PIR sensors

Narayana, Sujay; Prasad, R. Venkatesha; Rao, Vijay S.; Prabhakar, T. V.; Kowshik, Sripad S.; Iyer, Madhuri Sheethala

doi:10.1145/2737095.2742561

Cited by 75 publications

(13 citation statements)

References 15 publications

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“…Signal-based PIR sensors for localization: Signal-based methods are more popular for localization because they can receive more information from the signal. In the study by Narayana et al [ 88 ], the researchers explore the previously overlooked potential by examining the analog signals from an array of PIR sensors. This novel method enables the enhanced functions of PIR sensors, traditionally limited to binary detection tasks, to be fully utilized.…”

Section: Resultsmentioning

confidence: 99%

Passive Infrared Sensor-Based Occupancy Monitoring in Smart Buildings: A Review of Methodologies and Machine Learning Approaches

Shokrollahi,

Persson,

Malekian

et al. 2024

Sensors

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Buildings are rapidly becoming more digitized, largely due to developments in the internet of things (IoT). This provides both opportunities and challenges. One of the central challenges in the process of digitizing buildings is the ability to monitor these buildings’ status effectively. This monitoring is essential for services that rely on information about the presence and activities of individuals within different areas of these buildings. Occupancy information (including people counting, occupancy detection, location tracking, and activity detection) plays a vital role in the management of smart buildings. In this article, we primarily focus on the use of passive infrared (PIR) sensors for gathering occupancy information. PIR sensors are among the most widely used sensors for this purpose due to their consideration of privacy concerns, cost-effectiveness, and low processing complexity compared to other sensors. Despite numerous literature reviews in the field of occupancy information, there is currently no literature review dedicated to occupancy information derived specifically from PIR sensors. Therefore, this review analyzes articles that specifically explore the application of PIR sensors for obtaining occupancy information. It provides a comprehensive literature review of PIR sensor technology from 2015 to 2023, focusing on applications in people counting, activity detection, and localization (tracking and location). It consolidates findings from articles that have explored and enhanced the capabilities of PIR sensors in these interconnected domains. This review thoroughly examines the application of various techniques, machine learning algorithms, and configurations for PIR sensors in indoor building environments, emphasizing not only the data processing aspects but also their advantages, limitations, and efficacy in producing accurate occupancy information. These developments are crucial for improving building management systems in terms of energy efficiency, security, and user comfort, among other operational aspects. The article seeks to offer a thorough analysis of the present state and potential future advancements of PIR sensor technology in efficiently monitoring and understanding occupancy information by classifying and analyzing improvements in these domains.

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Section: Resultsmentioning

confidence: 99%

Passive Infrared Sensor-Based Occupancy Monitoring in Smart Buildings: A Review of Methodologies and Machine Learning Approaches

Shokrollahi,

Persson,

Malekian

et al. 2024

Sensors

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“…Sensor gerak dirancang khusus untuk deteksi manusia hal ini karena sensor ini peka terhadap gelombang panas manusia (8 -14 meter). Sensor gerak terdiri dari dua sensor inframerah, sehingga mampu mendeteksi perubahan suhu manusia dan suhu lingkungan ketika manusia melakukan gerakan [7]. Sensor cahaya yang digunakan dalam penelitian ini menggunakan IC opamp LM324 yang difungsikan sebagai rangkaian pembanding (comparator) dengan membandingkan intensitas cahaya matahari yang mengenai permukaan LDR dengan tegangan referensi yang dapat diatur sesuai dengan kebutuhan.…”

Section: Metode Dan Bahanunclassified

Lampu PJU Otomatis

Sutono¹,

Wicaksono²

2018

Komputika

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Tujuan dari penelitian ini untuk membantu Pemerintah dalam mengatasi krisis energi, terutama masalah Penerangan Jalan Umum. Di kota besar sangat dominan di temui lampu PJU yang memang merupakan sarana umum yang sangat vital terutama pada malam hari. Semakin banyak titik penempatan lampu PJU tentunya akan berdampak krisis energi walaupun ada suatu cara dengan mengganti lampu LED sebagai solusi dalam mengatasi krisis energi. atas dasar inilah Peneliti membuat rancangan lampu PJU dengan sumber listrik solar sel untuk mengurangi beban PLN yang sudah cukup besar dalam memenuhi kebutuhan listrik di kota besar seperti Jakarta, Bandung, Surabaya dan kota lainnya di Indonesia. Agar tujuan tersebut dapat terpenuhi, maka pada rancangan alat ini menggunakan multi sensor sehingga lampu PJU menyala pada malam hari dan terdapat objek di sekitar lampu PJU tersebut.

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“…Although the estimation of the occupancy count can further save the energy of the buildings, this requires a system that can accurately detect and give information about the occupancy. A passive infrared (PIR) sensor, usually used to measure the infrared light radiating from objects, has been widely employed to detect human movement and presence [11,13,14]. However, the displacement of the body from the PIR sensor, the speed, and the movement direction, reflects the analog output waves of PIR sensors.…”

Section: Introductionmentioning

confidence: 99%

Deep Learning-Based Industry 4.0 and Internet of Things towards Effective Energy Management for Smart Buildings

Elsisi

Tran

Mahmoud

et al. 2021

Sensors

131

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Worldwide, energy consumption and saving represent the main challenges for all sectors, most importantly in industrial and domestic sectors. The internet of things (IoT) is a new technology that establishes the core of Industry 4.0. The IoT enables the sharing of signals between devices and machines via the internet. Besides, the IoT system enables the utilization of artificial intelligence (AI) techniques to manage and control the signals between different machines based on intelligence decisions. The paper’s innovation is to introduce a deep learning and IoT based approach to control the operation of air conditioners in order to reduce energy consumption. To achieve such an ambitious target, we have proposed a deep learning-based people detection system utilizing the YOLOv3 algorithm to count the number of persons in a specific area. Accordingly, the operation of the air conditioners could be optimally managed in a smart building. Furthermore, the number of persons and the status of the air conditioners are published via the internet to the dashboard of the IoT platform. The proposed system enhances decision making about energy consumption. To affirm the efficacy and effectiveness of the proposed approach, intensive test scenarios are simulated in a specific smart building considering the existence of air conditioners. The simulation results emphasize that the proposed deep learning-based recognition algorithm can accurately detect the number of persons in the specified area, thanks to its ability to model highly non-linear relationships in data. The detection status can also be successfully published on the dashboard of the IoT platform. Another vital application of the proposed promising approach is in the remote management of diverse controllable devices.

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PIR sensors

Cited by 75 publications

References 15 publications

Passive Infrared Sensor-Based Occupancy Monitoring in Smart Buildings: A Review of Methodologies and Machine Learning Approaches

Passive Infrared Sensor-Based Occupancy Monitoring in Smart Buildings: A Review of Methodologies and Machine Learning Approaches

Lampu PJU Otomatis

Deep Learning-Based Industry 4.0 and Internet of Things towards Effective Energy Management for Smart Buildings

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