An overview of predictive maintenance in relation to 2D and 3D Geographical Information System (GIS) for built environment

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. Predictiv...

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Main Authors: Hairuddin, Farah Ilyana, Azri, Suhaibah
Format: Conference or Workshop Item
Language:English
Published: 2023
Subjects:
Online Access:http://eprints.utm.my/107727/1/FarahIlyana2023_AnoverviewofPredictiveMaintenanceinRelation.pdf
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author Hairuddin, Farah Ilyana
Azri, Suhaibah
author_facet Hairuddin, Farah Ilyana
Azri, Suhaibah
author_sort Hairuddin, Farah Ilyana
collection ePrints
description 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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spelling utm.eprints-1077272024-09-29T06:26:21Z http://eprints.utm.my/107727/ An overview of predictive maintenance in relation to 2D and 3D Geographical Information System (GIS) for built environment Hairuddin, Farah Ilyana Azri, Suhaibah G70.212-70.215 Geographic information system 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. 2023 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utm.my/107727/1/FarahIlyana2023_AnoverviewofPredictiveMaintenanceinRelation.pdf Hairuddin, Farah Ilyana and Azri, Suhaibah (2023) An overview of predictive maintenance in relation to 2D and 3D Geographical Information System (GIS) for built environment. In: International Graduate Conference of Built Environment and Surveying 2023, GBES 2023, 17 September 2023 - 18 September 2023, Hybrid, Johor Bahru, Johor, Malaysia. http://dx.doi.org/10.1088/1755-1315/1274/1/012003
spellingShingle G70.212-70.215 Geographic information system
Hairuddin, Farah Ilyana
Azri, Suhaibah
An overview of predictive maintenance in relation to 2D and 3D Geographical Information System (GIS) for built environment
title An overview of predictive maintenance in relation to 2D and 3D Geographical Information System (GIS) for built environment
title_full An overview of predictive maintenance in relation to 2D and 3D Geographical Information System (GIS) for built environment
title_fullStr An overview of predictive maintenance in relation to 2D and 3D Geographical Information System (GIS) for built environment
title_full_unstemmed An overview of predictive maintenance in relation to 2D and 3D Geographical Information System (GIS) for built environment
title_short An overview of predictive maintenance in relation to 2D and 3D Geographical Information System (GIS) for built environment
title_sort overview of predictive maintenance in relation to 2d and 3d geographical information system gis for built environment
topic G70.212-70.215 Geographic information system
url http://eprints.utm.my/107727/1/FarahIlyana2023_AnoverviewofPredictiveMaintenanceinRelation.pdf
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