The idea is to develop a new sensor, ‘iSense’ that has the capabilities to detect occupancy status, occupant count, comfort status as well as human-building system interactions (i.e. interactions with windows, shades, lighting and the thermostat). Based on real-time data collected from the ‘iSense,’ an analytics and modeling package will provide diagnostic information on comfort issues, building operation, and worker productivity. The underlying research elements include the development of the multi-functional sensor and the development of the analytics and modeling package to enable self-learning capabilities. Focus will be placed on the integration with BAS/EMCS, interoperability with data, and metrics to quantify the energy use and comfort level. The ‘iSense’ will bring the realm of personal devices and analytics into a new domain that can address individual comfort preferences and building energy consumption mitigation strategies, simultaneously.
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