Building automation systems for energy and comfort management in green buildings: A critical review and future directions

Qiang, Guofeng; Shu, Tang; Hao, Jian Li; Sarno, Luigi Di; Wu, Guanglei; Ren, Shaoxing

doi:10.1016/j.rser.2023.113301

Cited by 23 publications

(10 citation statements)

References 135 publications

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“…Liao et al [12] stated that effective cost management practices are crucial for achieving project objectives, meeting client expectations, and optimizing resource allocation. Studies by Qiang et al [13] emphasized the significance of cost management in enhancing project efficiency and mitigating financial risks. Various cost estimation techniques are employed in civil engineering projects to forecast project expenses accurately.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In civil engineering, AI offers the potential to transform cost optimization practices by delivering data-driven insights, predictive capabilities, and the automation of routine tasks [9,10]. AI algorithms can process large volumes of project data, detect patterns, and produce accurate cost estimates, allowing project managers to make more informed decisions and reduce financial risks [13].…”

Section: The Role Of Artificial Intelligence In Cost Optimizationmentioning

confidence: 99%

“…These techniques examine project variables and external factors, such as market conditions, regulatory changes, and weather patterns, to forecast potential cost overruns and schedule delays [21]. By identifying risks early in the project lifecycle, predictive analytics helps project managers develop risk mitigation strategies, allocate contingency funds, and improve project planning and execution [13].…”

Section: The Role Of Artificial Intelligence In Cost Optimizationmentioning

confidence: 99%

“…Robotic Process Automation (RPA) tools further enhance efficiency by automating repetitive tasks like invoice processing and payment tracking, reducing manual errors [17,18]. The integration of AI with Building Information Modeling (BIM) presents new avenues for cost optimization in civil engineering projects [13,14]. BIM models contain detailed information about project components, materials, and quantities, which AI algorithms can use for cost estimations, quantity takeoff, and value engineering [19].…”

Section: The Role Of Artificial Intelligence In Cost Optimizationmentioning

confidence: 99%

“…The next method, ISM, is used to analyze complex systems and identify the hierarchical relationships among elements [13]. In the context of MCDM, ISM enables decision-makers to visualize and understand the interdependencies among criteria or factors influencing a decision problem [14,15].…”

Section: Previous Studies Involving the Fuzzy Integrated Delphi-ism-m...mentioning

confidence: 99%

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Fuzzy Integrated Delphi-ISM-MICMAC Hybrid Multi-Criteria Approach to Optimize the Artificial Intelligence (AI) Factors Influencing Cost Management in Civil Engineering

Hu,

Jiang,

Goswami

et al. 2024

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This research paper presents a comprehensive study on optimizing the critical artificial intelligence (AI) factors influencing cost management in civil engineering projects using a multi-criteria decision-making (MCDM) approach. The problem addressed revolves around the need to effectively manage costs in civil engineering endeavors amidst the growing complexity of projects and the increasing integration of AI technologies. The methodology employed involves the utilization of three MCDM tools, specifically Delphi, interpretive structural modeling (ISM), and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC). A total of 17 AI factors, categorized into eight broad groups, were identified and analyzed. Through the application of different MCDM techniques, the relative importance and interrelationships among these factors were determined. The key findings reveal the critical role of certain AI factors, such as risk mitigation and cost components, in optimizing the cost management processes. Moreover, the hierarchical structure generated through ISM and the influential factors identified via MICMAC provide insights for prioritizing strategic interventions. The implications of this study extend to informing decision-makers in the civil engineering domain about effective strategies for leveraging AI in their cost management practices. By adopting a systematic MCDM approach, stakeholders can enhance project outcomes while optimizing resource allocation and mitigating financial risks.

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Section: Literature Reviewmentioning

confidence: 99%