They
extract passage duration and output amplitude from PIR output
signals, and perform classification analysis using support
vector machine and k-nearest neighbor algorithms. The experimental
results show 100% correct detection of direction of
movement and 83.49%–95.35% correct detection of distance
intervals. They also demonstrated their feature extraction and
sensor fusion technique could be exploited in low-cost, lowpower
sensor node system with limited computational and
memory resources. Although this research only considered a
2-way, back-and-forth movement as in previous research, this
style of motion direction detecting method based on feature
extraction from analog PIR sensor signal and machine learning
technologies echoes our motivation in this paper.
More recently, PIR sensors are commonly used with a
variety of sensors in diverse applications for building smart
environments such as healthcare, smart energy system, and
security. Tsai et al. illustrated a way of reducing the standby
power consumption of lighting devices based on PIR sensor,
ambient light sensor, and lighting duration modules