Integrating Artificial Intelligence and the Internet of Things in Cultural Heritage Preservation: A Systematic Review of Risk Management and Environmental Monitoring Strategies

Abstract

Heritage buildings are increasingly vulnerable to environmental challenges like air pollution and climate change. Traditional preservation methods primarily rely on periodic inspections and manual interventions and struggle to address these evolving and dynamic threats. This systematic review analyzes how integrating Artificial Intelligence (AI) and Internet of Things (IoT) technologies can transform cultural heritage preservation. Using the PRISMA guidelines, 92 articles from SCOPUS were reviewed, highlighting key risk management and environmental monitoring methodologies. The study found that while IoT enables real-time air quality and structural health monitoring, AI enhances data analysis, providing predictive insights. The combination of IoT and AI facilitates proactive risk management, ensuring more resilient conservation strategies. Despite the growing use of these technologies, adoption remains uneven, particularly in regions most impacted by climate change. The study identifies significant research gaps and proposes an innovative framework that leverages Heritage Building Information Modeling (H-BIM) and Digital Twin (DT) for continuous monitoring and predictive maintenance through a multi-step process, beginning with the digitalization of heritage assets using H-BIM, followed by the creation of real-time digital replicas via DT. By integrating advanced technologies, the framework offers a more adaptive and sustainable approach to preserving cultural heritage, addressing both immediate threats and long-term vulnerabilities. This research underscores the need for a global, technology-driven response to safeguard heritage buildings for future generations.