Please use this identifier to cite or link to this item: 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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