Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/77343
Title: Internet of things (IoTs) for facilities management
Authors: Chee, Isaac Haozhe
Keywords: DRNTU::Engineering::Mechanical engineering
Issue Date: 2019
Abstract: How can you get the best utility savings from the new opening of the electricity market in Singapore? The nation-wide privatisation of the electricity market, also known as OEM (Open Electricity Market) has been touted to bring about a wealth of benefits for the average homeowner. With more than 13 different electricity retailers now competing for market share, each are offering a variety of deals aimed at enticing you with attractive discounts. Faced with a myriad of choices, each seemingly as good as the next, will you be able to identify the plan that actually delivers its promise of producing the highest cost savings for your electricity usage pattern? With the rise of the digital age, many new developments to technology have provided possible solutions to optimize our energy consumption. A subject of interest of recent has been Artificial Intelligence (AI), which, put simply, allows computers to react and make decisions based on data too complex for a human. Utilising principles of Machine Learning (ML), a branch of AI, computers would be able to analyse energy usage and identify previously unknown trends in energy consumption data. Combining that with the increase in connectivity we see in all our devices; smartphones and smart refrigerators etc, also known as the Internet of Things (IoTs), and we can possibly create a self-regulating system for energy management. Equipped with new knowledge about your own personal habits of electricity usage, it would be more possible than ever for one to take full advantage of new electricity plans offered in the OEM and make a more informed decision.
URI: http://hdl.handle.net/10356/77343
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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