An information technology enabled sustainability test-bed (ITEST) for occupancy detection through an environmental sensing network

Dong, Bing; Andrews, Burton W.; Lam, Khee Poh; Höynck, Michael; Zhang, Rui; Chiou, Yun Shang; Benítez, Diego S.

doi:10.1016/j.enbuild.2010.01.016

Cited by 301 publications

(185 citation statements)

References 10 publications

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“…In [5] a wireless sensor network (WSN) test-bed of air quality and CO 2 sensors in an office space was implemented. Using Hidden Markov models to process the information from the sensors they could count the number of occupants (ranging from 1 to 5) with an average accuracy of 75%.…”

Section: A Discussionmentioning

confidence: 99%

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Measuring building occupancy using existing network infrastructure

Melfi

Rosenblum

Nordman

et al. 2011

2011 International Green Computing Conference and Workshops

136

112

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Abstract-The primary focus of Green IT has been on reducing energy use of the IT infrastructure itself. Additional significant energy savings can be achieved by using the IT infrastructure to enable energy savings in both the IT and non-IT infrastructure. Our premise is that energy can be saved by driving building operation on information gleaned from existing IT infrastructure already installed for non-energy purposes. We call our idea implicit occupancy sensing where existing IT infrastructure can be used to replace and/or supplement traditional dedicated sensors to determine building occupancy. Our implicit sensing methods are largely based on monitoring MAC and IP addresses in routers and wireless access points, and then correlating these addresses to the occupancy of a building, zone, and/or room. Occupancy data can be used to control lighting, HVAC, and other building functions to improve building functionality and reduce energy use. We experimentally evaluate the feasibility of this dual-use of IT infrastructure and assess the accuracy of implicit sensing. Our findings, based on data collected from two facilities, show that there is significant promise in implicit sensing using the existing IT infrastructure present in most modern nonresidential buildings.

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Section: A Discussionmentioning

confidence: 99%

“…Microphones on PC's, notebooks, and phones could provide occupant counts and identification based on sound levels or conversations. In [5] work has been done in relating acoustics to occupancy using dedicated sensors. The use of a webcam to detect occupants in front of a computer has already been demonstrated in [3].…”

Section: B Tier IImentioning

confidence: 99%

Measuring building occupancy using existing network infrastructure

Melfi

Rosenblum

Nordman

et al. 2011

2011 International Green Computing Conference and Workshops

136

112

View full text Add to dashboard Cite

show abstract

“…Data are acquired by measurement the conditions in the room for is used for calculating the amount of energy actually required and for control the distribution routes for efficient air distribution. As stated in [2,3], there are besides CO2 other measuring technologies which are experimentally tested, according [4,5] were tested even their combinations for their complementing, however, each technology has its own restrictions. Today´s most used CO2 sensors occupancy estimation is relatively exact but may interfere with long responsive time and air circulation patterns must be known.…”

Section: Next Steps In Research and Validation Of The Models And Discmentioning

confidence: 99%

Development the tool for demand control ventilation systems elements design and their impact to building life-cycle assessment: a review

Pinka

2018

MATEC Web Conf.

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Abstract. The paper describes possible methodology for DCV -demand control ventilation design process which will lead to solving the most important problems of more accurate ventilation system design, the efficiency: time and costs of design while improving its effectivity (level of design confidence, degree of uncertainty, financial parameters). For this purpose it has been started developing the tool implementing the methodology. Furthermore, it describes steps of testing and validation design process by implementation state-of-the-art algorithms for measuring the occupancy or CO2 detection for DCV system control testing sites and their comparison with computation design results. It describes also the reasons and necessity of decomposition of whole ventilation system to specific elements for the design and assessment procedure.

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“…However, these studies have fallen far short of the maximum level of achievable energy efficiency. In [9] a study was carried out which showed a significant correlation between number of occupants and certain environmental measurements which can give 75% accuracy in number detection. These results were obtained for office environments and so it is difficult to apply these results to industrial environments where the parameters measured may have no relationship with number of occupants (for example, acoustic measurements).…”

Section: Introductionmentioning

confidence: 99%

Energy efficiency improvements through surveillance applications in industrial buildings

Silvestre-Blanes

Pérez-Lloréns

2011

Energy and Buildings

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Presence sensors for energy control based on classic technologies to detect movement are now commonly seen in many areas of life. However, their use in structurally complex environments is not very common, due to their lack of reliability in these types of situations. Falling prices in technologies associated with surveillance applications are leading to a huge increase in their use in all types of environment, with monitoring of traffic and people the most common of these. In this work, we carry out an analysis of occupancy patterns in manufacturing industries with the aim of determining the possible energy savings that could be obtained using these new technologies. We also carry out an analysis of the possibilities of using these technologies as presence sensors, analyzing the trends and limitations associated with them.

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An information technology enabled sustainability test-bed (ITEST) for occupancy detection through an environmental sensing network

Cited by 301 publications

References 10 publications

Measuring building occupancy using existing network infrastructure

Measuring building occupancy using existing network infrastructure

Development the tool for demand control ventilation systems elements design and their impact to building life-cycle assessment: a review

Energy efficiency improvements through surveillance applications in industrial buildings

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