted using surveymonkey to get feedback and help improve future workshops. The results of the survey were used to  fine tune the Raspberry Pi labs.

 '''Raspberry Pi Based Laboratory'''

Here we give a general description of the raspberry pi based laboratory exercise aimed at estimating fundamental frequency of a recorded speech segment.

'''Equipment'''

#Raspberry Pi Model B+
#USB Microphone 
#HDMI Monitor 
#Raspberry Pi Compatible Keyboard and Mouse

'''Set-up'''

To run the lab, we must install the following software (these will require an internet connection which can be achieved using a WiFi dongle)

#Octave: Type sudo apt-get install octave
#Octave signals package: Type sudo apt-get install octave-signal
#SoX: Type sudo apt-get install sox

'''Laboratory Exercises'''

There will be three laboratory exercises. They are

1. Introduction to Octave. 

Here the students will be introduced to the Octave programming language. The laboratory manual can be downloaded here [[file:DSP_lab1.pdf]]

2. Speech in the time and frequency domain

This is an introduction to speech processing  in the time and frequency domains. The laboratory manual can be downloaded here [[file:DSP_lab2.pdf]]

3.  Estimation of Fundamental Frequency

In this lab, students will be introduced to extraction of parameters from a speech signal. The laboratory manual can be downloaded here [[file:DSP_lab3.pdf]]

''''''

Signals and Communication

2015-06-29T08:58:02Z

Cmaina:

'''Signals and Communication'''

This course is taught in the third year of the electrical engineering curriculum. After an introduction to the classification and mathematical analysis of signals in both the time and frequency domains, the course introduces analogue modulation schemes such as amplitude modulation (AM) and frequency modulation (FM). We propose to enhance the laboratory exercises in this course by introducing the students to the concept of software defined radio (SDR) using the Raspberry Pi and designing two laboratory exercises that implement SDR on a Raspberry Pi. We first briefly introduce SDR and then describe the two laboratory exercises.

'''Software Defined Radio'''

 SDR is a communication system framework that moves all the signal processing in current radio systems from dedicated hardware modules to software. Therefore the same hardware system is capable of implementing several modulation schemes by simply changing the controlling software. An SDR system consists of an antenna, an analogue-to-digital converter which converts the radio frequency (RF) signal to digital samples and software which manipulates these samples to retrieve the information 

 SDR has become popular with electronics hobbyists because it was discovered that cheap USB receivers (also known as dongles) designed to receive digital TV broadcasts could be turned into SDR receivers allowing access to samples of analogue RF signals. These samples could then be processed using appropriate software. A popular dongle is the DVB-T TV tuner dongle based on the RTL2832U chipset which retails for about $20.

[[File:Sdr1.jpg|thumb|SDR Dongle connecte to a Raspberry Pi Model B+.]]

With one of these cheap dongles, it is possible to implement different communication systems. In fact a large community of hobbyists has emerged and a number of their projects are freely available online (see [http://www.rtl-sdr.com/about-rtl-sdr/} http://www.rtl-sdr.com/about-rtl-sdr/]). An open source driver rtl-sdr is also available for linux based systems. This software allows the user to tune to a particular frequency in the range of the dongle's tuner (27-1700 MHz for the DVB-T TV tuner) and to obtain samples of the in-phase and quadrature components of the RF signal. These samples can then be appropriately processed to recover the message signal.

'''Software Setup'''

In order to run the laboratory exercises, we will need to install the rtl-sdr driver which turns the DVB-T TV tuner dongle into a software defined radio. You can obtain the source for the driver here [[https://github.com/steve-m/librtlsdr https://github.com/steve-m/librtlsdr]]. To check out the repository type

<code>git clone [git://github.com/steve-m/librtlsdr.git git://github.com/steve-m/librtlsdr.git]</code>

Once the code is downloaded. Follow these instructions [http://sdr.osmocom.org/trac/wiki/rtl-sdr [1]]. You will need to have installed cmake and libusb1.0. You can do this by typing

