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https://ipweaq.intersearch.com.au/ipweaqjspui/handle/1/8375
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DC Field | Value | Language |
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dc.contributor.author | O'Dea, Jim | - |
dc.date.accessioned | 2024-11-19T19:21:56Z | - |
dc.date.available | 2024-11-19T19:21:56Z | - |
dc.date.copyright | 2024 | en_US |
dc.date.issued | 2024 | - |
dc.identifier.uri | https://ipweaq.intersearch.com.au/ipweaqjspui/handle/1/8375 | - |
dc.description.abstract | Artificial Intelligence (AI) is transforming public works engineering by enhancing efficiency, reducing costs, and providing tailored solutions, especially in regional and remote parts of Australia. This presentation explores the multifaceted advantages of AI integration in public works engineering, highlighting the significant cost savings and the future potential of AI to support engineers working in less accessible areas. AI technologies enable engineers to optimise resource allocation, predict maintenance needs, and improve project planning. These advancements reduce operational costs and mitigate risks associated with unexpected infrastructure failures. For example, AI-driven predictive maintenance can foresee equipment breakdowns, allowing for timely interventions that prevent costly repairs and downtime. AI's ability to analyse large datasets aids greatly in making better informed decisions and reduces the time that engineers need to spend tied to a desk. The adoption of in-house AI software, like Copilot, presents a tailored approach to meeting the unique needs of local government. Copilot's customisable features allow engineers to fine-tune AI outputs to match specific project requirements, This customisation is particularly beneficial for regional and remote engineering projects, where standard AI solutions may not fully address local challenges. By leveraging in-house AI tools, engineers can develop bespoke solutions that considers local historical data, environmental conditions, logistical constraints, and community needs. The future of AI in public works engineering promises even greater advancements. Enhanced machine learning algorithms, improved data collection methods, and more intuitive AI interfaces will further empower engineers to deliver high-quality public infrastructure projects within a cost-effective resourcing model. The ongoing development of AI technologies will provide robust support to engineers in regional and remote parts of Australia, ensuring that these areas benefit from the same technological advancements as urban centres. | en_US |
dc.publisher | Institute of Public Works Engineering Australasia Queensland | en_US |
dc.subject | AI Asset management | en_US |
dc.title | Empowering Regional Engineers: The Cost-Saving Potential of AI in Public Works | en_US |
dc.type | Audio Visual Recording | en_US |
Appears in Collections: | 2024 Annual Conference Brisbane - Audiovisual Presentations |
Files in This Item:
File | Description | Size | Format | |
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Session 18 final.mp4 | 251.78 MB | Unknown | View/Open | |
Proterra Group - AI for Regional Engineers.pdf | 2.92 MB | Adobe PDF | View/Open | |
IPWEA-QNT Conference Paper - AI Empowering Regional Engineers J.O'Dea.pdf | 980.05 kB | Adobe PDF | View/Open |
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