Asgari, Zeynab and Rahimian, Farzad Pour (2017) Advanced Virtual Reality Applications and Intelligent Agents for Construction Process Optimisation and Defect Prevention. Procedia Engineering, 196. pp. 1130-1137. ISSN 1877-7058
|
Text (Full text)
Asgari, Rahimian - Advanced virtual reality applications and intelligent agents for construction process optimisation and defect prevention OA.pdf - Published Version Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0. Download (229kB) | Preview |
Abstract
Defects and errors in new or recently completed construction work continually pervade the industry. Whilst inspection and monitoring processes are established vehicles for their 'control', the procedures involved are often process driven, time consuming, and resource intensive. Paradoxically therefore, they can impinge upon the broader aspects of project time, cost and quality outcomes. Acknowledging this means appreciating concatenation effects such as the potential for litigation, impact on other processes and influence on stakeholders' perceptions—that in turn, can impede progress and stifle opportunities for process optimisation or innovation. That is, opportunities relating to for example, logistics, carbon reduction, health and safety, efficiency, asset underutilisation and efficient labour distribution. This study evaluates these kinds of challenge from a time, cost and quality perspective, with a focus on identifying opportunities for process innovation and optimisation. It reviews—within the construction domain—state of the art technologies that support optimal use of artificial intelligence, cybernetics and complex adaptive systems. From this, conceptual framework is proposed for development of real-time intelligent observational platform supported by advanced intelligent agents, presented for discussion. This platform actively, autonomously and seamlessly manages intelligent agents (Virtual Reality cameras, Radio-Frequency Identification RFID scanners, remote sensors, etc.) in order to identify, report and document 'high risk' defects. Findings underpin a new ontological model that supports ongoing development of a dynamic, self-organised sensor (agent) network, for capturing and reporting real-time construction site data. The model is a 'stepping stone' for advancement of independent intelligent agents, embracing sensory and computational support, able to perform complicated (previously manual) tasks that provide optimal, dynamic, and autonomous management functions.
Item Type: | Article |
---|---|
Uncontrolled Keywords: | Intelligent agent; Virtual Reality; Process Innovation; ICT; Sensors; Optimisation |
Subjects: | G600 Software Engineering G700 Artificial Intelligence |
Department: | Faculties > Engineering and Environment > Mechanical and Construction Engineering |
Depositing User: | Paul Burns |
Date Deposited: | 03 Sep 2018 17:29 |
Last Modified: | 01 Aug 2021 09:33 |
URI: | http://nrl.northumbria.ac.uk/id/eprint/35571 |
Downloads
Downloads per month over past year