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dc.contributor.author | Zeeshan Wakeel, 01-133162-175 | |
dc.contributor.author | Zahid Amanullah, 01-133162-050 | |
dc.contributor.author | Musammar Hassan Imrani, 01-133162-086 | |
dc.date.accessioned | 2022-04-13T06:20:37Z | |
dc.date.available | 2022-04-13T06:20:37Z | |
dc.date.issued | 2020 | |
dc.identifier.uri | http://hdl.handle.net/123456789/12604 | |
dc.description | Supervised by Engr M. Hassan Danish Khan | en_US |
dc.description.abstract | Energy efficiency issues have become a significant challenge for the development of the world. The system will control and monitor the electrical based equipment’s and reduce the power consumption in building by controlling devices automatically when devices are need to be on or off .The system will alarms for the bad conditions like fire and high energy usage and plus point is you can control your devices by sitting anywhere in the world and we make the monitoring easy. Moreover, it uses the machine learning and energy profiling system, this system will help to predict us the future values and billing of the building or system. Previously researches on building managements are made but they don’t use any type of machine learning, by seeing in the brief this project will train the machine on daily basis and can be perfect for office or specific building. This project will reduce the power consumption by 30% or even more efficient because it will only use the power when the appliances will need it. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Bahria University Engineering School | en_US |
dc.relation.ispartofseries | BEE;P-1635 | |
dc.subject | Electrical Engineering | en_US |
dc.title | IoE Based Building Energy Profiling System | en_US |
dc.type | Project Reports | en_US |