<code>sudo apt-get install cmake</code>

and

<code>sudo apt-get install libusb-1.0-0-dev</code>

'''Laboratory Exercises'''

There will be three laboratory exercises in this course. The labs are listed below with 

'''1. Introduction to python'''

In this lab, students will be introduced to python. This knowledge will be useful for the subsequent labs. Download the manual here [[media:SigCommLab1.pdf]]

 '''2. FM Signal Demodulation'''

In FM systems, a baseband message signal modifies the instantaneous frequency of the carrier signal. This laboratory exercise will expose the students to FM demodulation using SDR.

Signals and Communication

2015-06-29T08:37:57Z

Cmaina:

'''Signals and Communication'''

This course is taught in the third year of the electrical engineering curriculum. After an introduction to the classification and mathematical analysis of signals in both the time and frequency domains, the course introduces analogue modulation schemes such as amplitude modulation (AM) and frequency modulation (FM). We propose to enhance the laboratory exercises in this course by introducing the students to the concept of software defined radio (SDR) using the Raspberry Pi and designing two laboratory exercises that implement SDR on a Raspberry Pi. We first briefly introduce SDR and then describe the two laboratory exercises.

'''Software Defined Radio'''

 SDR is a communication system framework that moves all the signal processing in current radio systems from dedicated hardware modules to software. Therefore the same hardware system is capable of implementing several modulation schemes by simply changing the controlling software. An SDR system consists of an antenna, an analogue-to-digital converter which converts the radio frequency (RF) signal to digital samples and software which manipulates these samples to retrieve the information 

 SDR has become popular with electronics hobbyists because it was discovered that cheap USB receivers (also known as dongles) designed to receive digital TV broadcasts could be turned into SDR receivers allowing access to samples of analogue RF signals. These samples could then be processed using appropriate software. A popular dongle is the DVB-T TV tuner dongle based on the RTL2832U chipset which retails for about $20.

[[File:sdr1.jpg|thumb|SDR Dongle connecte to a Raspberry Pi Model B+.]]

With one of these cheap dongles, it is possible to implement different communication systems. In fact a large community of hobbyists has emerged and a number of their projects are freely available online (see [http://www.rtl-sdr.com/about-rtl-sdr/} http://www.rtl-sdr.com/about-rtl-sdr/]). An open source driver rtl-sdr is also available for linux based systems. This software allows the user to tune to a particular frequency in the range of the dongle's tuner (27-1700 MHz for the DVB-T TV tuner) and to obtain samples of the in-phase and quadrature components of the RF signal. These samples can then be appropriately processed to recover the message signal.

'''Software Setup'''

In order to run the laboratory exercises, we will need to install the rtl-sdr driver which turns the DVB-T TV tuner dongle into a software defined radio. You can obtain the source for the driver here [[https://github.com/steve-m/librtlsdr https://github.com/steve-m/librtlsdr]]. To check out the repository type

<code>git clone [git://github.com/steve-m/librtlsdr.git git://github.com/steve-m/librtlsdr.git]</code>

Once the code is downloaded. Follow these instructions [http://sdr.osmocom.org/trac/wiki/rtl-sdr [1]]. You will need to have installed cmake and libusb1.0. You can do this by typing

<code>sudo apt-get install cmake</code>

and

<code>sudo apt-get install libusb-1.0-0-dev</code>

'''Laboratory Exercises'''

There will be three laboratory exercises in this course. The labs are listed below with 

'''1. Introduction to python'''

In this lab, students will be introduced to python. This knowledge will be useful for the subsequent labs. Download the manual here []

 '''2. FM Signal Demodulation'''

In FM systems, a baseband message signal modifies the instantaneous frequency of the carrier signal. This laboratory exercise will expose the students to FM demodulation using SDR.

