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DTSTART:20250101T000000
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DTSTART;TZID=Asia/Hong_Kong:20260617T110000
DTEND;TZID=Asia/Hong_Kong:20260617T120000
DTSTAMP:20260612T014214
CREATED:20260609T085437Z
LAST-MODIFIED:20260609T085437Z
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SUMMARY:RPG Seminar – Adaptive Lightweight Learning for Edge Non-Intrusive Load Monitoring
DESCRIPTION:Zoom Link \nhttps://us05web.zoom.us/j/88334748156?pwd=YXWVQUg4FEHYb9nucvsm78fqasXabh.1 \nAbstract\nNon-intrusive load monitoring provides appliance-level electricity consumption information from aggregate household measurements\, supporting residential energy management without installing sensors on individual appliances. Processing these measurements on local edge devices can provide timely feedback while preserving user privacy. However\, practical deployment remains difficult because edge devices have limited computing and memory resources\, and differences among households can reduce the accuracy of models trained elsewhere. This seminar presents a lightweight learning framework that enables non-intrusive load monitoring models to operate on resource-constrained devices and adapt to previously unseen households without requiring appliance-level labels from local users. The study examines the full process from preparing a model for edge deployment to improving its performance after deployment. Ultimately\, the framework enables accurate\, low-cost\, and privacy-preserving household energy monitoring across diverse edge devices and residential environments. \nSpeaker\nMr Taoyu LU \nDepartment of Electrical and Computer Engineering \nThe University of Hong Kong \nBiography of the Speaker\nTaoyu LU received the B.Eng. degree in electrical engineering and automation from Huazhong University of Science and Technology in 2024. He is currently pursuing the M.Phil. degree in electrical and electronic engineering at the University of Hong Kong. His current research interests include low-carbon energy systems and edge intelligence in smart grids. \nOrganiser\nProf. Yi WANG \nDepartment of Electrical and Computer Engineering\, The University of Hong Kong \nAll are welcome.
URL:https://ece.hku.hk/events/20260617-1/
CATEGORIES:Seminar
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