Low-Cost Conservation Technology

Lead Research Organisation: University of Oxford
Department Name: Autonom Intelligent Machines & Syst CDT


Brief description of the context of the research including potential impact We are currently witnessing an ongoing mass extinction. This Anthropocene extinction is mainly caused by human activities that either directly decimate populations (e.g.over fishing and over hunting) or destroy their habitats(e.g.deforestation and pollution). Recently, human-induced climate change has additionally sped up habitat destruction, which is leading to an even greater loss of biodiversity. We hope to address this problem by providing better technology to conservation biologists. This should speed up and improve their investigations which will allow for more effective policy decisions.
Aims and Objectives Our goal is to foster open development of conservation technology. We expect that this will lead to faster progress and lower end-product costs. To do so, we will be making use of low-volume manufacturing, low-power microcontrollers and cloud processing. As a first step, we want to apply these ideas to the development of a GPS receiver for wildlife tracking. Novelty of the research methodology This GPS receiver will use a snapshot method, which means that it only records milliseconds of data at regular intervals. This leads to very low power consumption, which allows for smaller batteries, which in turn means less obtrusive tracking devices. Apart from the technical challenge of building the software and hardware, there is also the problem of making the solution scalable so that it can be accessible to researchers around the world. Some work has already been done on both the algorithms and the electronics for this approach. However, there currently exists no complete open-source solution stack and, more importantly, no affordable end-product. This is what conservation biologists will need to do large-scale GPS tracking.
Alignment to EPSRC's strategies and research areas This project relates to the EPSRC's research areas: sensors and instrumentation and digital signal processing.


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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/S024050/1 01/10/2019 31/03/2028
2243851 Studentship EP/S024050/1 01/10/2019 30/09/2023 Amanda Matthes