Signals and Communication

2015-06-29T08:35:01Z

Cmaina:

'''Signals and Communication'''

This course is taught in the third year of the electrical engineering curriculum. After an introduction to the classification and mathematical analysis of signals in both the time and frequency domains, the course introduces analogue modulation schemes such as amplitude modulation (AM) and frequency modulation (FM). We propose to enhance the laboratory exercises in this course by introducing the students to the concept of software defined radio (SDR) using the Raspberry Pi and designing two laboratory exercises that implement SDR on a Raspberry Pi. We first briefly introduce SDR and then describe the two laboratory exercises.

'''Software Defined Radio'''

 SDR is a communication system framework that moves all the signal processing in current radio systems from dedicated hardware modules to software. Therefore the same hardware system is capable of implementing several modulation schemes by simply changing the controlling software. An SDR system consists of an antenna, an analogue-to-digital converter which converts the radio frequency (RF) signal to digital samples and software which manipulates these samples to retrieve the information 

 SDR has become popular with electronics hobbyists because it was discovered that cheap USB receivers (also known as dongles) designed to receive digital TV broadcasts could be turned into SDR receivers allowing access to samples of analogue RF signals. These samples could then be processed using appropriate software. A popular dongle is the DVB-T TV tuner dongle based on the RTL2832U chipset which retails for about $20.

With one of these cheap dongles, it is possible to implement different communication systems. In fact a large community of hobbyists has emerged and a number of their projects are freely available online (see [http://www.rtl-sdr.com/about-rtl-sdr/} http://www.rtl-sdr.com/about-rtl-sdr/]). An open source driver rtl-sdr is also available for linux based systems. This software allows the user to tune to a particular frequency in the range of the dongle's tuner (27-1700 MHz for the DVB-T TV tuner) and to obtain samples of the in-phase and quadrature components of the RF signal. These samples can then be appropriately processed to recover the message signal.

'''Software Setup'''

In order to run the laboratory exercises, we will need to install the rtl-sdr driver which turns the DVB-T TV tuner dongle into a software defined radio. You can obtain the source for the driver here [[https://github.com/steve-m/librtlsdr https://github.com/steve-m/librtlsdr]]. To check out the repository type

<code>git clone [git://github.com/steve-m/librtlsdr.git git://github.com/steve-m/librtlsdr.git]</code>

Once the code is downloaded. Follow these instructions [http://sdr.osmocom.org/trac/wiki/rtl-sdr [1]]. You will need to have installed cmake and libusb1.0. You can do this by typing

<code>sudo apt-get install cmake</code>

and

<code>sudo apt-get install libusb-1.0-0-dev</code>

'''Laboratory Exercises'''

There will be three laboratory exercises in this course. The labs are listed below with 

'''1. Introduction to python'''

In this lab, students will be introduced to python. This knowledge will be useful for the subsequent labs. Download the manual here []

 '''2. FM Signal Demodulation'''

In FM systems, a baseband message signal modifies the instantaneous frequency of the carrier signal. This laboratory exercise will expose the students to FM demodulation using SDR.

File:Sdr1.jpg

2015-06-29T08:31:58Z

Cmaina:

Signals and Communication

2015-06-29T08:29:17Z

Cmaina:

'''Signals and Communication'''

This course is taught in the third year of the electrical engineering curriculum. After an introduction to the classification and mathematical analysis of signals in both the time and frequency domains, the course introduces analogue modulation schemes such as amplitude modulation (AM) and frequency modulation (FM). We propose to enhance the laboratory exercises in this course by introducing the students to the concept of software defined radio (SDR) using the Raspberry Pi and designing two laboratory exercises that implement SDR on a Raspberry Pi. We first briefly introduce SDR and then describe the two laboratory exercises.

'''Software Defined Radio'''

 SDR is a communication system framework that moves all the signal processing in current radio systems from dedicated hardware modules to software. Therefore the same hardware system is capable of implementing several modulation schemes by simply changing the controlling software. An SDR system consists of an antenna, an analogue-to-digital converter which converts the radio frequency (RF) signal to digital samples and software which manipulates these samples to retrieve the information 

 SDR has become popular with electronics hobbyists because it was discovered that cheap USB receivers (also known as dongles) designed to receive digital TV broadcasts could be turned into SDR receivers allowing access to samples of analogue RF signals. These samples could then be processed using appropriate software. A popular dongle is the DVB-T TV tuner dongle based on the RTL2832U chipset which retails for about $20.

