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dc.contributoren-US
dc.creatorMora, Dafni
dc.creatorDe Simone, Marilena
dc.creatorFajilla, Gianmarco
dc.creatorFábrega, José
dc.date2018-02-11
dc.date.accessioned2018-02-23T17:18:32Z
dc.date.available2018-02-23T17:18:32Z
dc.identifierhttps://knepublishing.com/index.php/KnE-Engineering/article/view/1474
dc.identifier10.18502/keg.v3i1.1474
dc.identifier.urihttp://ridda2.utp.ac.pa/handle/123456789/4379
dc.descriptionSensors were applied in an office building to obtain information regarding user presence and absence intervals. Occupancy was also recorded by manual observation, and indoor parameters such as air temperature, relative humidity, carbon dioxide (CO2), volatile organic compounds (VOC) were monitored. Occupants’ behaviors regarding door/window (open/closed) and electric power were considered.  Clustering analysis by manual observation was employed to identify similarities in daily or monthly occupancy and to describe possible occupancy profiles. Similar approach was carried out with each monitored parameter and the results of clustering elaboration were compared with the real occupancy profiles to identify which sensor is more effective to measure office occupancy. Furthermore, data were analyzed to explore relationships between occupancy and the magnitude of indoor environmental changes with the objective to identify daily, weekly, or monthly patterns.  Single-linkage, complete-linkage, and average-linkage clustering were applied to each dataset. The cophenetic correlation coefficient was used to verify the quality of the results obtained for each variable, and the complete linkage was selected to define the groups. Comparison between occupancy real data clustering and VOC and open/closed door groups demonstrated not similarities. The electricity consumption and CO2 data showed some similarities.Keywords: Occupancy detection, environmental sensor, clustering analysis, Office buildingsen-US
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dc.formatapplication/pdf
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dc.languageeng
dc.publisherKnE Publishingen-US
dc.relationhttps://knepublishing.com/index.php/KnE-Engineering/article/view/1474/3284
dc.relationhttps://knepublishing.com/index.php/KnE-Engineering/article/view/1474/3551
dc.relationhttps://knepublishing.com/index.php/KnE-Engineering/article/view/1474/3552
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttps://creativecommons.org/licenses/by/4.0/
dc.source2518-6841
dc.sourceKnE Engineering; 6th Engineering, Science and Technology Conference - Panama 2017 (ESTEC 2017); 711-720en-US
dc.titleOccupancy profiles modelling based on Indoor Measurements and Clustering Analysis: Application in an Office Buildingen-US
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion


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  • 2017: 6th Engineering, Science and Technology Conference - Panama (ESTEC 2017)
    The 6th Engineering, Science and Technology Conference (ESTEC 2017) organized by the Universidad Tecnologica de Panama (UTP) is the most relevant conference, engineering-based, of our country. The topics of the conference are focused on areas of interest of Panama and the Latin America region, including: agroindustry, astronomy, bioengineering, education on engineering, energy and environment, ICT engineering, infrastructure and construction, logistics and transportation, manufacturing processes and material science, robotic, automation and artificial intelligence. This year, ESTEC partnered with IEEE Panama Section to ensure the quality of the peer-reviewed process; we received more than 180 full papers from 20 countries and 50% of those were accepted to participate in the conference and will be published in the conference’s proceeding. Furthermore, the conference included technical tours to the Cocoli’s Gate and the Miraflores Visitors Center of The Panama Canal and to the Wind Power Park in Penonome, Panama.

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