In the domain of building management, the absence of timely damage assessment and proactive preventive intervention plans, compounded by inherent aging processes, accelerates the degradation of structures. Current systems for condition assessment and decision support exhibit deficiencies in capturing and retrieving detailed information, resulting in ineffective decisions and significant financial losses. This comprehensive literature review explores condition assessment and maintenance of existing buildings through the integration of geographic information system (GIS) and building information modelling (BIM). GIS and BIM are essential tools for digitising data on the functional, spatial, and physical aspects of buildings. The review emphasises the synergistic potential of GIS and BIM, addressing challenges in interoperability, data modelling, and visualisation. Key findings underscore the importance of improved architectural frameworks to facilitate seamless data integration across diverse GIS, BIM, and facility management tools. The paper also highlights future research directions, including the integration of deep learning and machine learning for predictive maintenance of buildings integrated to their surroundings. In addition, it emphasises the role of Internet of Things technologies, automation, and advancements in 3D GIS and virtual reality for enhancing data collection, visualisation, and decision-making aspects in building condition assessment and maintenance.
Nair et al. (Thu,) studied this question.