tinyML Talks on April 30, 2024 “MicroCam: A Low-Power and Privacy Preserving Multi-modal Sensor Platform for Occupancy Detection” by Senem Velipasalar

We held our next tinyML Talks webcast. Senem Velipasalar from Syracuse University presented MicroCam: A Low-Power and Privacy Preserving Multi-modal Sensor Platform for Occupancy Detection on April 30, 2024.

Heating, ventilation, and air conditioning (HVAC) consumes a significant portion of the energy used in buildings. Much of this is wasted energy, used when buildings are either not occupied at all, or occupied well under their maximum design conditions. In this talk, we will focus on residential occupancy detection to autonomously control HVAC systems and save energy. After discussing the limitations of existing solutions, MicroCam will be introduced. MicroCam is a low-cost, high accuracy, standalone residential occupancy sensing platform, which can operate on typical alkaline batteries without relying on the cloud or external computing resources, and consists of low-power, Artificial Intelligence (AI)-based, IoT platforms. Each platform has multi-modal sensors and can process motion, audio and video data. All sensor data is processed locally on platforms, and the only transmitted data is the binary occupancy state. MicroCam has been evaluated extensively, and the lessons learned will be presented.

Dr. Senem Velipasalar is a Professor in the Department of Electrical Engineering and Computer Science at Syracuse University. She received the Ph.D. and M.A degrees in electrical engineering from Princeton University, and the M.S. degree in electrical sciences and computer engineering from Brown University. The focus of her research has been on machine learning, computer vision, mobile camera applications, wireless embedded smart cameras, multi-camera tracking and surveillance systems. She received a Faculty Early Career Development Award (CAREER) from the National Science Foundation (NSF) in 2011, IEEE Region 1 Technological Innovation (Academic) Award in 2021 and Excellence in Graduate Education Faculty Recognition Award in 2014.

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Senem Velipasalar

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