EEE Student Design Videos

This page contains a small selection of EEE student projects, with links to videos showing the work.

Level 3 EEE Design

Students explore hardware and software design in the Level 3 EE3579 Electronics Design. Starting with similar hardware and similar objectives. Each team of two or three students work in teams to design software to assemble a microcontroller-based model car using motors to drive/steer the vehicle using ultrasound sensors to detect obstacles and navigate the car to avoid colliding with these obstacles.

This set of student-made videos demo the results obtained by two student groups.

QuickTime Video (Mac)

MP4 Video (PC)

The course EE3580 on digital systems develops understanding of implementation methods to realise a digital design, supported by practical examples that address real-world problems. The syllabus includes the principles of digital systems, hardware implementation, finite state machines and applications in digital communications and robotics.

Students design software, and hardware for a finite state machine with sensors. They make their design using the School's rapid printed circuit board prototyping facility and test this with their software. This video shows one such design for a heat-sensor alarm. A thermal sensor measures the temperature, and when close to a laptop fan, this reaches a configured thershold, triggering an audible alarm.

QuickTime Video (.mov Mac)

EE3576 is a short course teaching the fundamentals of digital communications engineering. The lectures and laboratories focus on remote control of equipment using an industry communication bus.  This starts with a description of the data received from a GPS device (to identify location and time), then studies the Digital Multiplex (DMX) control bus (a standard in the live entertainment industry) followed the Controller Area Network (CAN) used in various transport and industrial control applications.

Teaching and tutorials are supported by demonstrations of deisgns with actual equipment and by a set of practical laboratory exercises. Accessible to students of computer science and electrical/electronic engineering.

PC or QuickTime Video (Mac)

Level 4 EEE Individual Project

All Level 4 students complete an individual honours project. In their project each student needs to design, specify and test components of system. Sometimes this work is theoretical or it may involve analysis of experimental engineering data,. Many EEE students see their design through to practical evaluation of the finished system. The available projects cover a range of topics change year-by-year – often related to the teaching activities or research of the staff who supervise them, or a project linked to an industrial use-case.

Some examples of project work are presented in the videos below.

A Level 4 project designed a microcontroller-based board for lighting and stage control protocol in theatres and for live entertainment. Microcontroller implementation makes it feasible to build complex systems controlled from a single control bus.

This project explored use of the AVR microcontroller, implemented a ZIF programmer for the chip, and used this to design a receiver board for remote operation of a relay. This design has since been used for equipment at public events.

QuickTime Video (Mac)

MP4 Video (PC)

This project designed and built an interface to a remote-controlled video camera. This utilised an Arduino controller to interface a high-quality SVHS camera pan-tilt-zoom (PTZ) camera to a control bus. After analysis of the Sony VISCA interface, the student designed hardware and software to receive and process a control signal to operate the camera. This enabled the camera to be remotely operated. A working prototype was used to support video-streaming research.

QuickTime Video (Mac)

A Level 4 student project designed and built a remote-controlled battery electric car.

Software developed by students and running on a microcontroller at the front of the vehicle governs the steering and a spearate controller at the rear controls the drive power. The first test of the complete prototype is shown in the video.

MP4 Video (PC or Mac)

Angel Iliev (2016) designed and implemented a camera-based navigation system. A Raspberry-Pi microcomputer above a test area, provided a bird’s eye view of a small self-driven model car. The student developed a navigation algorithm using the camera that recognised the position and direction of travel of the car. This ensured the car stayed within the limits of a target area (bounded by black lines). When it approaches the bounds of the area, the Raspberry Pi wirelessly communicates with the car's microcontroller to stop and turn in a specific direction, before it resumes driving straight.

QuickTime Video (Mac)

MP4 Video (PC)

Scott McDougal designed and implemented the object-tracking algorithm being tested in the video. A PC-equipped with a camera mounted on a servo motor executes the tracking algorithm. This identifies a target (a yellow tennis ball in the video) in the camera field of view (shown on the monitor). The algorithm recognized the position of the target and communicates with the Arduino microcontroller controller using a servo motor to maintain the target at the centre of the video frame. The work complimented research in video-based monitoring of the environment.

QuickTime Video (Mac)

MP4 Video (PC)

Adam Elphinstone developed a LED matrix display based on an a three colour LED Pixel in 2014.

