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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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the question ‘how close to failure is the asset?’. By integrating a suite of state-of-the-art sensors and monitoring technologies with data fusion and AI analytics, this research will enable timely
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creating robust, low cost, and real-time edge-AI algorithms capable of accurately classifying diverse marine species and debris under complex and dynamic underwater conditions. The demand for such a low-cost
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language model (LLM) technologies to create advanced, multimodal predictive tools for plant health monitoring. Using imagery from RGB cameras, drones, satellites, and multispectral and hyperspectral sensors