Part II/ACS projects

  • Federated blockchain: The goal of this project is to design and implement a federated blockchain, where gateways are used to exchange data between blockchains to overcome differences in jurisdictional requirements. Specifically, each jurisdiction (country or a region of a country) has its own requirements for disclosure of project details for carbon credits. This makes it difficult to define a single blockchain transaction type that can be used globally. With this approach, a chain can store sector- and location-specific details of carbon sequestration from nature-based solutions. The gateways would provide translation of attributes between chains. The solution should be general, scaleable to global scale, and deployable using current mainnets such as for Tezos and Algorand.
  • Trusted image capture: The goal of this project is to link image capture from trusted hardware devices, such as Azure Sphere, to a global file store, such as IPFS, with summaries posted to a blockchain. This would allow us to trace an image to its creator with an unbroken chain of trust. Students who have some background working with microcontroller-based single-board devices, such as a Raspberry Pi, would be preferred. An alternative would be to develop the solution using an integrated hardware/software platform, such as iOS, and use iOS APIs to prove that the captured image, its time stamp, and device orientation had not been tampered with.
  • Speeding up forest simulation: The state of the art in forest simulation is an agent-based model, such as TROLL. Here, a software agent simulates each tree in a forest. This process is highly parallelisable, and the goal of this project is to exploit the inherent parallelism to greatly speed up agent-based simulations. (This project is now taken)
  • Durable storage of primary observational data: Observational data from trusted sources, such as satellites and trusted cameras (see above) are voluminous (terabytes to petabytes) but need to be stored for decades. This project explores storage and indexing of such data. Ensuring immutability of the data through a blockchain link would also be desirable. (This project is now taken)
  • Sensor design: Many sensors in use today, especially in agricultural contexts, are not suitable for long-term mass-scale forest deployment. Forest environments are less controlled and consistent than agricultural ones, and access to deployed sensors is comparatively limited. Thus, the sensors need to be self-managing, robust and long lived. Sensors may make different trade-offs between energy usage and lifespan. For example, active medium-lifespan sensors (e.g. spectroscopy for measuring soil quality) used during sapling establishment could be deployed alongside passive long-lived sensors designed to last for the expected lifetime of the trees (e.g. temperature and humidity via chipless RFID).Additional sensors may also be considered outside of those normally associated with agriculture, for example to account for dead organic matter, estimate carbon content of soil and litter, and to monitor for poaching, theft, vandalism and possible fraud. Thus, there is ample scope for research into appropriate sensor system design.
  • Geolocation in a rainforest: The goal here is to design a geolocation service in a rainforest, where GPS may be either unavailable or imprecise and the environmental conditions are harsh. Under such circumstance, the typical 10-30m accuracy achieved in the field would not be sufficient for fieldwork. The goal here would be to implement one of the many systems described for indoor wayfinding, such as using BLE and RSSI, e.g. , in an outdoor context. (This project is now taken)
  • Drone-based forest biomass and soil analysis: The goal of this project is to use drone along with a camera and a hyperspectral sensor to create pointclouds of the forest, and to run PLSR or RandomForest to work out which particular wavebands have reflectances that predict soils properties well.
  • Linking field data and remote sensing: How can we integrate diverse spatial and temporal field/point measurements of biodiversity and ecosystem functioning using remote sensing data? The idea is to use ground based sensors to establish ground truth for remote sensing imagery and remote sensing to tie together ground based sensors.