A matrix of LED pixels was interfaced this to a control surface that mapped video to the pixels. One challenge was to define a colour palette to compress the pixel information to be send over a serial long-distance control bus 300m distance to the display). The completed matrix has been used for teaching and is frequently displayed at University Open days.

Video

A 2017 Level 4 project by Pavel Dobrev completed a complete design for a DMX-based power distribution controller for 8 high current circuits using a 32A three phase supply.

The project developed a series of electronics boards with a front panel to monitor the power distribution system.  Remote control was provided via a control bus. The student designed temperature monitoring and control circuits to allow the unit to be placed in a 19” rack enclosure.

Quicktime Video (Mac)

MP4 Video (PC)

William Duthie developed a practical theatre gobo rotator in 2017 to provide computer-based control with indexing for rotational control of the image projected by a lighting fixture.

The design used Designspark software to design boards that were manufactured using the PCB milling machine. The system was based on Arduino Mega 2560 hardware and a H-bridge motor circuit. Analysis confirmed a linear relationship between the voltage and either motor RPM or angular rotation. An additional unit was later produced for use by the University.

MP4 Video (PC or Mac)

A 2018 project explored the communications aspects of the Philips Hue environment. Using a Philips Hue bridge, smart LED lights were controlled by implementing a gateway to Art-Net using software developed on a Raspberry Pi. The project constructed a smart wireless home power switch design using the NXP processor. This was integrated into a Hue network by developing an interface using Zigbee. The video shows the testing of the final design using using the Ethernet-based ArtNet control bus to connect to 3 connected bulbs in a wireless smart home network.

MP4 Video (PC or Mac)

Adam Elphinstone developed a LED matrix display based on an a three colour LED Pixel in 2014.

He designed a matrix of LED pixels and interfaced this to a control surface that map video and other control signals to the LED pixel outputs. One challenge was to define a colour palette that could compress the matrix pixel information allowing data to be sent over a serial control bus that was limited to 250 kbps. The completed matrix is used for teaching and is frequently displayed at University Open days.

Quicktime Video (Mac)

MP4 Video (PC)

A 2017 Level 4 project by Pavel Dobrev completed a design for a high power distribution controller using a 32A three phase supply. The project developed electronics boards controlled by a Arduino controller from a front panel that monitors the power distribution system.  Remote control was provided via an isolated RS-485 interface. Temperature monitoring and control circuits to allow the unit to be placed in an industry-standard 19” rack enclosure.

Quicktime Video (Mac)

MP4 Video (PC)

William Duthie developed a practical Theatre Gobo Rotator in 2017 to provide computer-based control with indexing for rotational control of the image projected by a lighting fixture.

The design used Designspark software to design boards that were manufactured using the University of Aberdeen PCB milling machine. The system was based on open source Arduino Mega 2560 hardware combined with a H-bridge motor control circuit providing precise control of the sppeed of rotation or the angular position. An additional unit was produced for use by the University.

MP4 Video (PC or Mac)

This project investigated and implemented a camera-based tracking system. A camera was mounted on two servo motors (adjusting pan and tilt) and interfaced to a processing unit (laptop) that analyses the video to identify and then steer the camera to follow a target as it moves. The system identifies the target using distinctive colours not present in the background this colour information is dynamically adjusted to account for variations in the ambient light. .

MP4 Video (PC or Mac)

The 2018 level 4 project by Kieran Mackay designed, built and evaluated hardware and software to test an equipment control bus. The project designed a pair of printed cirucit boards to interface for an Arduino Mega in RS Designspark 8.0 These prototypes and a final design were manufactured using the School of Engineering rapid prototyping PCB milling machine. Together with the designed software, the final unit realises a complete handheld battery powered communications tester.

MP4 Video (PC or Mac)

A 2018 project investigated three-dimensional mapping of the surroundings using the Kinect IR camera. This investigated the operating principles of the camera, the hardware and software requirements and the concepts behind design of a 3D-mapping system.

The project created an algorithm to retrieve camera sensor readings, and display and store them using the OpenNI2 and OpenCV open-source libraries. A scene is segmentated by scanning the depth image to split the captured scene into separate objects based on their location within the environment.

MP4 Video (PC or Mac)