Human identification using pyroelectric infrared sensors

The pyroelectric infrared (PIR) sensor with the lead-titanate (PbTiO3) thin film has been successfully fabricated. A RF planar magnetron sputter was used to deposit PbTiO3 thin film. A perovskite thin film can be obtained. From the properties measurement we can obtain the remanent polarization Pr=20.8μc/cm^2 and coercive electric field Ec=79.365 kV/cm. The pyroelectric coefficient of 1.09×10^(-5) C/m^2 K at 50℃ was measured as a function of temperature. In addition, the fabricated PIR sensor properties is RV=600 (VW^(-1)) when chopper frequency is 0.3 Hz. D*=7.3×10^5 cm Hz(superscript 1/2) W^(-1) for a modulation frequency of 0.5 Hz. In this experiment, the 4×4 array for PIR sensor is also constructed and tested.

Analysis of the multiple factors affecting human identification ability based on pyroelectric infrared technology is a complex problem. First, we examine various sensed pyroelectric waveforms of the human body thermal infrared signal and reveal a mechanism for affecting human identification. Then, we find that the mechanism is decided by the distance, human target, pyroelectric infrared (PIR) sensor, the body type, human moving velocity, signal modulation mask, and Fresnel lens. The mapping relationship between the sensed waveform and multiple influencing factors is established, and a group of mathematical models are deduced which fuse the macro factors and micro factors. Finally, the experimental results show the macro-factors indirectly affect the recognition ability of human based on the pyroelectric technology. At the same time, the correctness and effectiveness of the mathematical models is also verified, which make it easier to obtain more pyroelectric infrared information about the human body for discriminating human targets.

In this paper, a multimodal hand gesture detection and recognition system using differential Pyroelectric Infrared (PIR) sensors and a regular camera is described. Any movement within the viewing range of the differential PIR sensors are first detected by the sensors and then checked if it is due to a hand gesture or not by video analysis. If the movement is due to a hand, one-dimensional continuous-time signals extracted from the PIR sensors are used to classify/recognize the hand movements in real-time. Classification of different hand gestures by using the differential PIR sensors is carried out by a new winner-take-all (WTA) hash based recognition method. Jaccard distance is used to compare the WTA hash codes extracted from 1-D differential infrared sensor signals. It is experimentally shown that the multimodal system achieves higher recognition rates than the system based on only the on/off decisions of the analog circuitry of the PIR sensors(1).

Pyroelectric infrared (PIR) sensors can detect the presence of human without the need to carry any device, which are widely used for human presence detection in home/office automation systems in order to improve energy efficiency. However, PIR detection is based on the movement of occupants. For occupancy detection, PIR sensors have inherent limitation when occupants remain relatively still. Multisensor fusion technology takes advantage of redundant, complementary, or more timely information from different modal sensors, which is considered an effective approach for solving the uncertainty and unreliability problems of sensing. In this paper, we proposed a simple multimodal sensor fusion algorithm, which is very suitable to be manipulated by the sensor nodes of wireless sensor networks. The inference algorithm was evaluated for the sensor detection accuracy and compared to the multisensor fusion using dynamic Bayesian networks. The experimental results showed that a detection accuracy of 97% in room occupancy can be achieved. The accuracy of occupancy detection is very close to that of the dynamic Bayesian networks.

High sensitive pyroelectric infrared (IR) sensors have been fabricated by using c-axis oriented La-modified PbTiO3 (Pb1–xLaxTi1−x/4O3, PLT) thin films. The PLT thin films were deposited on (100)-cleaved MgO single crystal substrates by intermittent rf-magnetron sputtering method. The PLT thin films have high figures of merit for IR sensor without a poling treatment. High performance pyroelectric IR sensors (single element type and linear array type) were fabricated by using PLT (x=0·1, γ=5·5x10−8 C/cm2K, ϵr=200) thin films. The sensors have remarkably high D* of 3–6x108 cmHz1/2/W and very fast response. A new compact IR sensing system using the linear array sensor (8 elements) has been developed for a new type of room air-conditioner. This system can measure thermal distribution (8x64) by horizontal scanning of the vertical linear array. Image processing with neural network concept makes possible high-accuracy using a few data from the sensor elements. This sensing system provides ‘‘smart aircond...

