Part III & MPhil Project Suggestions

These are some suggestions for Part III and MPhil projects within the Digital Technology Group. If you have an idea related to our group's research interests that isn't mentioned here, get in touch.



Many-Robot Systems

New Projects

Suggestions by Dr Amanda Prorok

Systems projects

New Projects

The list of new Part III and MPhil projects are available here.

Projects from previous years

The list of Part III and MPhil projects from previous years are available here.

Indoor Smartphone and Person Tracking

  1. Bluetooth Low Energy Phone Tracking

    This project will look at positioning mobile phones using BLE beacons distributed around the environment. This is a topic in industry at the moment but the beacons are expensive and the phone platforms have only just begun to support BLE properly. We will create beacons using raspberry pis and cheap bluetooth dangles. Unknowns include what power to beacon at, what update rate can be expected, what the continuous scan costs on the phone, whether we can infer good distance estimates and how easy it will be to spoof beacons and thereby cause havoc! The project has a high chance of international publication and further PhD work. Programming for android and/or iOS needed, along with good Linux skills. Previous knowledge of Bluetooth (in any form) is valuable but not essential.

    Contact: R. Harle

  2. Bluetooth Low Energy Sensor Network

    This project will invert the typical Bluetooth tracking scenario by using BLE beacons on the person rather than in the environment building a sensor network of Raspberry Pi BLE sensors. Beacons are small and last years so each person could conceivably carry multiple to aid positioning and to minimise body attenuation. The research aim will be to establish the capabilities of such a system in terms of range, accuracy, power consumption, update rate and maximum beacon numbers. The project has a high chance of international publication and further PhD work. Experience working with Raspberry Pis or Linux environments essential. Previous knowledge of Bluetooth (in any form) is valuable but not essential.

    Contact: R. Harle

  3. Smartphone Camera-based Movement Classification

    A key problem in Pedestrian Dead Reckoning is determining the direction of motion. It is hard to distincuish between back steps, side steps and forward steps. This project will look at repurposing smartphone cameras to estimate relative movement direction based on feature tracking applied to the ceiling or floor. Many optical flow-like algorithms exist that can be trialled. The important result is not just that the direction is correct, but also that the drain on the smartphone battery is minimised. This project will be carried out using the Android platform: some experience of programming for it will be necessary. The optical algorithms may be imported from e.g. openCV (which has an Android port), or written from scratch if preferable.

    Contact: R. Harle

  4. WiFi-IR Positioning

    The dominant indoor positioning approach is the use of WiFi fingerprints. However, these are typically unable to unambiguously locate to a room since WiFi penetrates walls. We have in the past developed an InfraRed based location system (the Active Badge) that had people wear IR emitters and used IR receivers in each room. IR was very good at room localisation (IR does not penetrate walls) but we could not realistically install receivers everywhere. This project will look at exploiting the rising number of IR transmitters on recent smartphones (e.g. Galaxy S4) and simple networked IR receivers (built from e.g. Raspberry Pis or similar) to create a modern-day Active Badge that is fused with WiFi positioning data to create a more robust and ubiquitous tracking system. Experience of Android programming essential.

    Contact: R. Harle

Other suggestions by individual group members

  1. Suggestions by Dr Andrew Rice