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Field
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impacts and suboptimal decision-making. Examples include crowd management and large-scale communication networks based on cellular or wireless sensors. For instance, during mass gatherings such as the sport
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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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are categorised as non-destructive testing techniques, but they can be costly considering the number of sensors required and the maintenance of the data acquisition system. Hence, the alternative of direct
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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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data are needed to enhance our understanding of sources, pathways and impact of litter. Cefas is developing a visible light (VL) deep learning (DL) algorithm and collected a large 89 litter category
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, despite its widespread application, polygraph data capture and analysis has received limited systematic research and does not yet incorporate modern sensors, computing and analytical techniques. Project
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across Scotland’s west coast. It will evaluate the practicality of different image capture techniques and the potential of different sensor types (e.g., RGB, multispectral) to generate beach litter images
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capable of leveraging signals from terrestrial base stations, non-terrestrial networks such as LEO satellite, and complementary on-board sensors. Specifically, it will: To design reconfigurable airborne
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materials and innovative sensor architectures that maintain stable performance under bending, moisture exposure, and mechanical loading. The envisioned platform will contribute to future responsive biomedical
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velocity continuity or GNSS-derived velocity estimates. Sensor fusion consistency: aligning pseudorange corrections with complementary sensors, such as inertial navigation systems. Map-based constraints