A device-free human detection system based on a received signal strength indicator (RSSI) monitors and analyzes the change of RSSI signals to detect human movements in a wireless network. This study proposes and implements a real-time, device-free human detection system based on an RSSI distribution-based detection method with an autonomous threshold. The novelty and contribution of our solution is that the RSSI distribution concept is considered and used to calculate the optimal threshold setting for human detection, while thresholds can be automatically determined from RSSI data streams gathered from test environments. The proposed system can efficiently work without requiring an offline phase, as introduced in many existing works in the research literature. Experiments using 2.4 GHz IEEE 802.15.4 technology have been carried out in indoor environments in two laboratory rooms with different numbers of wireless links, human movement patterns, and movement speeds. Experimental results show that, in all test scenarios, the proposed method can monitor and detect human movement in a wireless network in real time. It outperforms a comparative method and achieves high accuracy (i.e., 100% detection accuracy) with a low computational complexity requirement.
Pochaiya et al. (Thu,) studied this question.