A Carbon Footprint Management Framework for Prefabricated Buildings Based on Knowledge Graph

Longhui Liao, Yuhang Wen (), Wenting Mo and Cuiping Gan
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Longhui Liao: Sino-Australia Joint Research Center in BIM and Smart Construction, Shenzhen University
Yuhang Wen: Sino-Australia Joint Research Center in BIM and Smart Construction, Shenzhen University
Wenting Mo: Sino-Australia Joint Research Center in BIM and Smart Construction, Shenzhen University
Cuiping Gan: Sino-Australia Joint Research Center in BIM and Smart Construction, Shenzhen University

Chapter Chapter 106 in Proceedings of the 28th International Symposium on Advancement of Construction Management and Real Estate, 2024, pp 1551-1569 from Springer

Abstract: Abstract The study presents an integrated framework for managing the carbon footprint of prefabricated buildings throughout their life cycle. The framework integrates ontology modeling, knowledge graph storage, and life cycle assessment (LCA) to analyze carbon footprint data. Sensor technology and natural language processing techniques are used for data collection and processing to build a knowledge graph for managing the carbon footprint of prefabricated buildings throughout their life cycle. The framework enables carbon footprint measurement, carbon source tracking, monitoring and feedback, and provides the basis for carbon reduction decisions. The study outlines the challenges in carbon footprint knowledge data management, including inconsistent definitions and methods, limited knowledge availability, and the complexity of carbon footprint data collection and processing. It also outlines the process of building carbon footprint ontology models, data processing, knowledge graph construction and storage, and carbon footprint measurement and carbon source tracking. The goal of the framework is to promote sustainable building practices and facilitate informed decision-making processes.

Keywords: Carbon footprint; Prefabricated buildings; Knowledge graph; Monitoring; Measurement (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/978-981-97-1949-5_107

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