Measuring Digital Exclusion

Single chair in an empty room

We assume that technologies will improve our lives, work and quality of life. For many people such benefits are undoubtedly true. However, does this apply to everyone? A House of Lords report in 2023 proposed that the "digital divide is undermining efforts to improve UK productivity, economic growth and socio-economic inclusion" and that groups likely to be most effected included the elderly, with 31 per cent of people aged over 65 not using the internet at home, compared with only 4 per cent of those aged 35-44 (https://publications.parliament.uk/pa/ld5803/ldselect/ldcomm/219/21902.htm ).  

A useful project would be to explore options for research in this area. Perhaps formulate a survey strategy, questionnaire, workshop, or proposed data sources that might be used for subsequent exploration. Proposals would need to be informed by background research and considerate of research rigour and ethics. 

Internet of Things / Digital Twins

Agricultural scene - field with combine harvesters

The Internet of Things and Digital Twins are becoming hot industry topics. It would be great for us to build our capabilities in these fields, with a view to expanding our teaching and research options. A useful project would be to explore low cost (even free!) options to that would enable academic researchers and students to explore topics such as medium/long range wireless networks (such as LoRa), IoT system simulation, or Digital Twin development. 

Data Science: Using Open Data Sets for Research and Strategic Planning

Hospital worker in blue scrubs stood next to elderly man in wheelchair

Government agencies are increasingly making data available to the public and researchers. Examples include higher education data published by HESA, socio-economic data published by ONS, and health data published by NHS. Such data might provide a useful source for analysis, research and planning. A project could investigate what data is available in a certain field, and then explore how it might be used, for example by being prepared and interrogated using Python or R. Alternatively, a potential use could be decided, such as predicting the number of total hip and knee replacement operations needed in the next ten years, and then looking at how this might be predicted and what existing data might be used.

Automotive Cyber Security

Car dashboard and steering wheel with a laptop next to them displaying data captured from the car.

The rise in connected autonomous vehicles presents challenges such as software reliability, operational trust and determination of accountability. A major concern is cyber security. Vehicle-attack opportunities are still emerging and not yet fully understood.

 

1) Assessing the threat and perceptions of automotive cyber risk. Vehicles will increasingly need to communicate with one another and to cloud systems. With the rise in connectivity, come the increasing risk of cyber breaches. Attacks could potentially affect data privacy, vehicle security or even vehicle safety. But how great is the danger? What are the perceptions of the car users? And how should we measure these? These are questions that automotive manufactures will need to increasingly ask in the next few years. 

 

2) Devising and testing automotive cyber attack scenarios. The Controller Area Network (CAN) is a crucial in-vehicle network used by safety crucial components, such as transmission, engine performance and braking. It is possible to read packets from the car’s CAN (as well as inject malicious packets), though the car manufacturers keep the meaning of the data secret.

Projects could investigate what CAN data sets might be available for testing attack detection, or investigate how attacks might be simulated, or devise algorithms to detect suspicious anomalies in data which might indicate an attack. One option would be to use a laptop based based CAN simulator (such as the free Kvaser CAN King) and CAN Python libraries with pre-gathered CAN logs (which we already collected).