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.

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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 designs with actual equipment and by a set of practical laboratory exercises. Accessible to students of computer science and electrical/electronic engineering.

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Level 5 (MEng) activities include designing robots to meet various challenges. In this laboratory, teams of students compete to build robots that can navigate a maze. The robot shown is based on an Arduino AT-Mega with sensors and software designed by students.

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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.

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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.

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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, the Raspberry Pi wirelessly communicates with the car's microcontroller to stop and turn in a specific direction, before resuming driving straight.

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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.

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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 is used as a teaching demoinstration and is sometimes displayed at University Open days.

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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.

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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.

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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.

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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 designed boards that were manufactured using the University 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 Level 4 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. .

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This level 4 project by Kieran Mackay designed, built and evaluated hardware and software to test an equipment control bus. It designed a pair of printed cirucit boards to interface for an Arduino Mega in RS Designspark 8.0. The 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.

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This level 4 project investigated hardware and software aspects of three-dimensional mapping of the surroundings using the Kinect IR camera.

An algorithm retrieved camera sensor readings, and displayed them using the OpenNI2 and OpenCV open-source libraries. Each scene is segmentated by scanning the depth image to split the captured scene into separate objects based on their location within the environment.

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LoRaWAN is a Low Power Wide Area Network protocol for radio communication. This MEng level 4 project investigated using this to provide building environmental monitoring providing telemetry from the Internet of Things (IoT). An experimental approach developed various prototypes and integrating with a GPS receiver to allow teh deviceb to track GPS location. The video records a morning test trip to log the radio coverage provided by our campus IoT network.

MP4 Video (PC or Mac)