“Measuring People-Flow Through Doorways using Easy-to-Install IR Array Sensors” by Hessam Mohammadmoradi, Sirajum Munir, Omprakash Gnawali, and Charles Shelton. In Proceedings of the Thirteenth IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS 2017), June 2017.
People counting has many applications in smart buildings. For example, adjusting HVAC systems based on the number of occupants in each room can save a significant amount of energy. In addition, security and safety of the building can be managed by determining the number and location of occupants. Different technologies and sensing platforms have been proposed for accurate and efficient people counting. However, these solutions are expensive, hard to deploy, or privacy invasive. We investigate the possibility of placing an 8x8 IR array sensor at the doorways and counting the number of people inside rooms. Our solution is real-time, inexpensive, privacy preserving with much less deployment constraints compared to its competitors. The proposed solution deals with realistic and dynamic changes in the sensing environment by leveraging a combination of Otsu'ss thresholding and modeling thermal noise distribution. We evaluated our solution via several controlled and uncontrolled real-world environments. The results show an average of 93% accuracy in estimating the number of occupants in rooms.
BibTeX entry:
@inproceedings{peoplecounting-dcoss2017,
author = {Hessam Mohammadmoradi and Sirajum Munir and Omprakash Gnawali
and Charles Shelton},
title = {{Measuring People-Flow Through Doorways using Easy-to-Install
IR Array Sensors}},
booktitle = {Proceedings of the Thirteenth IEEE International
Conference on Distributed Computing in Sensor Systems (DCOSS
2017)},
month = jun,
year = {2017}
}