Scalable Smartification of Commercial Buildings HVAC Systems Using the Internet of Things and Machine Learning
Most of the commercial buildings in Malaysia are still equipped with the legacy control for their Heat ventilation and air conditioning system (HVAC), which several studies claimed to have contributed to energy consumption in buildings. A significant amount of this energy is consumed by the building...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Other Authors: | |
| Format: | Conference Paper |
| Published: |
Springer Science and Business Media Deutschland GmbH
2023
|
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1833412711322484736 |
|---|---|
| author | Mahdi M.N. Bakare T.A. Ahmad A.R. Buhari A.M. Mohamed K.S. |
| author2 | 56727803900 |
| author_facet | 56727803900 Mahdi M.N. Bakare T.A. Ahmad A.R. Buhari A.M. Mohamed K.S. |
| author_sort | Mahdi M.N. |
| building | UNITEN Library |
| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Most of the commercial buildings in Malaysia are still equipped with the legacy control for their Heat ventilation and air conditioning system (HVAC), which several studies claimed to have contributed to energy consumption in buildings. A significant amount of this energy is consumed by the building Heat Ventilation and Air Conditioning units. This is mostly due to the lack of smart and remote functionalities in the legacy HVAC systems to control the chillers and the Air handling units. This massive energy consumption is an antithesis to what governments all over the world are aiming for. However, scalability and deployment of low-cost resource-limited hardware embedded with control algorithms used to save energy in commercial building�s Heat Ventilation and Air Conditioning (HVAC) units is a difficult engineering task. But the unprecedented advancement and perverseness of information technology services over the past two decades has led to an ever more connected world. This project will leverage the concept of the Internet of Energy to make the systems smarter and more decentralized for flexible energy usage. Modern-day devices are increasingly linked to the internet, creating what is now referred to as the internet of things (IoT). The IoT paradigm has provided technologists with the ability to remotely control devices, and with the recent progress in Machine learning (ML) and Artificial Intelligence (AI), devices are trained to make smart decisions that can independently influence human to machine interactions. � 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. |
| format | Conference Paper |
| id | my.uniten.dspace-27283 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2023 |
| publisher | Springer Science and Business Media Deutschland GmbH |
| record_format | dspace |
| spelling | my.uniten.dspace-272832023-05-29T17:42:06Z Scalable Smartification of Commercial Buildings HVAC Systems Using the Internet of Things and Machine Learning Mahdi M.N. Bakare T.A. Ahmad A.R. Buhari A.M. Mohamed K.S. 56727803900 57232790600 35589598800 56525158000 57216259938 Most of the commercial buildings in Malaysia are still equipped with the legacy control for their Heat ventilation and air conditioning system (HVAC), which several studies claimed to have contributed to energy consumption in buildings. A significant amount of this energy is consumed by the building Heat Ventilation and Air Conditioning units. This is mostly due to the lack of smart and remote functionalities in the legacy HVAC systems to control the chillers and the Air handling units. This massive energy consumption is an antithesis to what governments all over the world are aiming for. However, scalability and deployment of low-cost resource-limited hardware embedded with control algorithms used to save energy in commercial building�s Heat Ventilation and Air Conditioning (HVAC) units is a difficult engineering task. But the unprecedented advancement and perverseness of information technology services over the past two decades has led to an ever more connected world. This project will leverage the concept of the Internet of Energy to make the systems smarter and more decentralized for flexible energy usage. Modern-day devices are increasingly linked to the internet, creating what is now referred to as the internet of things (IoT). The IoT paradigm has provided technologists with the ability to remotely control devices, and with the recent progress in Machine learning (ML) and Artificial Intelligence (AI), devices are trained to make smart decisions that can independently influence human to machine interactions. � 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. Final 2023-05-29T09:42:06Z 2023-05-29T09:42:06Z 2022 Conference Paper 10.1007/978-3-030-85990-9_15 2-s2.0-85121821578 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121821578&doi=10.1007%2f978-3-030-85990-9_15&partnerID=40&md5=089ab749d309808fe5a7e5dc89b402c8 https://irepository.uniten.edu.my/handle/123456789/27283 322 165 174 Springer Science and Business Media Deutschland GmbH Scopus |
| spellingShingle | Mahdi M.N. Bakare T.A. Ahmad A.R. Buhari A.M. Mohamed K.S. Scalable Smartification of Commercial Buildings HVAC Systems Using the Internet of Things and Machine Learning |
| title | Scalable Smartification of Commercial Buildings HVAC Systems Using the Internet of Things and Machine Learning |
| title_full | Scalable Smartification of Commercial Buildings HVAC Systems Using the Internet of Things and Machine Learning |
| title_fullStr | Scalable Smartification of Commercial Buildings HVAC Systems Using the Internet of Things and Machine Learning |
| title_full_unstemmed | Scalable Smartification of Commercial Buildings HVAC Systems Using the Internet of Things and Machine Learning |
| title_short | Scalable Smartification of Commercial Buildings HVAC Systems Using the Internet of Things and Machine Learning |
| title_sort | scalable smartification of commercial buildings hvac systems using the internet of things and machine learning |
| url_provider | http://dspace.uniten.edu.my/ |