With one of these cheap dongles, it is possible to implement different communication systems. In fact a large community of hobbyists has emerged and a number of their projects are freely available online (see [http://www.rtl-sdr.com/about-rtl-sdr/} http://www.rtl-sdr.com/about-rtl-sdr/]). An open source driver rtl-sdr is also available for linux based systems. This software allows the user to tune to a particular frequency in the range of the dongle's tuner (27-1700 MHz for the DVB-T TV tuner) and to obtain samples of the in-phase and quadrature components of the RF signal. These samples can then be appropriately processed to recover the message signal.

'''Software Setup'''

In order to run the laboratory exercises, we will need to install the rtl-sdr driver which turns the DVB-T TV tuner dongle into a software defined radio. You can obtain the source for the driver here [[https://github.com/steve-m/librtlsdr https://github.com/steve-m/librtlsdr]]. To check out the repository type

<code>git clone [git://github.com/steve-m/librtlsdr.git git://github.com/steve-m/librtlsdr.git]</code>

Once the code is downloaded. Follow these instructions [http://sdr.osmocom.org/trac/wiki/rtl-sdr [1]]. You will need to have installed cmake and libusb1.0. You can do this by typing

<code>sudo apt-get install cmake</code>

and

<code>sudo apt-get install libusb-1.0-0-dev</code>

<code></code>

<code></code>'''Laboratory Exercises'''

There will be three laboratory exercises in this course. The labs are listed below with 

'''1. Introduction to python''' In this lab, students will be introduced to python. This knowledge will be useful for the subsequent labs. Download the manual here []

 '''2. FM Signal Demodulation'''

In FM systems, a baseband message signal modifies the instantaneous frequency of the carrier signal. This laboratory exercise will expose the students to FM demodulation using SDR.

Signals and Communication

2015-06-29T08:28:50Z

Cmaina:

'''Signals and Communication'''

This course is taught in the third year of the electrical engineering curriculum. After an introduction to the classification and mathematical analysis of signals in both the time and frequency domains, the course introduces analogue modulation schemes such as amplitude modulation (AM) and frequency modulation (FM). We propose to enhance the laboratory exercises in this course by introducing the students to the concept of software defined radio (SDR) using the Raspberry Pi and designing two laboratory exercises that implement SDR on a Raspberry Pi. We first briefly introduce SDR and then describe the two laboratory exercises.

'''Software Defined Radio'''

 SDR is a communication system framework that moves all the signal processing in current radio systems from dedicated hardware modules to software. Therefore the same hardware system is capable of implementing several modulation schemes by simply changing the controlling software. An SDR system consists of an antenna, an analogue-to-digital converter which converts the radio frequency (RF) signal to digital samples and software which manipulates these samples to retrieve the information 

 SDR has become popular with electronics hobbyists because it was discovered that cheap USB receivers (also known as dongles) designed to receive digital TV broadcasts could be turned into SDR receivers allowing access to samples of analogue RF signals. These samples could then be processed using appropriate software. A popular dongle is the DVB-T TV tuner dongle based on the RTL2832U chipset which retails for about $20.

With one of these cheap dongles, it is possible to implement different communication systems. In fact a large community of hobbyists has emerged and a number of their projects are freely available online (see [http://www.rtl-sdr.com/about-rtl-sdr/} http://www.rtl-sdr.com/about-rtl-sdr/]). An open source driver rtl-sdr is also available for linux based systems. This software allows the user to tune to a particular frequency in the range of the dongle's tuner (27-1700 MHz for the DVB-T TV tuner) and to obtain samples of the in-phase and quadrature components of the RF signal. These samples can then be appropriately processed to recover the message signal.

