Hai Tao Long

Mr. Hai Tao Long


Research Focus & Metrics

Academic Career Length

2Years (2025-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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24 October 2025 in Applied Sciences
Verified
Journal Article
Open access
PDF file
Philip Y L WongPhilip Y L Wong
Philip Y L Wong
KLKinson Lo
Kinson Lo
HLHai Tao Long
Hai Tao Long
Joseph LaiJoseph Lai
Joseph Lai
Digital transformation powered by Building Information Modeling (BIM) and Artificial Intelligence (AI) is reshaping renovation practices by addressing persistent challenges such as fragmented records, scheduling disruptions, regulatory delays, and inefficiencies in stakeholder coordination. This study explores the integration of these technologies through a case study of a Catholic church renovation (2022–2023) in Hong Kong, supplemented by insights from 10 comparable projects. The research proposes a practical framework for incorporating digital tools into renovation workflows that focuses on diagnosing challenges, defining objectives, selecting appropriate BIM/AI tools, designing an integrated system, and combining implementation, monitoring, and scaling into a cohesive iterative process. Key technologies include centralized BIM repositories, machine learning-based predictive analytics, Internet of Things (IoT) sensors, and robotic process automation (RPA). The findings show that these tools significantly improve data organization, proactive planning, regulatory compliance, stakeholder collaboration, and overall project efficiency. While qualitative in nature, this study offers globally relevant insights and actionable strategies for advancing digital transformation in renovation practices, with a focus on scalability, continuous improvement, and alignment with regulatory frameworks.