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Intelligently controlling HVAC with IoT technology

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dc.date.accessioned 2020-12-08T11:29:16Z
dc.date.available 2020-12-08T11:29:16Z
dc.date.issued 2020-12-08
dc.identifier.uri http://hdl.handle.net/123456789/32376
dc.title Intelligently controlling HVAC with IoT technology en
ethesis.discipline none und
ethesis.department none und
ethesis.faculty Matemaattis-luonnontieteellinen tiedekunta fi
ethesis.faculty Faculty of Science en
ethesis.faculty Matematisk-naturvetenskapliga fakulteten sv
ethesis.faculty.URI http://data.hulib.helsinki.fi/id/8d59209f-6614-4edd-9744-1ebdaf1d13ca
ethesis.university.URI http://data.hulib.helsinki.fi/id/50ae46d8-7ba9-4821-877c-c994c78b0d97
ethesis.university Helsingin yliopisto fi
ethesis.university University of Helsinki en
ethesis.university Helsingfors universitet sv
dct.creator Rinta-Homi, Mikko
dct.issued 2020
dct.language.ISO639-2 eng
dct.abstract Heating, ventilation, and air conditioning (HVAC) systems consume massive amounts of energy. Fortunately, by carefully controlling these systems, a significant amount of energy savings can be achieved. This requires detecting a presence or amount of people inside the building. Countless different sensors can be used for this purpose, most common being air quality sensors, passive infrared sensors, wireless devices, and cameras. A comprehensive review and comparison are done for these sensors in this thesis. Low-resolution infrared cameras in counting people are further researched in this thesis. The research is about how different infrared camera features influence counting accuracy. These features are resolution, frame rate and viewing angle. Two systems were designed: a versatile counting algorithm, and a testing system which modifies these camera features and tests the performance of the counting algorithm. The results prove that infrared cameras with resolution as low as 4x2 are as accurate as higher resolution cameras, and that frame rate above 5 frames per second does not bring any significant advantages in accuracy. Resolution of 2x2 is also sufficient in counting but requires higher frame rates. Viewing angles need to be carefully adjusted for best accuracy. In conclusion, this study proves that even the most primitive infrared cameras can be used for accurate counting. This puts infrared cameras in a new light since primitive cameras can be cheaper to manufacture. Therefore, infrared cameras used in occupancy counting become significantly more feasible and have potential for widespread adoption. en
dct.subject IoT
dct.subject HVAC
dct.subject Infrared cameras
dct.language en
ethesis.isPublicationLicenseAccepted true
ethesis.language.URI http://data.hulib.helsinki.fi/id/languages/eng
ethesis.language englanti fi
ethesis.language English en
ethesis.language engelska sv
ethesis.thesistype pro gradu -tutkielmat fi
ethesis.thesistype master's thesis en
ethesis.thesistype pro gradu-avhandlingar sv
ethesis.thesistype.URI http://data.hulib.helsinki.fi/id/thesistypes/mastersthesis
dct.identifier.ethesis E-thesisID:39a6c475-addc-4cad-8f0f-bd3174d147c7
dct.identifier.urn URN:NBN:fi:hulib-202012084727
dc.type.dcmitype Text
ethesis.facultystudyline Hajautetut järjestelmät ja tietoliikenne fi
ethesis.facultystudyline Networking and Services en
ethesis.facultystudyline Distribuerade system och datakommunikation sv
ethesis.facultystudyline.URI http://data.hulib.helsinki.fi/id/SH50_084
ethesis.mastersdegreeprogram Tietojenkäsittelytieteen maisteriohjelma fi
ethesis.mastersdegreeprogram Master's Programme in Computer Science en
ethesis.mastersdegreeprogram Magisterprogrammet i datavetenskap sv
ethesis.mastersdegreeprogram.URI http://data.hulib.helsinki.fi/id/MH50_009

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