Title:	INFORMATION MANAGEMENT IN CARBON EMISSIONS QUANTIFICATION
Author(s):	Lai Ke En, Nafisah Abdul Rahiman and Kherun Nita Ali
ISBN:	978-989-8704-48-1
Editors:	Miguel Baptista Nunes, Pedro Isaías and Philip Powell
Year:	2023
Edition:	Single
Keywords:	Carbon Emissions Quantification, Internet of Things (IoT), Building Information Modelling (BIM), Blockchain
Type:	Full Paper
First Page:	147
Last Page:	154
Language:	English
Cover:
Full Contents:	click to dowload
Paper Abstract:	Global warming is a critical problem that resulted from excessive greenhouse gas emissions and 97% of the greenhouse gases are carbon emissions. The current carbon quantification methods involved massive information and deemed to have low productivity and the accuracy of the quantified carbon emissions is debatable. Thus, the effectiveness of mitigation efforts to reduce carbon emissions is lowered due to the simplification and assumptions during the quantification process. This paper aims to review the potential of Internet of Things (IoT), Building Information Modelling (BIM), and blockchain to quantify the lifecycle carbon emissions. Literature review using synthesis method is adopted to identify the state-of-art for the application of IoT, BIM, and blockchain for carbon emissions quantification. The review concluded that IoT, BIM, and blockchain have the potential to reduce human errors and speed up the real-time carbon emissions quantification. IoT is capable to extract real-time data from the physical environment, BIM can reduce document errors, enhance the collaboration between the stakeholder, and improve the workflow across the supply chain, and Blockchain is well-known for its tamper-proof characteristic which increases the reliability and security of the data stored. These technologies are complementary to each other and able to enhance the reliability and accuracy of carbon emissions quantification. In short, the integration of the technologies can increase the credibility in quantifying the carbon emitted and facilitate the selection of the most appropriate retrofit scenarios for emissions reduction.
	Go Back