Extended Conference Paper
Open Access
GIS based solutions for management of public building and infrastructure assets: a review of state of the art and research trend analysis
  • DOI
    10.55092/sc20250008
  • Copyright
    Copyright2025 by the authors. Published by ELSP.
Abstract

Building asset management is a complex endeavor that involves development, operation, maintenance and disposal of large-scale costly assets that serve one or more significant functions. Recent and continuing developments in Geographical Information Systems (GIS) offer solutions to the significant challenges of integrating and visualizing asset management data, choosing development proposals, cost assessment, risk assessment and maintenance strategies. Furthermore, GIS data is a common element among many types of projects, buildings and infrastructure assets. GIS technologies can therefore have a significant and broad impact. Navigating GIS developments can be difficult and unclear. To this end, this study performs a literature review on state-of-the-art and emerging GIS technologies as they apply to public asset management. The aim is to provide public authorities with a means to understand the potential and the challenges of these GIS technologies in order to support more informed decision making. The main opportunities that these technologies provide to AM are examined. These include data integration, optimization of resource use, risk assessment and improved decision making from reactive to proactive. In addition, a new Word2Vec K-means based keyword gap analysis tool is proposed to aid in the visualization of keywords in the literature corpus by sorting the keywords into meaningful subject focused categories. This study will help make adoption choices of GIS technologies more informed and coherent, which will allow the reduction benefits in costs, energy and environmental impacts to be more easily leveraged.

Keywords

geography information systems; public assets; asset management; building information modeling; literature review; digitization; natural language processing (NLP); Word2Vec; K-means

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