Last night I stumbled upon . I decided to sign up and upload one of my early datasets. This dataset 2010 ZigBee Sensor Data Collected From a House (in Vancouver, Canada) Dataset contains power meter, ambient light, and ambient temperature sensors readings; including weather and daylight data. Sensor readings are at 15 minute intervals for about 8 months.
This dataset was originally used in the my conference publication An intelligent agent for determining home occupancy using power monitors and light sensors (2011) and the later expanded journal paper Home Occupancy Agent: Occupancy and Sleep Detection (2012).
This dataset monitors the same house that AMPds and should have not limited use for testing very low-frequency load disaggregation (nonintrusive load monitoring or NILM) algorithms and activity inference algorithms.
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Published by Stephen Makonin
Dr. Stephen Makonin is an Adjunct Professor in Engineering Science and the Principal Investigator of the Computational Sustainability Lab at Simon Fraser University (SFU). He received his PhD in Computing Science at Simon Fraser University in 2014 in the area of computational sustainability. He has been a software engineer for over 24 years working for various local/international industry clients. Stephen is a registered Professional Engineering (PEng) with Engineers and Geoscientists BC and a Senior Member of the IEEE. His research interests include computational sustainability and the understanding of socioeconomic issues that pertain to technological advancement. Stephen is an expert in data engineering, software engineering, and a world-renowned researcher in non-intrusive load monitoring (NILM) and disaggregation. Stephen is currently the Vice-Chair of the IEEE Signal Processing Society Vancouver Chapter and sits on the IEEE DataPort Advisory Committee. He currently serves as the Editor in Chief of the IEEE DataPort Metadata Review Board, and as an Editorial Board Member of Nature's Scientific Data journal.
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Non-Intrusive Load Monitoring (NILM) 