Occupancy Monitoring Using Passive RFID Technology for Efficient Building Lighting Control

Manzoor, Farhan; Linton, D.; Loughlin, Michael

doi:10.1109/rfid.2012.10

Cited by 29 publications

(17 citation statements)

References 8 publications

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“…Previous studies introduced various approaches to office buildings in order to save energy on lighting [3][4][5][6][7][8][9][10][11]. One approach is daylight-linked control, which adjusts the dimming level of lights based on illumination intensity in accordance with the amount of daylight and artificial light [3][4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

“…One approach is daylight-linked control, which adjusts the dimming level of lights based on illumination intensity in accordance with the amount of daylight and artificial light [3][4][5][6][7]. Another approach is individual occupancy control (IC), which turns on only lights that are close to occupants (people at the office) [3,[8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

“…The energy savings of daylight-linked control range from 20 to 31%, depending on the amount of available daylight [3][4][5]. In addition, the energy savings of IC range from 13 to 35%, depending on the occupancy patterns or types of work [3,8,11].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Experimental evaluation for daylight‐linked gradation lighting control using image‐based motion sensors

Futagami

Yano

Huang

et al. 2020

IEEJ Transactions Elec Engng

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In this study, we propose a daylight‐linked gradation lighting control, which adjusts the dimming level of a light above an occupant according to daylight and also gradually lowers the dimming level of surrounding lights based on the distance from the occupants by using image‐based motion sensors. We evaluated it in terms of both energy savings and visual comfort of the occupants in comparison experiments. Compared with the individual occupancy control (IC), the actual and simulated median energy savings of daylight‐linked gradation control (DGC) were 27.1 and 28.9%, respectively, per day. The results of a questionnaire consisting of seven questions and using a semantic differential method for scoring visual comfort showed that the DGC tended to improve visual comfort compared with the IC. Further experiments, however, are needed as only four of nine occupants responded to the questions. In addition, we found that the DGC creates a smoother contrast in the office than the IC, which may produce conspicuous changes in illumination intensity. Finally, we analyzed the advantages and disadvantages of the DGC on the basis of our experimental results. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Experimental evaluation for daylight‐linked gradation lighting control using image‐based motion sensors

Futagami

Yano

Huang

et al. 2020

IEEJ Transactions Elec Engng

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“…Since Wi-Fi signals distribute indoor space like air surrounding it and will be reflected by human body, [33]. On the other hand, Manzoor proposed a study for efficient building lighting control by monitoring occupancy with passive RFID technology, which proved 13% of electrical energy savings [34]. Li et al reported the average accuracy of RFID systems was 88% for stationary occupants and 62% for mobile occupants [35].…”

Section: Occupancy Studies With Single Data Typementioning

confidence: 99%

Cross-source sensing data fusion for building occupancy prediction with adaptive lasso feature filtering

Wang

Hong

et al. 2019

Building and Environment

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Fusing various sensing data sources is able to improve the accuracy and reliability of building occupancy detection. Efficiently fusing environmental sensors and wireless network signals is seldom studied for its computational and technical challenges. This study aims to propose an integrated model that is able to extract critical data features for environmental and Wi-Fi probe dual sensing sources to promote computational efficiency. The adaptive lasso model was introduced for the feature extraction and reduction process. To validate the proposed model, an onsite experiment was conducted and two occupancy resolutions, real-time and four-level occupancy resolutions, were compared. The results suggested that eight features among all twelve features are most relevant. The mean absolute error of the selected data features is about 2.18 for real-time occupancy and F1_accuracy is about 84.36% for four-level occupancy.

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“…In a hospital environment, it is important to consider data protection, that is anonymity of the people, as well as accurate detection of people whether they are as individuals or in groups. Prior research work has proposed the use of various technologies such as Radio Frequency Identification (RFID) [6], [8], Wi-Fi [9] and sensor networks [10], [11], [12], [13] to monitor occupancy.…”

Section: Overview Of People Counting Technologiesmentioning

confidence: 99%

Design of an Occupancy Monitoring Unit: A Thermal Imaging Based People Counting Solution for Socio-Technical Energy Saving Systems in Hospitals

Taha

Krabicka

et al. 2019

2019 11th Computer Science and Electronic Engineering (CEEC)

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Aside from their physical exterior/interior design, the energy demands of industrial buildings are strongly related to how they are used. It follows that the behaviour of the occupants contributes and is related to the energy consumption of a building. In a hospital, this could mean equipment usage, heating, water and so on. This implies that energy consumption in a specific area may be measured as a function of occupancy, making occupancy monitoring an important part of an organisation's energy management plan. This paper presents the design, implementation and testing of an Occupancy Monitoring Unit (OMU), based on thermal imaging technology, to provide occupancy data on individual selected wards/areas of Medway NHS Foundation Trust (MWNFT). The paper also presents successful tests performed to assess the functionality of the OMU in counting people and identifying the direction of motion. The results show the potential for the OMU to count individual people as well as groups.

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Occupancy Monitoring Using Passive RFID Technology for Efficient Building Lighting Control

Cited by 29 publications

References 8 publications

Experimental evaluation for daylight‐linked gradation lighting control using image‐based motion sensors

Experimental evaluation for daylight‐linked gradation lighting control using image‐based motion sensors

Cross-source sensing data fusion for building occupancy prediction with adaptive lasso feature filtering

Design of an Occupancy Monitoring Unit: A Thermal Imaging Based People Counting Solution for Socio-Technical Energy Saving Systems in Hospitals

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