The University of Lancaster and Howz have collaborated to develop innovative change detection methodologies that enhance health and social care monitoring. By leveraging IoT sensors, their approach analyzes daily routines and sleep patterns to detect anomalies in residents' behavior—critical for identifying potential health issues. Their latest methodologies utilize inhomogeneous Poisson processes to differentiate natural daily variations from significant changes across days, offering valuable insights into health trends and early indicators of decline. This groundbreaking research is revolutionizing disease prevention and in-home health improvement.

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