SemanticLCA: A new generation of life cycle assessment methods applied to buildings
SemanticLCA: A new generation of life cycle assessment methods applied to buildings
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DOI：
10.1109/ice/itmc-iamot55089.2022.10033206
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发表时间：
2022-06
期刊：
影响因子：
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通讯作者：
Abdulrahman Fnais;Ali Ghoroghi;Y. Rezgui;T. Beach;I. Petri
中科院分区：
文献类型：
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作者：
Abdulrahman Fnais;Ali Ghoroghi;Y. Rezgui;T. Beach;I. Petri
本文介绍了一个研究项目的概要，该项目旨在开发一个基于语义的框架，以提供近实时的环境足迹，并为建筑环境提供有效的运营和管理策略。本文认为，利用实时数据的价值的语义生命周期方法可以促进和提高动态生命周期评估的准确性。该方法涉及三个不同的元素，即语义、动态数据和学习系统。将探索几个用例，以验证所建议的方法在实际案例研究中的有效性。在审查了相关工作之后，将提出方法，以解释所涉及的各个组成部分以及不同层之间的信息交流。将简要介绍计划中的用例，然后是结论和未来的工作。
This paper presents the outlines of a research project that aims to develop a semantic-based framework for delivering near real-time environmental footprint and informing effective operation and management strategies for the built environment. This paper argues that a semantic life cycle approach leveraging the value of real-time data can facilitate and enhance the accuracy of dynamic life cycle assessments. The methodology involves three distinct elements, namely semantics, dynamic data, and learning systems. Several use cases will be explored to validate the proposed methodology on real case studies. Following a review of related work, the methodology will be presented to explain the various components involved and the information exchange between different layers. The planned use case will be briefly introduced, followed by conclusion and future work.