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Occupancy Detection and Localization by Monitoring Nonlinear Energy Flow of a Shuttered Passive Infrared Sensor

机译:通过监视快门式被动红外传感器的非线性能量流来进行占空检测和定位

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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 paper, 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 m, and moving detection for up to 8 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 for tracking, and over 83% in detecting front/back or side facing direction.
机译:被动红外(PIR)传感器是建筑物中个体存在检测的当前选择。一个主要问题是,PIR传感器仅检测移动中的个人,通常会提供错误的阴性检测结果,从而导致不舒服的照明/温度波动,设备使用寿命短以及能源浪费。在本文中,旋转快门被引入到旋转快门PIR(Ro-PIR)传感器中,以探索其在运动感测之外的功能,包括静止的个体定位,跟踪和面向方向的检测。更具体地说,通过监视和分析由旋转快门引起的非线性红外能量流的极性相位,Ro-PIR能够对静止个体进行区域级定位。通过进一步分析输出的占空比,可以预测占用方向。通过分析三种由快门移动形成的红外辐射覆盖配置,创建了两个理论模型来识别面对的方向(正面/背面或侧面)。覆盖配置的组合序列表示感应的极性-相输出电压,示出在一个分段的扫描周期内的占用位置信息。进行参数分析和实证研究以获得关于百叶窗的宽度和百叶窗周期的最佳设置。实验结果表明,对于3m的静止检测和8m的移动检测,存在100%的存在精度。通过使用从极性相位信号提取的两个特征的机器学习分类器,区域级定位可以达到98%的精度。实验结果还显示,跟踪的均方根误差小于0.44 m,而检测前后方向或侧面方向的均方根误差超过83%。

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