A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Methodology for a Large Scale Building Internet of Things Retrofit
With the presence of sensing technologies today, buildings can be built fitted with various sensors and systems to encourage energy efficiency and sustainability. However, legacy buildings are not originally built to support internet-of-things (IoT) technology or to promote sustainability. Thus, legacy buildings that are still being actively used today require retrofitting works to improve the efficiency of the buildings. Retrofitting the legacy buildings with IoT capabilities can be very challenging due to the active use of the buildings, dynamic building functions, undocumented indoor modifications and vulnerable physical structure, among others. Therefore, a comprehensive methodology is needed for systematic deployment of the sensors and associated systems into the building, covering a complete cycle from identifying the needs and requirements of the system until its full operation. This study aims to devise and advocate a methodology for systematic retrofitting of sensors in legacy buildings and hence enabling the collection of energy consumption data. To do that, a 20-year old six-storey academic building in one of the institutes of higher learning in Malaysia is used as a case study. This paper explains the first part of the progressive development of the proposed methodology, which is on the protocol for the placement of the sensors and devices. The outcome of this study details the operational planning that can be referred to for future buildings retrofitting work on a similar scale. Issues and challenges faced in the process of establishing the protocol are also discussed.
Methodology for a Large Scale Building Internet of Things Retrofit
With the presence of sensing technologies today, buildings can be built fitted with various sensors and systems to encourage energy efficiency and sustainability. However, legacy buildings are not originally built to support internet-of-things (IoT) technology or to promote sustainability. Thus, legacy buildings that are still being actively used today require retrofitting works to improve the efficiency of the buildings. Retrofitting the legacy buildings with IoT capabilities can be very challenging due to the active use of the buildings, dynamic building functions, undocumented indoor modifications and vulnerable physical structure, among others. Therefore, a comprehensive methodology is needed for systematic deployment of the sensors and associated systems into the building, covering a complete cycle from identifying the needs and requirements of the system until its full operation. This study aims to devise and advocate a methodology for systematic retrofitting of sensors in legacy buildings and hence enabling the collection of energy consumption data. To do that, a 20-year old six-storey academic building in one of the institutes of higher learning in Malaysia is used as a case study. This paper explains the first part of the progressive development of the proposed methodology, which is on the protocol for the placement of the sensors and devices. The outcome of this study details the operational planning that can be referred to for future buildings retrofitting work on a similar scale. Issues and challenges faced in the process of establishing the protocol are also discussed.
Methodology for a Large Scale Building Internet of Things Retrofit
Dzulkifly, Sumayyah (author) / Aris, Hazleen (author) / Jørgensen, Bo Nørregaard (author) / Santos, Athila Quaresma (author)
2020-01-01
Dzulkifly , S , Aris , H , Jørgensen , B N & Santos , A Q 2020 , Methodology for a Large Scale Building Internet of Things Retrofit . in 2020 8th International Conference on Information Technology and Multimedia (ICIMU) . IEEE , pp. 62-67 , 2020 8th International Conference on Information Technology and Multimedia (ICIMU) , Selangor , Malaysia , 24/08/2020 . https://doi.org/10.1109/ICIMU49871.2020.9243304
Article (Journal)
Electronic Resource
English
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