'''Software Setup'''

In order to run the laboratory exercises, we will need to install the rtl-sdr driver which turns the DVB-T TV tuner dongle into a software defined radio. You can obtain the source for the driver here [[https://github.com/steve-m/librtlsdr https://github.com/steve-m/librtlsdr]]. To check out the repository type

<code>git clone [git://github.com/steve-m/librtlsdr.git git://github.com/steve-m/librtlsdr.git]</code>

Once the code is downloaded. Follow these instructions [http://sdr.osmocom.org/trac/wiki/rtl-sdr [1]]. You will need to have installed cmake and libusb1.0. You can do this by typing

<code>sudo apt-get install cmake</code>

and

<code>sudo apt-get install libusb-1.0-0-dev</code>

'''Laboratory Exercises'''

There will be three laboratory exercises in this course. The labs are listed below with 

'''1. Introduction to python''' In this lab, students will be introduced to python. This knowledge will be useful for the subsequent labs. Download the manual here []

 '''2. FM Signal Demodulation'''

In FM systems, a baseband message signal modifies the instantaneous frequency of the carrier signal. This laboratory exercise will expose the students to FM demodulation using SDR.

Signals and Communication

2015-06-29T08:27:59Z

Cmaina:

'''Signals and Communication'''

This course is taught in the third year of the electrical engineering curriculum. After an introduction to the classification and mathematical analysis of signals in both the time and frequency domains, the course introduces analogue modulation schemes such as amplitude modulation (AM) and frequency modulation (FM). We propose to enhance the laboratory exercises in this course by introducing the students to the concept of software defined radio (SDR) using the Raspberry Pi and designing two laboratory exercises that implement SDR on a Raspberry Pi. We first briefly introduce SDR and then describe the two laboratory exercises.

'''Software Defined Radio'''

 SDR is a communication system framework that moves all the signal processing in current radio systems from dedicated hardware modules to software. Therefore the same hardware system is capable of implementing several modulation schemes by simply changing the controlling software. An SDR system consists of an antenna, an analogue-to-digital converter which converts the radio frequency (RF) signal to digital samples and software which manipulates these samples to retrieve the information 

 SDR has become popular with electronics hobbyists because it was discovered that cheap USB receivers (also known as dongles) designed to receive digital TV broadcasts could be turned into SDR receivers allowing access to samples of analogue RF signals. These samples could then be processed using appropriate software. A popular dongle is the DVB-T TV tuner dongle based on the RTL2832U chipset which retails for about $20.

With one of these cheap dongles, it is possible to implement different communication systems. In fact a large community of hobbyists has emerged and a number of their projects are freely available online (see [http://www.rtl-sdr.com/about-rtl-sdr/} http://www.rtl-sdr.com/about-rtl-sdr/]). An open source driver rtl-sdr is also available for linux based systems. This software allows the user to tune to a particular frequency in the range of the dongle's tuner (27-1700 MHz for the DVB-T TV tuner) and to obtain samples of the in-phase and quadrature components of the RF signal. These samples can then be appropriately processed to recover the message signal.

'''Software Setup'''

In order to run the laboratory exercises, we will need to install the rtl-sdr driver which turns the DVB-T TV tuner dongle into a software defined radio. You can obtain the source for the driver here [[https://github.com/steve-m/librtlsdr https://github.com/steve-m/librtlsdr]]. To check out the repository type

<code>git clone [git://github.com/steve-m/librtlsdr.git git://github.com/steve-m/librtlsdr.git]</code>

Once the code is downloaded. Follow these instructions [http://sdr.osmocom.org/trac/wiki/rtl-sdr [1]]. You will need to have installed cmake and libusb1.0. You can do this by typing

<code>sudo apt-get install cmake</code>

and

<code>sudo apt-get install libusb-1.0-0-dev</code>

= '''Laboratory Exercises''' =
There will be three laboratory exercises in this course. The labs are listed below with 

'''1. Introduction to python'''
In this lab, students will be introduced to python. This knowledge will be useful for the subsequent labs. Download the manual here []

 '''2. FM Signal Demodulation'''

In FM systems, a baseband message signal modifies the instantaneous frequency of the carrier signal. This laboratory exercise will expose the students to FM demodulation using SDR.

