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https://hdl.handle.net/10356/78431
Title: | Automating of air-conditioning mechanical ventilation (ACMV) operation using artificial intelligence | Authors: | Muhammad Ilyasa' Idris | Keywords: | DRNTU::Engineering::Mechanical engineering | Issue Date: | 2019 | Abstract: | In facilities management, energy consumption resulting from the use of Air-Conditioning Mechanical Ventilation (ACMV) Systems represents the highest cost in a building’s lifecycle. A portion of this cost can be attributed to the mismatch of ACMV system output settings to the room’s occupancy level as well as ‘characteristic behaviour’. The main goal of this project is to examine how an occupant interacts and behaves in a typical room and evaluating if such behaviour can be modelled and predicted. Data collected by sensors deployed in the room will be processed using analytic methods of Machine Learning (ML) to produce models that can forecast the temperature and humidity levels preferred by the occupant. | URI: | http://hdl.handle.net/10356/78431 | Schools: | School of Mechanical and Aerospace Engineering | Rights: | Nanyang Technological University | Fulltext Permission: | restricted | Fulltext Availability: | With Fulltext |
Appears in Collections: | MAE Student Reports (FYP/IA/PA/PI) |
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File | Description | Size | Format | |
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FYP Report.pdf Restricted Access | FYP Report | 1.39 MB | Adobe PDF | View/Open |
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