IOT smart single wall outlet
Wall outlets are devices that supply electrical power to appliances and are widely used in the residential, commercial, and industrial sectors. Due to economic growth and population expansion, the demand for electricity in all these sectors surges to a new high every year. Subsequently, the generati...
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| Format: | Final Year Project / Dissertation / Thesis |
| Published: |
2022
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| Online Access: | http://eprints.utar.edu.my/4958/ http://eprints.utar.edu.my/4958/1/3E_1702255_FYP_report_%2D_YEE_REN_PHANG.pdf |
| _version_ | 1848886287634792448 |
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| author | Phang, Yee Ren |
| author_facet | Phang, Yee Ren |
| author_sort | Phang, Yee Ren |
| building | UTAR Institutional Repository |
| collection | Online Access |
| description | Wall outlets are devices that supply electrical power to appliances and are widely used in the residential, commercial, and industrial sectors. Due to economic growth and population expansion, the demand for electricity in all these sectors surges to a new high every year. Subsequently, the generation of electricity is required to expand at a tremendous rate. To control the demand, Tenaga Nasional Berhad (TNB) introduced the Enhanced Time of Use (ETOU) scheme to offer different tariff rates for commercial and industrial end-users at different times of the day. Fixed electricity tariffs no longer represent actual electricity prices. This report presents an Internet of Things (IoT)-based smart wall outlet system that adapts to the ETOU scheme. With the aid of a central console, this system can link a network of wall outlets together and manage them via the Node-Red or Android application. The network enables this system to measure the real-time electricity bill and current usage of each room in a house, office, or factory. All this information will be visualised in a floorplan layout. Also, the power consumption of appliances connected to a single wall outlet can be predicted based on the user’s usage behaviour. The developed energy consumption predictive model can achieve an accuracy of up to 90% in predicting the wall outlet power consumption. |
| first_indexed | 2025-11-15T19:36:06Z |
| format | Final Year Project / Dissertation / Thesis |
| id | utar-4958 |
| institution | Universiti Tunku Abdul Rahman |
| institution_category | Local University |
| last_indexed | 2025-11-15T19:36:06Z |
| publishDate | 2022 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | utar-49582022-12-23T13:08:20Z IOT smart single wall outlet Phang, Yee Ren TK Electrical engineering. Electronics Nuclear engineering Wall outlets are devices that supply electrical power to appliances and are widely used in the residential, commercial, and industrial sectors. Due to economic growth and population expansion, the demand for electricity in all these sectors surges to a new high every year. Subsequently, the generation of electricity is required to expand at a tremendous rate. To control the demand, Tenaga Nasional Berhad (TNB) introduced the Enhanced Time of Use (ETOU) scheme to offer different tariff rates for commercial and industrial end-users at different times of the day. Fixed electricity tariffs no longer represent actual electricity prices. This report presents an Internet of Things (IoT)-based smart wall outlet system that adapts to the ETOU scheme. With the aid of a central console, this system can link a network of wall outlets together and manage them via the Node-Red or Android application. The network enables this system to measure the real-time electricity bill and current usage of each room in a house, office, or factory. All this information will be visualised in a floorplan layout. Also, the power consumption of appliances connected to a single wall outlet can be predicted based on the user’s usage behaviour. The developed energy consumption predictive model can achieve an accuracy of up to 90% in predicting the wall outlet power consumption. 2022 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/4958/1/3E_1702255_FYP_report_%2D_YEE_REN_PHANG.pdf Phang, Yee Ren (2022) IOT smart single wall outlet. Final Year Project, UTAR. http://eprints.utar.edu.my/4958/ |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Phang, Yee Ren IOT smart single wall outlet |
| title | IOT smart single wall outlet |
| title_full | IOT smart single wall outlet |
| title_fullStr | IOT smart single wall outlet |
| title_full_unstemmed | IOT smart single wall outlet |
| title_short | IOT smart single wall outlet |
| title_sort | iot smart single wall outlet |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://eprints.utar.edu.my/4958/ http://eprints.utar.edu.my/4958/1/3E_1702255_FYP_report_%2D_YEE_REN_PHANG.pdf |