Audio setup

2015-04-29T12:48:12Z

Cmaina:

For a number of experiments we will need to manipulate audio signals with the Raspberry Pi. Here we give a few hints on how to get audio to work.

'''Audio Input'''

In order to record audio, we need to connect a microphone to the Pi. If you connect a USB mic, you can ensure that the Pi recognizes it by typing lsusb at the command line

<code>pi@raspberrypi ~ $ lsusb</code> <code>Bus 001 Device 002: ID 0424:9514 Standard Microsystems Corp. Bus 001 Device 001: ID 1d6b:0002 Linux Foundation 2.0 root hub Bus 001 Device 003: ID 0424:ec00 Standard Microsystems Corp. Bus 001 Device 004: ID 0000:0538 Bus 001 Device 006: ID 0d8c:013c C-Media Electronics, Inc. CM108 Audio Controller Bus 001 Device 005: ID 1c4f:0002 SiGma Micro Keyboard TRACER Gamma Ivory</code>

Here we have connected the C-Media USB Microphone.

You can obtain the device details by typing arecord -l

<code>pi@raspberrypi ~ $ arecord -l</code>

<code>**** List of CAPTURE Hardware Devices ****</code>

<code>card 1: Device [USB PnP Sound Device], device 0: USB Audio [USB Audio]</code>

<code> Subdevices: 1/1

Subdevice #0: subdevice #0

</code>
These device details will be useful in recording audio.

'''Installing SoX for audio recording'''

SoX is a program for recording and manipulating audio. You can install it by typing 

sudo apt-get install sox

at the command line. There are two functions play and rec which can then be used for recording and playback. To record some speech, follow the following steps

#set the audio driver by typing export AUDIODRIVER=alsa
#set the recoding device by typing export AUDIODEV=hw:<card number>,<device number>. The card and device numbers of the recording device are obtained from arecord -l. Using the result above we type export AUDIODEV=hw:1,0
#Record some audio by typing rec -c 1 -r 8000 speech.wav trim 0 2 and pressing Enter. This command will record a single channel at 8kHz and save the resulting speech in speech.wav. The recording will last 2 seconds.

'''Audio Output'''

To playback the audio recorded, we follow the following steps

#Plug in a set of head phones in the audio jack.
#Set the audio output to the headphones by typing amixer cset numid=3 1 at the command line .
#Determine the playback device details using aplay -l 
#Set the audio device using  AUDIODEV=hw:<card number>,<device number>.
#Type play speech.wav
#If the volume is too low type alsamixer and adjust the volume using the arrow keys.

Audio setup

2015-04-29T12:46:27Z

Cmaina:

For a number of experiments we will need to manipulate audio signals with the Raspberry Pi. Here we give a few hints on how to get audio to work.

'''Audio Input'''

In order to record audio, we need to connect a microphone to the Pi. If you connect a USB mic, you can ensure that the Pi recognizes it by typing lsusb at the command line

<code>pi@raspberrypi ~ $ lsusb</code> <code>Bus 001 Device 002: ID 0424:9514 Standard Microsystems Corp. Bus 001 Device 001: ID 1d6b:0002 Linux Foundation 2.0 root hub Bus 001 Device 003: ID 0424:ec00 Standard Microsystems Corp. Bus 001 Device 004: ID 0000:0538 Bus 001 Device 006: ID 0d8c:013c C-Media Electronics, Inc. CM108 Audio Controller Bus 001 Device 005: ID 1c4f:0002 SiGma Micro Keyboard TRACER Gamma Ivory</code>

Here we have connected the C-Media USB Microphone.

