Passive IR (PIR) sensors are excellent devices for wireless sensor networks (WSN), being low-cost, low-power, and presenting a small form factor. PIR sensors are widely used as a simple, but reliable, presence trigger for alarms, and automatic lighting systems. However, the output of a PIR sensor depends on several aspects beyond simple people presence, as, e.g., distance of the body from the sensor, direction of movement, and presence of multiple people. In this paper, we present a feature extraction and sensor fusion technique that exploits a set of wireless nodes equipped with PIR sensors to track people moving in a hallway. Our approach has reduced computational and memory requirements, thus it is well suited for digital systems with limited resources, such as those available in sensor nodes. Using the proposed techniques, we were able to achieve 100% correct detection of direction of movement and 83.49%–95.35% correct detection of distance intervals.

Tracking Motion Direction and Distance With Pyroelectric IR Sensors

ZAPPI, PIERO;FARELLA, ELISABETTA;BENINI, LUCA
2010

Abstract

Passive IR (PIR) sensors are excellent devices for wireless sensor networks (WSN), being low-cost, low-power, and presenting a small form factor. PIR sensors are widely used as a simple, but reliable, presence trigger for alarms, and automatic lighting systems. However, the output of a PIR sensor depends on several aspects beyond simple people presence, as, e.g., distance of the body from the sensor, direction of movement, and presence of multiple people. In this paper, we present a feature extraction and sensor fusion technique that exploits a set of wireless nodes equipped with PIR sensors to track people moving in a hallway. Our approach has reduced computational and memory requirements, thus it is well suited for digital systems with limited resources, such as those available in sensor nodes. Using the proposed techniques, we were able to achieve 100% correct detection of direction of movement and 83.49%–95.35% correct detection of distance intervals.
Zappi P.; Farella E.; Benini L.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/94517
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