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In an era defined by rapid technological advances in computing , built environment industries like construction and civil engineering are in a sweet spot to embrace innovation . One of the most promising technologies being adopted today is Computer Vision , a subfield of Artificial Intelligence ( AI ), which enables computers to interpret visual data . Paired with Geographic Information Systems ( GIS ), Computer Vision offers new solutions for managing and auditing asset inventories . This article will explore how Computer Vision AI can be utilized to streamline asset inventory audits , thus ushering the industry into a new age of efficiency and accuracy .
The problem : asset inventory auditing
Asset inventory auditing is a critical - but often cumbersome - process for construction and civil engineering projects . It involves the identification , classification , and documentation of various assets , such as materials , equipment , and structures . Traditional auditing methods , which involve manual , on-site inspections , can be costly and time-consuming . Moreover , human errors , whether in data collection or interpretation , can lead to inaccurate inventory audits , potentially causing significant downstream problems .
The solution : computer vision AI and GIS integration
Computer Vision AI technology can automate and optimise the inventory auditing process by analyzing images and video data from various sources ( i . e ., vehicle or drone-mounted cameras ), identifying and classifying assets , and noting their condition and location . When integrated with GIS - which is designed to capture , store , and manage geographical data - the technology becomes a powerhouse tool for asset inventory management . Here ’ s how :
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