Abstract

This paper presents an analysis of the received signal strength indicator (RSSI) from the radio frequency signals for human identification in an indoor wireless sensor network (WSN). Instead of using closed-circuit television as the existing security platform, this indoor safety system was improved with a convenient, cheap, and low-power solution. The system was developed using 20 of ESP8266-12F Wi-Fi modules transmitters and another 2 of ESP8266-12F as the access points located in 3 m × 3 m area of interest. With a suitable coordinate of sensor nodes, a WSN telemetry could be established to minimize the blind spot area and limit the movement of the intruder with a minimum area of 0.2 m2. The RSSI measurement was repeatedly conducted for three different conditions, in an empty room, with the presence of a single intruder and the presence of multiple intruders. Based on the RSSI values, we found that there are distinctive features of data that can be utilized as flags for classifying the three above conditions. Besides that, to justify the efficiency of system performance, we also examined the sensitivity of RSSI values towards the variation of temperature. Our results show that the RSSI average values for both morning and night were practically the same. However, during the afternoon, the RSSI signal strength fluctuated by − 1.0 dBm. These results motivate the development of an alarm system that only uses the RSSI statistics to detect human presence.

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