Low power wireless human detector utilizing thermopile infrared array sensor

Tanaka, J.; Imamoto, Hiroshi; Seki, T.; Oba, Masatoshi

doi:10.1109/icsens.2014.6985035

Cited by 14 publications

(8 citation statements)

References 1 publication

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“…Similarly, there has been recent works on using the TSA on human activity recognition, and abnormal behaviour detection [32]- [36]. The approach followed to process the TSA output is similar to image-processing approaches [37] while the analytical techniques on individual time intervals, frames, were different for instance Support Vector Machine (SVM) [12], Adaptive Boosting [6], [10], K-Nearest Neighbour (KNN) [30], [38], decision trees [20], [39], and Kalman filtering [40], [41]. One of the notable technical challenges reported in most human-based applications, which use TSA is that external heat sources have a major negative impact on the system performance.…”

Section: Related Workmentioning

confidence: 99%

Multiple Thermal Sensor Array Fusion Toward Enabling Privacy-Preserving Human Monitoring Applications

Naser

Lotfi

Zhong

2022

IEEE Internet Things J.

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Human-centric applications of a single Thermal Sensor Array (TSA) have performed extremely well in many areas. However, most of these works have not yet reached the real applicability stage of the Internet of Things (IoT) applications. The main limitation of deploying such systems on a large scale is the challenge of fusing multiple TSAs to cover a wide inspection area, e.g. smart homes, hospitals and many other domestic environments. On the other hand, objects that appear in the low-resolution thermal images acquired from TSA have low intra-class variations and high inter-class similarities, making the identification of the overlapping regions through matching a comparable template image in multiple images very difficult. This paper proposes a motion-based approach to fuse multiple TSAs and learn the domestic environment layout to enable further human-centred IoT applications to run in the cloud. Besides, a privacy-improvement on utilising these sensors in IoT applications is proposed. The proposed approach is evaluated with comprehensive experiments on different sensor placements and domestic environment conditions. This paper shows an average performance of 92.5% accuracy using various machine learning techniques and use case scenarios.

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Section: Related Workmentioning

confidence: 99%

Multiple Thermal Sensor Array Fusion Toward Enabling Privacy-Preserving Human Monitoring Applications

Naser

Lotfi

Zhong

2022

IEEE Internet Things J.

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“…V exploits K = 3 thermopile sensors. Each sensor consists of an array of 64 thermopile elements organized in 2D 8 × 8 images (Panasonic Grid-EYE model [23]). Each element independently measures the captured IR radiation and translates to temperature readings that are inputs of data pipeline i = 3 (in Fig.…”

Section: B Ir Array Sensors and Body-induced Thermal Signaturesmentioning

confidence: 99%

A Multisensory Edge-Cloud Platform for Opportunistic Radio Sensing in Cobot Environments

Kianoush

Savazzi

Beschi

et al. 2021

IEEE Internet Things J.

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Worker monitoring and protection in industrial production lines require advanced sensing capabilities and flexible solutions that are able to monitor the movements of the operator in proximity of moving robots. Considering that, in the context of human-robot collaborative (HRC) workplaces, no single technology can currently solve the problem of continuous worker monitoring, we propose the combination and transformation of multiple sensing technologies into a multisensory cloud-edge platform for passive sensing and perception. Multidimensional data acquisition, from different sources, pre-processing, manipulation, feature extraction, data distribution and fusion, along with distributed learning and computing methods are described. The platform proposes a practical solution for data fusion and analytics obtained from distributed heterogeneous sensor devices, that perform the opportunistic perception of the worker through radio signals, including WiFi, radars working in the sub-THz band and infrared sensors. The proposed platform performance is validated through real HRC use case scenarios inside a pilot industrial plant in which operator safety is guaranteed.

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“…Existing techniques are mostly based on frame-based computer vision approaches [4]. They consider analytics over individual time-slices (frames) of raw temperature measurements, ranging from K-nearest neighbor (K-NN) classifiers [11], [12], decision trees [14], [15], Kalman filtering [5], [16], support vector machines [8], [13] up to deep convolutional encoderdecoder networks [17]. Typical challenges in thermal vision need to face the temporal disappearance of the subjects [18], due to noisy readings and external heat sources that might be interpreted as false targets.…”

Section: A Related Workmentioning

confidence: 99%

Processing of Body-Induced Thermal Signatures for Physical Distancing and Temperature Screening

Savazzi

Rampa

Costa³

et al. 2021

IEEE Sensors J.

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Massive and unobtrusive screening of people in public environments is becoming a critical task to guarantee safety in congested shared spaces, as well as to support early non-invasive diagnosis and response to disease outbreaks. Among various sensors and Internet of Things (IoT) technologies, thermal vision systems, based on low-cost infrared (IR) array sensors, allow to track thermal signatures induced by moving people. Unlike contact tracing applications that exploit shortrange communications, IR-based sensing systems are passive, as they do not need the cooperation of the subject(s) and do not pose a threat to user privacy. The paper develops a signal processing framework that enables the joint analysis of subject mobility while automating the temperature screening process. The system consists of IR-based sensors that monitor both subject motions and health status through temperature measurements. Sensors are networked via wireless IoT tools and are deployed according to different configurations (wallor ceiling-mounted setups). The system targets the joint passive localization of subjects by tracking their mutual distance and direction of arrival, in addition to the detection of anomalous body temperatures for subjects close to the IR sensors. Focusing on Bayesian methods, the paper also addresses best practices and relevant implementation challenges using on field measurements. The proposed framework is privacy-neutral, it can be employed in public and private services for healthcare, smart living and shared spaces scenarios without any privacy concerns. Different configurations are also considered targeting both industrial, smart space and living environments.

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Low power wireless human detector utilizing thermopile infrared array sensor

Cited by 14 publications

References 1 publication

Multiple Thermal Sensor Array Fusion Toward Enabling Privacy-Preserving Human Monitoring Applications

Multiple Thermal Sensor Array Fusion Toward Enabling Privacy-Preserving Human Monitoring Applications

A Multisensory Edge-Cloud Platform for Opportunistic Radio Sensing in Cobot Environments

Processing of Body-Induced Thermal Signatures for Physical Distancing and Temperature Screening

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