Event Abstract Back to Event A Room-Level Indoor Location System for Smart Houses Seon-Woo Lee1* 1 Hallym University, Department of Electronic Engineering, South Korea It is well known that tracking and identifying people in an environment is an important issue in ambient intelligent systems [1]. Many indoor location-aware systems have some limitations, for example beacon-based methods require that the users need to carry tags or mobile devices. In contrast, the other methods such as Smart Floor [2] and our previous work [3] can provide two capabilities, user identification and user tracking without requirement of wearing any sort of devices or tags. This paper presents a room-level indoor location system for smart houses which can detect location transition such as entrance and exit to a room and also identify the user who passed the room, simultaneously. As shown in Fig. 1, we developed a wireless sensor node which has two pyroelectric infrared (PIR) sensors and an ultrasonic sensor, as well as a 2.4 GHz radio frequency wireless transceiver. The proposed sensor node was designed to have longer operation lifetime and the same two sensing capabilities of the previous prototype in [3]. The proposed user identification method is to discriminate a person based on his/her stature by using an ultrasonic sensor. The detection idea of entering/exiting behavior is based on order of triggering of two PIR sensors. The topology of the developed wireless sensor network system is simple star structure in which each sensor node is connected to one sink node directly as shown in Fig. 2. We evaluated the proposed sensing system with a set of experiments for three subjects in a model house. The experimental result shows that the averaged recognition rate of user identification is 81.3% for three persons, and perfect entering/exiting behavior detection performance. fig 1 fig 2

Traditional wheeled robots cannot easily adapt to complex home environments with stairs and doorsills. This paper presents the design and implementation of a novel wireless sensor network based home security system with a modular self-reconfigurable robot (Transmote) as the mobile node. The security system is composed of some static monitoring nodes, a Transmote, and a home server. Static nodes with pyroelectric infrared (PIR) sensor and digital camera are mounted on doorframes and windows to detect intruders and send intrusion alarm messages to the home server. Transmote with PIR sensor and camera can patrol in the house for security surveillance. Transmote also can provide network repairing service when some static router nodes fail. Transmote modules and static monitoring nodes are controlled by two different wireless sensor networks. The remote house owner can get the alarm messages through Internet. Transmote can transform into I-shaped or O-shaped configuration according to different locomotion requirements. A prototype system has been implemented and some performance tests have been done. Experimental results show that the I-shaped Transmote can pass through an 8.8 cm high and 10 cm wide channel. The velocity of the I-shaped Transmote is up to 3 m/min and the maximum velocity of O-shaped Transmote is 9.3 m/min. A 12 kB captured photo can be transmitted to the gateway through 15 hops without any packet loss.

Pyroelectric Infrared (PIR) sensors are low-cost, low-power, and highly reliable sensors that have been widely used in smart environments. Indoor localization systems can be categorized as wearable and non-wearable systems, where the latter are also known as device-free localization systems. Since the binary PIR sensor detects only the presence of a human motion in its field of view (FOV) without any other information about the actual location, utilizing the information of overlapping FOV of multiple sensors can be useful for localization. In this study, a PIR detector and sensing signal processing algorithms were designed based on the characteristics of the PIR sensor. We applied the designed PIR detector as a sensor node to create a non-wearable cooperative indoor human localization system. To improve the system performance, signal processing algorithms and refinement schemes (i.e., the Kalman filter, a Transferable Belief Model, and a TBM-based hybrid approach (TBM + Kalman filter)) were applied and compared. Experimental results indicated system stability and improved positioning accuracy, thus providing an indoor cooperative localization framework for PIR sensor networks.

For the purpose of detecting human group activity and its recognition, a novel algorithm based on heat map is presented using PIR sensors in order to optimize the targeted digital advertising in shopping complexes. Firstly, we use the PIR (pyroelectric infrared) sensors to detect the presence of people. The projected algorithm first represents trajectories of people as sequence of “heat sources” followed by the application of a thermal diffusion process to consequently generate a heat map (HM) in order to depict and illustrate the group activities. The heat maps are generated with respect to multiple factors like temporal factors such as time of day and day of week/month, cultural factors such as during festivals or other notable occasions, etc. The generated heat map brings forth an original surface fitting (SF) method, which can also be applied for identifying human group activities in academic buildings and hostel blocks. The proposed heat map can effectively retain the temporal motion knowledge of the crowd of humans, and the proposed surface fitting can efficiently fetch the features of the heat map for activity discovery and perception. By using heat maps in targeted digital advertising, signs and billboards can be optimized.

