Selçuk University
Discussion
Started 11 December 2021
Human-Machine Intelligence in Civil and Environmental Engineering
What is the boundary between the tasks that need human interventions and the tasks that can be fully autonomous in the domain of civil and environmental engineering? What are ways of establishing a human-machine interface that combines the best parts of human intelligence and machine intelligence in different civil and environmental engineering problem-solving processes? Any tasks that can never be autonomous and need civil and environmental engineers? Coordinating international infrastructure projects? Operating future cities with many interactions between building facilities? We would love to learn from you about your existing work and thoughts in this broad area and hope we can build the future of humans and civil & environmental engineering together.
Please see this link for an article that serves as a starting point for this discussion initiated by an ASCE task force:
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Popular replies (1)
Dhofar University
Dear Dr Pingbo Tang . See the following useful link: https://www.mdpi.com/topics/Artificial_intelligence_Civil_Engineering
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All replies (20)
Dhofar University
Dear Pingbo Tang
Civil engineers may employ AI models to make building projects more precise, less expensive, and less disruptive. This involves depending on off-site facilities run by autonomous robots that assemble crucial components of a construction project, which are subsequently assembled on-site by human labour.
Machine learning has also been used to identify modal parameters, perform sparse time-frequency analysis, and rebuild sparse data. The solution technique of compressive sensing–based data reconstruction is codified into a regular supervised-learning job for sparse data reconstruction.
AI and Machine Learning have several potential uses in building. Machine learning is that intelligent helper, assisting teams in identifying the most essential risk factors in terms of construction safety and quality that require immediate attention.
Kind Regards
Qamar Ul Islam
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Carnegie Mellon University
Thanks, Qamar, these are great mentions of AI and machine learning applications in the domain of construction engineering and civil engineering projects.
Carnegie Mellon University
Seyed Mostafa Banihashem Thank you so much, Seyed. These are great articles, touch both human and machine intelligence for engineering. We will certainly review and learn from you. The next step of our efforts will be a series of webinars and online discussions, we may try to reach out to these researchers.
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The University of Texas at Arlington
Pingbo Tang your welcome dear. It's kind of you.
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Carnegie Mellon University
Kiprotich Kiptum thank you so much, water resource is a big area of using human and machine intelligence for discovering risks related to water treatment and water use. Thanks!
Dhofar University
Dear Dr Pingbo Tang . See the following useful link: https://www.mdpi.com/topics/Artificial_intelligence_Civil_Engineering
4 Recommendations
Dhofar University
Kindly see also the following beneficial link: https://arxiv.org/pdf/2107.13498
2 Recommendations
Dhofar University
Also see kindly the following useful link: https://www.sciencedirect.com/science/article/am/pii/S0141029617335526
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University of Diyala
AI have many applications in the Civil and environmental engineering in construction design and management and BMI
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Carnegie Mellon University
Aref Wazwaz Thanks, Aref, very informative sources.
Carnegie Mellon University
Ali J. Abboud Thanks, Ali, yes, AI in construction through many BIM-enabled approaches are blooming in the past 10 years. Thanks for sharing.
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Dhofar University
You are most welcome dear Pingbo Tang .
Wish you the best always.
2 Recommendations
University of Diyala
You are most welcome dear Pingbo Tang .
Wish you the best always.
4 Recommendations
Carnegie Mellon University
Dauji Saha
You are welcome, Dauji, I hope to learn from all of you about this topic. I am sure that we can build this topic together.2 Recommendations
University of Waterloo
This is the topic of our recently published paper.
We use a HoloLens 2 headset to perform structural inspections. We deploy an interactive segmentation algorithm to segment damaged regions on the bridge. Our work falls under the umbrella of human-AI collaboration because the user selects initial seed points inside and outside the damage region, and then the AI uses those points to refine the segmentation result.
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Are very small or negative p-norm stress sensitivity values expected in global p-norm stress measure?
I'm working on p-norm topology optimization in plane stress using a MATLAB code adapted from the article An efficient 146-line 3D sensitivity analysis code of stress-based topology optimization" by Hao Deng, Praveen S. Vulimiri and Albert C.To. I've noticed small sensitivity values (e.g., 4.54e-05, -7.30e-09) with a stress norm parameter (p) of 5. Are such values typical in this context, and should negative sensitivity values be expected? The relevant codes are attached.
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