Passive infrared (PIR) sensors are the most popular deployed sensors in buildings for individual presence detection. However, PIR sensors are motion detectors in nature, responding only to incident radiation variation, which leads to false negative detections, inaccurate occupancy estimation, and uncomfortable lighting swings and waste of energy. To address this issue, an optical shutter driven by a Lavet motor PIR (LAMPIR) sensor is developed for true presence detection. In comparison with our previously developed chopped PIR (C-PIR) and rotationally-chopped PIR (Ro-PIR) sensors, a low-power single-phase electro-mechanical driving approach, is introduced for LAMPIR, to replace traditional servo and stepper motors, and thus significantly reduce the power consumption by up to 89%, size by up to 60%, weight by up to 75%, cost by up to 31%, and acoustic noise by 12 dBA. More specifically, driven by pulsed signal from a microcontroller unit (MCU), the electro-mechanical vibrator drives a semi-transparent long-wave infrared (LWIR) optical shutter to chop the field of view (FOV) of a PIR sensor periodically. By monitoring and analyzing the voltage outputs generated by the LAMPIR senor, high-accuracy presence detection can be achieved, by optimizing the shutter width and shuttering period through parametric studies. Experimental results show that a classification accuracy of 100% can be reached for detecting stationary occupants up to 4.5 m and moving occupants up to 10 m, suggesting a detection range improvement from both the C-PIR and the Ro-PIR sensors (4.0 m for stationary and 8.0 m for moving occupancy detection for both sensors). Additionally, the LAMPIR sensor has a FOV of 90° in horizontal and 100° in vertical, which is sufficient for most applications. For a 31-hour-long presence detection test, an accuracy of 97% is achieved when classifying unoccupied and occupied scenarios, while an accuracy of 93% when classifying unoccupied, stationary and moving occupant scenarios.

Passive infrared (PIR) sensors are the current choice for individual presence detection in buildings. A major problem is that PIR sensors only detect moving individuals, which often provides false negative detections, resulting in uncomfortable lighting/temperature swings, short lifetime of the equipment, and waste of energy. In this letter, a rotating shutter is introduced to the rotationally-shuttered PIR (Ro-PIR) sensor to explore its functionalities beyond motion sensing, including stationary individual localization, tracking, and facing direction detection. More specifically, by monitoring and analyzing polarity-phase of the nonlinear infrared energy flow induced by the rotating shutter, Ro-PIR is capable of zone-level localization for stationary individuals. By further analyzing the duty cycle of the output, occupancy facing direction can be predicted. Two theoretical models are created to identify facing directions (front/back or side) by analyzing three infrared radiation covering configurations, shaped by shutter movement. Combining sequence of covering configurations represents the induced polarity-phase output voltage, illustrating the occupancy localization information during one segmented scanning period. Parametric analysis, and empirical studies are performed to obtain the optimal setting of the shutter in terms of its width and shuttering period. Experimental results reveal 100% presence accuracy for stationary detection for up to 3.0 m, and moving detection for up to 8.0 m. Zone-level localization can reach 98% accuracy by applying machine learning classifier using two features extracted from polarity-phase signals. Experimental results also show less than 0.44 m root mean square error (RSME) for tracking, and over 83% in detecting front/back or side facing direction.

This article presents the modeling and experimental validation of a piezoelectric stack energy harvester with a flexure-free convex force amplification frame to convert walking force into electricity. Compared to a stand-alone piezoelectric stack, experiments show an 8 times greater voltage output and a 112 times greater power output of such an energy harvester. A finite element method is used to provide a more accurate electromechanical model using Hamilton’s principle and the piezoelectric constitutive equations. Simulation results from such a finite element method agree with the single-degree-of-freedom model. Experimental measurement shows the percentage errors of the output power are of 3.53% for the finite element method and 8.04% for the single-degree-of-freedom model of the piezoelectric stack energy harvester.