You can obtain the device details by typing arecord -l

<code>pi@raspberrypi ~ $ arecord -l</code>

<code>**** List of CAPTURE Hardware Devices ****</code>

<code>card 1: Device [USB PnP Sound Device], device 0: USB Audio [USB Audio]</code>

<code> Subdevices: 1/1

Subdevice #0: subdevice #0

</code>
These device details will be useful in recording audio.

'''Installing SoX for audio recording'''

SoX is a program for recording and manipulating audio. You can install it by typing 

sudo apt-get install sox

at the command line. There are two function play and rec which can then be used for recording and playback. To record some speech, follow the following steps

#set the audio driver by typing export AUDIODRIVER=alsa
#set the recoding device by typing export AUDIODEV=hw:<card number>,<device number>. The card and device numbers of the recording device are obtained from arecord -l. Using the result above we type export AUDIODEV=hw:1,0
#Record some audio by typing rec -c 1 -r 8000 speech.wav trim 0 2and pressing Enter. This command will record a single channel at 8kHz and save the resulting speech in speech.wav. The recording will last 2 seconds.

'''Audio Output'''

To playback the audio recorded, we follow the following steps

#Plug in a set of head phones in the audio jack.
#Set the audio output to the headphones by typing amixer cset numid=3 1 at the command line .
#Determine the playback device details using aplay -l 
#Set the audio device using  AUDIODEV=hw:<card number>,<device number>.
#Type play speech.wav
#If the volume is too low type alsamixer and adjust the volume using the arrow keys.

Audio setup

2015-04-29T12:45:54Z

Cmaina:

For a number of experiments we will need to manipulate audio signals with the Raspberry Pi. Here we give a few hints on how to get audio to work.

'''Audio Input'''

In order to record audio, we need to connect a microphone to the Pi. If you connect a USB mic, you can ensure that the Pi recognizes it by typing lsusb at the command line

<code>pi@raspberrypi ~ $ lsusb</code> <code>Bus 001 Device 002: ID 0424:9514 Standard Microsystems Corp. Bus 001 Device 001: ID 1d6b:0002 Linux Foundation 2.0 root hub Bus 001 Device 003: ID 0424:ec00 Standard Microsystems Corp. Bus 001 Device 004: ID 0000:0538 Bus 001 Device 006: ID 0d8c:013c C-Media Electronics, Inc. CM108 Audio Controller Bus 001 Device 005: ID 1c4f:0002 SiGma Micro Keyboard TRACER Gamma Ivory</code>

Here we have connected the C-Media USB Microphone.

You can obtain the device details by typing arecord -l

<code>pi@raspberrypi ~ $ arecord -l</code>

<code>**** List of CAPTURE Hardware Devices ****</code>

<code>card 1: Device [USB PnP Sound Device], device 0: USB Audio [USB Audio]</code>

<code> Subdevices: 1/1

Subdevice #0: subdevice #0

</code>
These device details will be useful in recording audio.

'''Installing SoX for audio recording'''

SoX is a program for recording and manipulating audio. You can install it by typing 

sudo apt-get install sox

at the command line. There are two function play and rec which can then be used for recording and playback. To record some speech, follow the following steps

#set the audio driver by typing export AUDIODRIVER=alsa
#set the recoding device by typing export AUDIODEV=hw:<card number>,<device number>. The card and device numbers of the recording device are obtained from arecord -l. Using the result above we type export AUDIODEV=hw:1,0
#Record some audio by typing rec -c 1 -r 8000 speech.wav trim 0 2and pressing Enter. This command will record a single channel at 8kHz and save the resulting speech in speech.wav. The recording will last 2 seconds.

Audio Output

To playback the audio recorded, we follow the following steps

#Plug in a set of head phones in the audio jack.
#Set the audio output to the headphones by typing amixer cset numid=3 1 at the command line .
#Determine the playback device details using aplay -l 
#Set the audio device using  AUDIODEV=hw:<card number>,<device number>.
#Type play speech.wav
#If the volume is too low type alsamixer and adjust the volume using the arrow keys.