System Design for Passive Human Detection Using Principal Components of the Signal Strength Space

Abstract

In this article, device-free human presence detection method based on principal components analysis of the radio signal strength variations is proposed. The method increases user awareness for automated power management interaction in residential power saving systems. Motivation comes from a need for decreasing the installation complexity and development costs induced by the integration of specific human presence detection sensors. The method exploits the fact that a human body interferes with radio signals by introducing irregularities in the radio signature which indicate possible human presence. By analyzing radio signals between radio transceivers embedded in 2.4 GHz wireless power outlets, the original environment is not visually modified and a certain level of sensorial intelligence is introduced without additional sensors. The analysis of the signal strength variations in principal components space enhances the detection accuracy level of human presence detection method, retaining low installation costs and improving overall energy conservation.

Measurement of long-distance Wi-Fi connections: An empirical study

“…Mrazovac et al [15,16] investigated variations in the Received Signal Strength Indicator (RSSI) values due to human mobility in an indoor environment; then, based on their model, they designed a passive approach to detect such mobility. Ohshima et al [19] conducted a three-month field experiment and posited that the relative humidity is the most important factor that affects the network performance of Wi-Fi links; Nadeem et al [17] evaluated the effects of rain on wireless RF links; while Kaur and Singh [12] assessed the effects of fog and snow on RF links.…”

“…Finally, the technology uses the 2.4GHz ISM (Industrial, Scientific and Medical) band, which is crowded by many other radio sources/technologies (e.g., Bluetooth, ZigBee, microwave ovens, and cordless phones). Several studies have investigated the network performance of Wi-Fi links under different environmental factors, such as human activities [15,16], weather conditions [12,17,19], and path properties [5,6,8,9,22,23,25]. Even so, there is a dearth of systematic, continuous, and long-term studies of practical long-distance Wi-Fi connections in real-world settings.…”

Li-Tect: 3-D Monitoring and Shape Detection Using Visible Light Sensors

“…Note that, in these schemes the phases of WiFi signals are particularly sensitive to slow human motion. In [23] processing of changes in the received signal strength indicator (RSSI) for 2.4-GHz wireless power outlets were used for sensor-less detection of human presence. Li-Tect offers an improved shape and posture detection method where there is no requirement for precise shadow estimation, thereby avoiding complexity due to shadow overlapping and blurry shadow edges.…”

RSSI-based Human Presence Detection System for Energy Saving Automation

“…Researches done on the available solutions and method to human presence detection system and the applications of it are focused and discussed. A novel method to detect the presence of human in a residential network that has a radio frequency energy is presented in [4]. The researcher's method of detecting human presence is by utilizing radio irregularity phenomenon.…”

“…To improve presence detection in a larger rooms, additional smart outlets are needed to ensure its propagation path's signal can be intersected by a human body. However, testing in another buildings made of different materials is yet to be done, since such testing would help to find patterns that can enable filter function defining which will result in the ability of distinguishing an occupied or unoccupied room especially when correlation occurs between the signal variations [4].…”