Occupancy estimation using environmental parameters
Energy consumption in Singapore has been rising in recent years. A huge contributor to this trend comes from heating, ventilation, and air conditioning (HVAC) systems in modern buildings, where energy may be wasted to provide cooling unnecessarily. As a result, energy-saving technologies are being s...
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| Outros Autores: | |
| Formato: | Final Year Project (FYP) |
| Idioma: | English |
| Publicado em: |
Nanyang Technological University
2021
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| Acesso em linha: | https://hdl.handle.net/10356/149865 |
| _version_ | 1826114783919734784 |
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| author | Law, Jun Hong |
| author2 | Soh Yeng Chai |
| author_facet | Soh Yeng Chai Law, Jun Hong |
| author_sort | Law, Jun Hong |
| collection | NTU |
| description | Energy consumption in Singapore has been rising in recent years. A huge contributor to this trend comes from heating, ventilation, and air conditioning (HVAC) systems in modern buildings, where energy may be wasted to provide cooling unnecessarily. As a result, energy-saving technologies are being studied and introduced in Singapore, to slow down the growth of electricity consumption and reduce electricity wastage. One such study field involves the prediction of occupancy levels, by incorporating data retrieved from environment sensors, with machine learning techniques. This paper thus covers the analysis of several measured environmental parameters, combined with some machine learning models, to effectively produce occupancy statuses of an indoor environment. Moreover, the machine learning models utilised will be evaluated and discussed, to identify the suitable models to apply for the conservation of energy consumption, for relevant electrical systems and appliances in buildings. |
| first_indexed | 2024-10-01T03:44:49Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/149865 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:44:49Z |
| publishDate | 2021 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1498652023-07-07T17:59:53Z Occupancy estimation using environmental parameters Law, Jun Hong Soh Yeng Chai School of Electrical and Electronic Engineering EYCSOH@ntu.edu.sg Engineering::Electrical and electronic engineering Energy consumption in Singapore has been rising in recent years. A huge contributor to this trend comes from heating, ventilation, and air conditioning (HVAC) systems in modern buildings, where energy may be wasted to provide cooling unnecessarily. As a result, energy-saving technologies are being studied and introduced in Singapore, to slow down the growth of electricity consumption and reduce electricity wastage. One such study field involves the prediction of occupancy levels, by incorporating data retrieved from environment sensors, with machine learning techniques. This paper thus covers the analysis of several measured environmental parameters, combined with some machine learning models, to effectively produce occupancy statuses of an indoor environment. Moreover, the machine learning models utilised will be evaluated and discussed, to identify the suitable models to apply for the conservation of energy consumption, for relevant electrical systems and appliances in buildings. Bachelor of Engineering (Electrical and Electronic Engineering) 2021-06-09T08:01:29Z 2021-06-09T08:01:29Z 2021 Final Year Project (FYP) Law, J. H. (2021). Occupancy estimation using environmental parameters. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/149865 https://hdl.handle.net/10356/149865 en A1123-201 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Electrical and electronic engineering Law, Jun Hong Occupancy estimation using environmental parameters |
| title | Occupancy estimation using environmental parameters |
| title_full | Occupancy estimation using environmental parameters |
| title_fullStr | Occupancy estimation using environmental parameters |
| title_full_unstemmed | Occupancy estimation using environmental parameters |
| title_short | Occupancy estimation using environmental parameters |
| title_sort | occupancy estimation using environmental parameters |
| topic | Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/149865 |
| work_keys_str_mv | AT lawjunhong occupancyestimationusingenvironmentalparameters |