This article proposes a compressive infrared sampling method in pursuit of the acquisition and processing of human motion simultaneously. The spatial-temporal changes caused by the movements of the human body are intrinsical clues for determining the semantics of motion, while the movements of short-term changes can be considered as a sparse distribution compared with the sensing region. Several pyroelectric infrared (PIR) sensors with pseudo-random-coded Fresnel lenses are introduced to acquire and compress motion information synchronously. The compressive PIR array has the ability to record the changes in the thermal radiation field caused by movements and encode the motion information into low-dimensional sensory outputs directly. Therefore, the problem of recognizing a high-dimensional image sequence is cast as a low-dimensional sequence recognition process. A database involving various kinds of motion played by several people is built. Hausdorff distance-based template matching is employed for motion recognition. Experimental studies are conducted to validate the proposed method.

PIR (Pyroelectric InfraRed) sensors can be used to detect the presence of humans without the need for them to wear any device. By construction, the fields of view of the sensors are not uniform both in terms of vision space and of sensitivity. The aim of this work is twofold: to provide a probabilistic model of the sensors’ detection sensitivity with respect to the movement of the person and of his/her emission surface, and to identify the probability of detection within an area covered by multiple PIR sensors. This allows the computation of the coverage of the PIRs and their optimal arrangement that maximizes the probability of detection of the person.

Measurement uncertainty analysis of centering error of pyroelectric infrared sensor module

Scarce energy budget of battery-powered wireless sensor nodes calls for cautious power management not to compromise performance of the system. To reduce both energy consumption and delay in energy-hungry wireless sensor networks for latency-restricted surveillance scenarios, this paper proposes a multimodal two-tier architecture with wake-up radio receivers. In video surveillance applications, using information from distributed low-power pyroelectric infrared (PIR) sensors, which detect human presence limits the activity of cameras and reduces their energy consumption. PIR sensors transmit the information about the event to camera nodes using wake-up radio receivers. We show the benefits of wake-up receivers over duty cycling in terms of overcoming energy consumption versus latency tradeoff (proved with two orders of magnitude lower latency-only 9 ms). At the same time, the power consumption of the camera node, including a wake-up receiver is comparable with the one having only duty-cycled main transceiver with 1% duty cycle (about 32 mW for 25 activations per hour).

High-quality La-modified PbTiO3 (Pb1−xLaxTi1−x/4O3; PLT) thin films were prepared by an rf-magnetron sputtering method. In this method, intermittent deposition was realized by periodical repetition of deposition and nondeposition processes. This deposition was found to enhance the horizontal grain growth of the films. The PLT thin films exhibit the phenomena named “self-polarization” and have high pyroelectric properties (pyroelectric coefficient γ of 5.0×10−8C/cm2K and low dielectric constant εr of 185) without a poling treatment. It was interestingly found that this self-polarization of the PLT thin films depends on the substrate temperature (Ts) and is based on a fairly small difference of the film composition (Pb/Ti). The pyroelectric properties were improved by means of addition of Mg to the PLT thin films. These thin films are expected to offer suitable materials for pyroelectric infrared (IR) sensors. High sensitive pyroelectric IR sensors (single element type and linear array type) were fabricated by using the PLT (x=0. 1) thin films with the new structures and the device processes. The sensors have remarkably high specific detectivity D* of 3.5×108 cm. Hz1/2/W and very fast response. A new compact IR sensing system using the linear array sensor (8 elements) has been developed for a new type of room air-conditioner.

In this study, An optimization on a structure of Pb(Zr,Ti)O3 (PZT) thin film pyroelectric infrared (IR) sensor was investigated. Since the pyroelectric sensor detects the temperature change of the PZT film, the temperature of the PZT film is required to keep changing in detection time periods in order to obtain high detectivity. Therefore optimal pyroelectric sensor structures were investigated by transient heat transfer analysis using finite element model for fabrication of pyroelectric IR sensor with high performance. Various sensor models were simulated to investigate effects of parameters such as lengths, widths, and thickness of the sensor structures. As a result, the optimal PZT film pyroelectric sensor structure can be obtained from transient heat transfer analysis.