Data mining a three dimensional beehive content monitoring system

dc.contributor.authorBuhr, Phiona
dc.contributor.examiningcommitteeJeffrey, Ian (Electrical and Computer Engineering)en_US
dc.contributor.examiningcommitteeFerens, Ken (Electrical and Computer Engineering)en_US
dc.contributor.supervisorShafai, Cyrus
dc.date.accessioned2022-08-25T13:53:41Z
dc.date.available2022-08-25T13:53:41Z
dc.date.copyright2022-08-24
dc.date.issued2022-08-24
dc.date.submitted2022-08-24T17:03:37Zen_US
dc.date.submitted2022-08-24T22:32:38Zen_US
dc.degree.disciplineElectrical and Computer Engineeringen_US
dc.degree.levelMaster of Science (M.Sc.)en_US
dc.description.abstractData from a novel capacitive sensor array developed at the University of Manitoba, temperature sensors, humidity sensors, and light sensors placed inside a beehive for a summer is analysed using various time series analysis and data mining techniques. The goal of the analyses are to create features relevant in tracking honey production, detecting swarming, and detecting clustering events. The secondary goal of this thesis is to outline the current state of precision beekeeping in order to understand how this novel capacitive sensor array fits into the greater world of precision beekeeping. This work is a first step in the analytic requirements for the ultimate goal of automating beekeeping using data from sensors like these. Data from this novel capacitive sensor array demonstrated performance unrivalled by other content monitoring methods currently used in precision beekeeping.en_US
dc.description.noteOctober 2022en_US
dc.identifier.urihttp://hdl.handle.net/1993/36757
dc.language.isoengen_US
dc.rightsopen accessen_US
dc.subjectPrecision beekeepingen_US
dc.subjectPrecision agricultureen_US
dc.subjectData miningen_US
dc.titleData mining a three dimensional beehive content monitoring systemen_US
dc.typemaster thesisen_US
local.subject.manitobanoen_US
project.funder.identifierhttps://doi.org/10.13039/501100000038en_US
project.funder.nameNSERCen_US
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