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There is growing UK and international interest in networked sensing and autonomous collaborative platforms, where multiple airborne sensors co-operate to collect and exploit data. In contrast
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role involves designing and integrating real-time software algorithms with robotic hardware, including perception, control, communication, and safety modules to enable safe, precise, and reliable remote
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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drone detection and localisation performance using radar systems. This can be achieved by improving the detection performance of individual sensors and by employing a cooperative network of sensors which
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sustainability. The research will delve into power-aware computing strategies, thermal management, and the development of algorithms that balance performance with energy consumption. Students will aim to create
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, thermal, electromagnetic or kinetic), are critical for the sustainable operation of wireless IoT devices and remote sensors. The world can reduce reliance on batteries and fossil-fuel-derived power if more
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twins, enabling real-time stress-testing under simulated edge cases like cyber-physical attacks and sensor failures. The Research Challenges There exists a complex interplay of factors that present
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the number of sensors required and the maintenance of the data acquisition system. Hence, the alternative of direct instrumentation of the structure, whilst effective, can be logistically expensive