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Demo: FORK: Fine grained Occupancy estimatoR using Kinect on ARM Embedded Platforms

Abstract

Occupancy estimation is very useful for a wide range of smart building applications including energy efficiency, safety, and security. In this demonstration, we present a novel solution called FORK, which uses a Kinect depth sensor for estimating occupancy in real-time. Unlike other camera-based solutions, FORK is much less privacy invasive (even if the sensor is compromised) and it does not require a powerful machine like a Microsoft XBOX or an Intel® CoreTM i7 processor to process the depth data. Our system performs the entire depth data processing on a cheaper and lower-power ARM processor, in real-time. In order to do that, FORK uses a novel lightweight human model by leveraging anthropometric properties of human bodies for detecting individuals. We will show how FORK detects, tracks, and counts occupants accurately in real-time.

Publication
In proc. of the 4th ACM International Conference on Systems for Energy-Efficient Built Environments
Date
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