Updating and extending the Roundware server: Roundare is a contributory augmented reality system that has been used as the technical foundation for a variety of art installations. The server API is implemented in python using the Django framework and requires updating to support modern versions. Moreover, containerisation of the platform is highly desirable so that new installations can be deployed quickly. The objective of this project would be to moderniseand re-write the ROundware code as appropriate to achieve the above goals in collaboration with the Roundare dev team.
Indoor localisation for the Roundware app: Roundare is a contributory augmented reality system that has been used as the technical foundation for a variety of art installations. The objective of this project is to modernise and augment the Androi to incorporate geomagentic indoor location sensing functionality using the IndoorAtlas system, in collaboration with the Roundare dev team.
IoT system for Coastal Monitoring: The Coastal Sensing project aims to develop low power wireless environmental sensors using stte-of-the-art IoT technologies to assist process understanding and inform future coastal protection schemes. Theere are three different projects that are offered within this work, namely: (a) comparative investigation of through-solids low power wireless protocols such as LoRa and M-Bus in the coastal setting (wet sand), (b) advanced sensing technniques such as Accoustic Emissions to monitor sand movement, and (c) sensor fusion for in-solids localisation.
IoT platfrom for RF energy harvesting at 2.4GHz: An ARM-based platform is developed at the department as part of a feasibility study on IoT devices powered solely from energy harvested from ambient Wi-Fi and BLE emissions. The aim of the project is to develop adaptive software techniques for maintaining robust system operation under such intermitent energy budgets.
Novel digital biomarkers for Parkinson's: The aim of the project is to contribute addition data analysis tools to the open source PDkit python-based toolkit developed at the department for the processing of sensor data captured from smartphones and wearables. There are several areas that require further development currently including additional feature extraction for all processors, advanced cross-validation and longtitutinal and multi-feature biomarker implementation.
Contact George Roussos to discuss the suitability of the above areas for your project.