Abstract
Well-preserved buildings can be a great asset to the country, contributing to its economic growth. The lifespan of a building and its assets can be extended through proper maintenance. This will improve the longevity of its function, sustain its performance, and optimize maintenance costs. Predictive maintenance is a proactive approach to maintenance, as it is conducted based on the current operational state of equipment rather than average life statistics. It is generally implemented in building maintenance, machinery, and many other industries. While predictive maintenance has grown in application with artificial intelligence, digital twins, and machine learning, its application with geographical information systems (GIS) and 3D GIS have limitedly discussed. Geospatial predictive maintenance can be realized by integrating the asset's location with its maintenance semantic and temporal information. By incorporating geospatial thinking into the predictive framework, it can help optimize decision-making processes such as allocating maintenance costs based on calculating affected areas, visualizing the location of assets, understanding their interactions with meteorological events and virtual situations. Therefore, this paper will discuss a review of predictive maintenance in relation to GIS and 3D GIS.
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More From: IOP Conference Series: Earth and Environmental Science
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