Indoor Air Quality Monitoring Using Infrastructure-Based Motion Detectors

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dc.contributor.author Hossein Motlagh, Naser
dc.contributor.author Zaidan, Martha
dc.contributor.author Lagerspetz, Eemil
dc.contributor.author Varjonen, Samu
dc.contributor.author Toivonen, Juhani
dc.contributor.author Mineraud, Julien
dc.contributor.author Rebeiro-Hargrave, Andrew
dc.contributor.author Siekkinen, Matti
dc.contributor.author Hussein, Tareq
dc.contributor.author Nurmi, Petteri
dc.contributor.author Tarkoma, Sasu
dc.date.accessioned 2020-01-31T14:35:02Z
dc.date.available 2020-01-31T14:35:02Z
dc.date.issued 2019
dc.identifier.citation Hossein Motlagh , N , Zaidan , M , Lagerspetz , E , Varjonen , S , Toivonen , J , Mineraud , J , Rebeiro-Hargrave , A , Siekkinen , M , Hussein , T , Nurmi , P & Tarkoma , S 2019 , Indoor Air Quality Monitoring Using Infrastructure-Based Motion Detectors . in Proceedings : 2019 IEEE 17th International Conference on Industrial Informatics (INDIN) . vol. 1 , IEEE International Conference on Industrial Informatics (INDIN) , vol. 1 , IEEE , pp. 902-907 , 17th International Conference on Industrial Informatics (INDIN) , Helsinki , Finland , 22/07/2019 . https://doi.org/10.1109/INDIN41052.2019.8972332
dc.identifier.citation conference
dc.identifier.other PURE: 124496865
dc.identifier.other PURE UUID: d8a52c50-7f55-4ef3-b438-8bdb79844c31
dc.identifier.other ORCID: /0000-0002-0241-6435/work/68614915
dc.identifier.other ORCID: /0000-0001-7527-5787/work/68616548
dc.identifier.other ORCID: /0000-0002-6348-1230/work/68617676
dc.identifier.other ORCID: /0000-0003-3875-8135/work/68617965
dc.identifier.other ORCID: /0000-0001-9923-9879/work/68618031
dc.identifier.other WOS: 000529510400133
dc.identifier.uri http://hdl.handle.net/10138/310796
dc.description.abstract Poor indoor air quality is a significant burden to society that can cause health issues and decrease productivity. According to research, indoor air quality is intrinsically linked with human activity and mobility. Indeed, mobility is directly linked with transfer of small particles (e.g. PM2.5) and extent of activity affects production of CO2. Currently, however, estimation of indoor quality is difficult, requiring deployment of highly specialized sensing devices which need to be carefully placed and maintained. In this paper, we contribute by examining the suitability of infrastructure-based motion detectors for indoor air quality estimation. Such sensors are increasingly being deployed into smart environments, e.g., to control lighting and ventilation for energy management purposes. Being able to take advantage of these sensors would thus provide a cost-effective solution for indoor quality monitoring without need for deploying additional sensors. We perform a feasibility study considering measurements collected from a smart office environment having a dense deployment of motion detectors and correlating measurements obtained from motion detectors against air quality values. We consider two main pollutants,PM2.5 and CO2, and demonstrate that there indeed is a connection between extent of movement and PM2.5concentration. However, for CO2, no relationship can be established, mostly due to difficulties in separating between people passing by and those residing long-term in the environment. en
dc.format.extent 6
dc.language.iso eng
dc.publisher IEEE
dc.relation.ispartof Proceedings
dc.relation.ispartofseries IEEE International Conference on Industrial Informatics (INDIN)
dc.relation.isversionof 978-1-7281-2927-3
dc.rights.uri info:eu-repo/semantics/openAccess
dc.subject 113 Computer and information sciences
dc.title Indoor Air Quality Monitoring Using Infrastructure-Based Motion Detectors en
dc.type Conference contribution
dc.contributor.organization Department of Computer Science
dc.contributor.organization Global Atmosphere-Earth surface feedbacks
dc.contributor.organization INAR Physics
dc.contributor.organization Institute for Atmospheric and Earth System Research (INAR)
dc.contributor.organization Air quality research group
dc.contributor.organization Content-Centric Structures and Networking research group / Sasu Tarkoma
dc.contributor.organization Helsinki Institute for Information Technology
dc.description.reviewstatus Peer reviewed
dc.relation.doi https://doi.org/10.1109/INDIN41052.2019.8972332
dc.relation.issn 2378-363X
dc.rights.accesslevel openAccess
dc.type.version acceptedVersion

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