An exceptional student from the University of West of Scotland has been named Young Software Engineer of the Year 2019. Stuart Adams won first prize for an innovative project describing the mathematical theory behind modern photorealistic rendering and contributes to the field of computer graphics by showing a simple, practical implementation of physically-based rendering.
Second place was won by Euan Reid from Abertay University for his work on using IoT technology to regulate consumption from EV charge points. Teodora Georgescu from the University of Edinburgh won third place with an innovative project investigating the classification of coughs using wearable devices.
The Leidos Software Engineering Project Award went to Alessio Gadaleta from Robert Gordon University for his project on designing, developing and implementing a deck planning tool for the oil and gas industry using artificial intelligence.
The Young Software Engineer of the Year Awards, now in their 30th year, are given to the best undergraduate software projects, drawn from across all students studying computing science and software engineering in Scotland. Each university submits the best final year undergraduate software engineering project from amongst their students.
The Awards are organised by ScotlandIS, the trade body for the digital technologies industry and were presented at the ScotSoft2019 dinner, with over 550 guests from across the industry.
Brilliant young minds making breakthroughs in computing science and programming:
University of the West of Scotland
“Real-Time Physically-Based Rendering”
Stuart came to the University of the West of Scotland’s Computer Games Technology course through West College Scotland, where he completed an HND in Computer Games Development. At UWS, he showed particular aptitude within modules centred on graphics programming and high performance computing; he was also elected president of the Game Development Society
His project Real-Time Physically-Based Rendering describes the mathematical theory behind modern photorealistic rendering and the practical implementation of a real-time physically based rendering system.
The new renderer, ‘Moka’, implements complex shading techniques used by video games and movies to produce photorealistic materials. Moka uses a physically plausible model of a material’s microscopic structure and applies electromagnetic theory to create a correct distribution of reflected light.
The project is cross-platform and can run on Windows or Linux desktops. It is written in C++17 and OpenGL. It is open-source and freely available to be read, modified and redistributed by anyone who wishes to learn about modern graphics techniques.
This project contributes to the field of computer graphics by showing a simple, practical implementation of physically-based rendering in OpenGL. It tests the implementation against a leading commercial game engine to evaluate the physically-based approach and determine if the development efforts were successful.
The judges considered this project to be exceptional. As overall winner of the Young Software Engineer of the Year Award received a cheque for £2500 from Sopra Steria, and a trophy from ScotlandIS.
“Utilsing IoT technology to regulate existing EV charge points for the prevention of distribution network overloading”
With sales of electric and plug-in hybrid vehicles increasing at an exponential rate, concerns regarding the impact they may have on electrical distribution networks are becoming ever more pressing. Utilizing IoT technologies to dynamically schedule EV charging could serve as a cost-effective alternative to extensive redevelopment of the country’s electrical distribution networks.
This project aimed to investigate how IoT capable devices could be integrated into existing EV charging infrastructure, to operate as an effective method for averting electrical distribution network overloading. A prototype IoT device was developed that integrates directly with existing EV charge points to monitor and control their charge state. This was paired with a backend charge management system, which periodically determines which EVs will have permission to charge in a way that prevents the distribution network they’re connected to from becoming overloaded.
The system not only prevented the simulated distributed network from becoming overloaded through combined use of the charge management system and IoT devices, but also to undertake this while fairly splitting charge time between all EV chargers on the system.
The results from this project demonstrated that integrating smart charging capabilities into existing EV charging infrastructure can be used to monitor and control vehicle charging when developing EV charge management systems for distribution networks.
The judges were impressed by this smart solution to a complex, current technology challenge and considered Euan to be a well deserved runner-up. He received a cheque for £2000 from sponsor BCS, and a trophy from ScotlandIS.
University of Edinburgh
“Classification of Coughs using the Wearable RESpeck Monitor”
Respiratory illnesses ranging from upper airways infections to obstructive disorders such as COPD and asthma can be managed by monitoring respiratory events, such as normal and obstructive breathing, and coughs. Respiratory event monitoring is still a task mainly carried out by close personal observations or using physically intrusive monitoring devices, such as nasal cannulae or chest straps. Cough detection has only been attempted successfully using microphones, although the classification accuracy is high, this method fails to capture any other respiratory events, is prone to error due to background noise and can be personally intrusive to patients.
This project aimed to address the weaknesses of existing methods by automatically detecting coughs, in addition to normal breathing and movement detection, using the Respeck device (developed in the School of Informatics, University of Edinburgh) worn unobtrusively as a plaster by patients. The accelerometer and gyroscope sensors record the movement of the rib cage continuously at 25Hz which is transmitted wirelessly to a paired Android mobile device.
Labelled respiratory events and movement data were collected from a range of participants wearing the Respeck to record breathing and coughing, when stationary, walking or running. Models were developed incrementally for detecting coughing episodes by identifying and analysing amplitude and frequency features in the sensor signals. The resulting cough detector with an accuracy of 96.12% in the stationary case was able to differentiate coughing from other events such as laughing, talking or eating, which perturb the chest rotations in similar ways.
Teodora’s project has pushed the state-of-the-art in cough monitoring detection methods and realised an accurate cough monitor which can now be used in clinical trials in respiratory and pulmonary medicine.
Teodora won third prize for her well executed project, a cheque for £1500 from sponsor Edge Testing and a trophy from ScotlandIS.
Robert Gordon University
“Artificial Intelligence and Deck Planning in the Oil and Gas Industry”
Deck planning is the activity of deciding the positioning of cargoes on a vessel. It is traditionally considered a difficult and time-consuming task made harder by the necessity to adhere to legal and practical constraints; additionally, inefficiencies in the process may lead to severe economic damages including delays in the production, the need for additional vessels and human costs.
The aim of the project was to design, implement and evaluate a software tool able to automatically generate two-dimensional deck plans for vessels in the oil and gas industry which, while adhering to legal and practical constraints, maximise the load of the vessel area, allowing the opportunity to perform the same set of deliveries with a smaller number of vessels.
The software is designed and implemented as a web service which makes its functionality available to other systems and a virtually infinite number of possible applications including commercial and educational tools. It is also designed to improve the easiness of maintainability and future expandability thanks to the use of modern design patterns.
The project includes the evaluation of different artificial intelligence algorithms, the most successful of which was the implementation of a Hybrid Simulated Annealing together with Fast Layer-Based Heuristic which in the end allowed the production of a high-quality solution in a very short amount of time (i.e. less than 10 seconds for 100 cargoes).
The judges were impressed by the quality of this project and its adherence to best practice software engineering principles, and awarded Alessio the Leidos Software Engineering Award.
In addition to the Award, Alessio received a cheque for £1500 donated by Leidos, and the Leidos Trophy was given to his university, and Robert Gordon University.