Room Occupancy Estimation Through WiFi, UWB, and Light Sensors Mounted on Doorways

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“ Room occupancy estimation through wifi, UWB, and light sensors mounted on doorways” by Hessam Mohammadmoradi, Shengrong Yin, Omprakash Gnawali. In In Proceedings of the 2017 International Conference on Smart Digital Environment(ICSDE'17)., July 2017.

Abstract

Recent studies have shown that adjusting HVAC systems based on the number of people inside the room can save at least 38% of energy consumed for reheating. Besides, accurate estimate of room’s occupants is useful in improving the safety and security of the buildings. There are many research proposals and commercial products for reliable and efficient people counting, however, these solutions are expensive, hard to deploy, or obstructive to people flow. We investigate the possibility of utilizing wireless and light sensing technologies in the doorways to track the entrances/exits to/from the room. Our solution is inexpensive, unobtrusive with much fewer deployment constraints compared to existing people counting solutions. For RF based sensing, we use ultra-wideband signals at center frequency of 4 GHz with 500 MHz bandwidth and narrowband wireless signals (WiFi) at the center frequency of 2.4 GHz with the bandwidth of 20 MHz. We also evaluate the possibility of using existing WiFi infrastructure to count people. Ambient light is second physical phenomenon which we utilize for accurately counting number of people walk through the doors. We place low cost photodiode on door frames to detect changes in light illuminance level when there are people walking through the door. Light based people counting requires an installation of just one inexpensive photodiode at the doorway which makes our solution highly applicable for large scale deployments. We evaluated our solution via several controlled and uncontrolled real-world environments. The results show an average of 96% accuracy in estimating the number of occupants in rooms.

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BibTeX entry:

@inproceedings{peoplecounting-iscde17,
   author = {Hessam Mohammadmoradi, Shengrong Yin, Omprakash Gnawal.}
   title = {Room Occupancy Estimation Through WiFi, UWB, and Light Sensors Mounted on Doorways},
   booktitle = { In Proceedings of the 2017 International Conference on Smart Digital Environment(ICSDE'17)},
   month = {July},
   year = {2017}
}