An Automatic People Counter in Stores Using a Low-Cost IoT Sensing Platform
In this paper, we propose an automatic people counting system by using our low-cost Internet-of-Things (IoT) platform consisting of a single camera and Raspberry Pi. In this system, we count the number of moving people in bidirection by observing from a side view. Because the system can determine the height of the people, our system can be used to classify them into adults or children. This system is applied for no people overlapping problem in indoor environment only. The background subtraction and morphological operations are used to extract foreground objects from background images. The experimental results show proposed method can achieve 98% of people counting accuracy. It can also achieve 91% accuracy in adult/child classification. Although the algorithms for the people counting and classification are not novel, our technical contribution is that we have implemented them onto our IoT platform, whose cost is less than 100 US dollars. In addition, the images do not need be sent to the server, but all the image processing is done inside the device and only the results are uploaded to the server. This system can be applied to for customer behavior analysis or security.
KeywordsPeople counting IoT sensing Raspberry Pi
This is a collaboration project for joint internship program among Panyapiwat Institute of Management, Thailand, Future Standard Company and Yamasaki Lab of The University of Tokyo, Japan.
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