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Analyzing the flow of crowd counting can be used for public policy, corporate strategy, and commercial district analysis. Existing devices are installed on poles, buildings, etc. to detect WiFi signals from personal devices. However, these devices are often not located adjacent to actual sidewalks, do not provide power at all times, or have limitations in collecting personal terminal identification information, especially due to restrictions under the strengthened Personal Information Protection Act. This paper designs a WiFi scanner to accurately collect WiFi. We also conduct research on a repeater that transmits smartphone MAC information to a cloud server that does not violate the Personal Information Protection Act. In addition, it solves the power problem of existing communication transmitters with a self-generating system using solar power and piezoelectric power generation. The results of this paper will be used in commercial analysis, corporate strategy, and public policy, and will contribute to the development of wireless communication and artificial intelligence technology. [ABSTRACT FROM AUTHOR]

Estimation of the presence of people in real time is extremely useful for businesses in providing better services. Many companies and researchers have attempted various researches in order to count the number of floating population in a specific space. Recently, as part of smart cities and digital twins, commercialization of measuring floating populations using Wi-Fi signals has become active in the public and private sectors. In this paper we present a method of estimating the floating population based on MAC-address values collected from smartphones. By distinguishing Real MAC-address and Random MAC-address values, we compare the estimated number of smartphone devices and the actual number of people caught on CCTV screens to evaluate the accuracy of the proposed method. And it appeared to have a similar correlation between the two datas. As a result, we present a method of estimating the floating population based on analyzing Wi-Fi Probe Requests. [ABSTRACT FROM AUTHOR]