Single-Pixel Thermopile Infrared Sensing for People Counting

Abstract

People-counting data can be used in buildingcontrol systems to improve comfort and in space management applications to optimize building space. In this work, we consider a combi-sensor with a single-pixel thermopile and passive infrared sensor for people counting. We first develop a thermopile signal model for object temperature measurements under multiple people occupancy. We then propose a people counting method based on: cumulative sum (CUSUM) change detection in the object temperature signal, forming a people count estimate using likelihoods of differential mean temperature in detected changes, and decision fusion with an infrared vacancy sensor. The proposed method is evaluated with data generated using the developed signal model as well as experimental data from a cell office/meeting room environment. We obtain an average counting error of 0.11 and 0.19 for 90% of the instants respectively when considering 15 minute windows for simulated and experimental datasets.

An Excess Kurtosis People Counting System Based on 1DCNN-LSTM Using Impulse Radio Ultra-Wide Band Radar Signals

“…Based on the human signals extracted by changing the threshold, the algorithm formed a frame using the W signals in the slow time direction and then extracted the feature vector from it. Given W, the nth slow time-indexed frame F (T n ,T m ) [n] is expressed as shown in Equation (11).…”

“…An RFID-based [7,8] people counting method is not convenient for daily use and maintenance due to the considerable number of RF sensor devices required. Besides RF-based people counting methods, there are also detection methods using (Passive Infrared Detectors) PIR [11] and thermal imaging-based techniques [12]. PIR-based detection methods are simple in principle and in terms of equipment and exhibit low algorithmic complexity; however, they are susceptible to detection failures under the effect of the surrounding temperature.…”