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A Prototype Model of Monitoring Energy Consumption and Optimizing Distribution of Smart Buildings

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dc.contributor.authorShalaby A.M.en_US
dc.contributor.authorSidhu M.S.en_US
dc.contributor.authorTan W.C.en_US
dc.contributor.authorWei L.Z.en_US
dc.contributor.authorYong C.J.en_US
dc.contributor.authorXi L.Y.en_US
dc.contributor.authorid57972325200en_US
dc.contributor.authorid56259597000en_US
dc.contributor.authorid57169386900en_US
dc.contributor.authorid57972111900en_US
dc.contributor.authorid57971500700en_US
dc.contributor.authorid57971500800en_US
dc.date.accessioned2023-05-29T09:39:15Z
dc.date.available2023-05-29T09:39:15Z
dc.date.issued2022
dc.descriptionEducation computing; Energy utilization; Intelligent buildings; Internet of things; Long short-term memory; Open systems; Particle swarm optimization (PSO); Remote control; Arduino; Firebase; Firestore; LSTM; MQTT broker; Neural-networks; Opencv; PSO; Raspberry PI; Weather API; Pythonen_US
dc.description.abstractGiven the upcoming post-pandemic times, there are more universities considering adopting the hybridization model. As such, not all the facilities and building utilities will be fully utilized as only half of the student population will be expected, thus wasting the campus's energy consumption. An intelligent management system can be implemented into smart campuses to reduce the overall electrical bills to adapt to the hybrid education model. The research was then conducted on existing prior work around intelligent buildings and energy optimization. It was found that many of the energy optimization models utilized an IoT application highly specific to the designed IoT system only. This inspired developing an open source generalized IoT application to provide two-way communication between the energy optimization models and IoT devices. This would allow researchers to test their intelligent energy optimization models without building a support application from scratch. During the development phase, Firebase and open-source Chart JS were used to create an interactive web application with features including a dashboard, insightful data analysis, and remote-control features to be applied in a smart campus. A successful connection was established with a Raspberry Pi-based IoT system, where data could be stored and retrieved from the database into the web application. The second phase is going to be implementation of AI model which is currently in progress and being trained to fulfill the required criteria. � 2022 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1109/IICAIET55139.2022.9936774
dc.identifier.scopus2-s2.0-85142248169
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85142248169&doi=10.1109%2fIICAIET55139.2022.9936774&partnerID=40&md5=2d9c2bcd150202eb57636c51e122b3c0
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/27070
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitle4th IEEE International Conference on Artificial Intelligence in Engineering and Technology, IICAIET 2022
dc.titleA Prototype Model of Monitoring Energy Consumption and Optimizing Distribution of Smart Buildingsen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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