Artificial Intelligence (AI) in construction
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The document outlines an introductory session on the application of analytics in construction management, covering terminologies, practical applications, and future strategies. It emphasizes the importance of knowledge sharing, networking, and upskilling for construction practitioners and data scientists. Additionally, it describes various analytics applications in construction such as cost estimation, performance monitoring, and risk analysis, alongside future community engagement plans.
Artificial Intelligence (AI) in construction
- 1. Application of Analytics in Construction Management An Introductory session Source: https://www.freepik.com/free-photos-vectors/business >Business vector created by starline - www.freepik.com
- 2. Problem definition Introduction 01 Understand terminologies Definitions 02 Investigate practical applications in various areas of construction Practical Applications 03 Discuss Future Strategies The Meetup Strategy 04 Agenda Source: https://www.freepik.com/free-photos-vectors/background >Background vector created by rawpixel.com - www.freepik.com
- 3. Introduction
- 6. Why bother? Data and Analytics Facility for National Infrastructure
- 8. • Knowledge Sharing • Interdisciplinary interaction • Networking • Bridging the gap between the industry and academia • Share success cases • Upskilling construction practitioners in the field of Analytics • Upskill data scientist and Analytics professionals with the opportunities in the construction industry • Collaboration and joint efforts to disrupt current practices in the construction industry Objectives of this Meetup
- 9. Definition
- 10. Definitions Business Case Analysis Qualitative Analytics Preliminary Data Report Business Intelligence Forecasting Optimisation of operations Business Data Science PresentPast Future
- 11. Definitions Business Case Analysis Qualitative Analytics Preliminary Data Report Dashboard Reporting Forecasting Optimisation of operations Business Artificial Intelligence Machine Learning Data Science/ Analytics PresentPast Future Business Intelligence
- 12. Types of Data Data Types Structured Data Continuous Categorical Big Data Later
- 13. Predictive Analytics Predictive Analytics Supervised Regression Classification Unsupervised Clustering Reinforcement
- 16. Classification
- 18. Big Data Analytics Big Data Analytics Computer Vision Natural Language Processing Audio Recognition
- 19. Neural Networks
- 23. Data in Construction Context Cost Estimating Change Management Cost Control Finance (ERP) Risk Analysis Programme Management Performance & Reporting
- 24. Data Streamlining using BIM Cost Estimating Change Management Cost Control Finance (ERP) Risk Analysis Programme Management Performance & Reporting BIM
- 25. Analytics Applications in Construction Discipline Applications Health and Safety PPE detection, Hazards warning, Near miss reporting Pose estimation for detecting Security Face recognition ANPR Automated detection of intruders Theft detection Quality Compliance check, defects inspection, process validation Stakeholders Quantification of Community engagement effectiveness Duration prediction for consents Environment Emission prediction Recycling using CV and Robots Ecology Surveys
- 26. Analytics Applications in Construction Discipline Applications Controls and Reporting BI tools to automate reporting Performance monitoring Automated progress capturing Accurate forecasting Schedule duration estimation Cost estimation prediction Procurement Work winning Review bidding companies Commercial Management of Contracts Correspondence Monitoring Engineering Design Compliance Review Design Recommendations Recommendations for design HR Recruitment skills analysis Interview video analysis Absenteeism prediction
- 27. Data Science for H&S
- 28. Security
- 32. Procurement RFP • Request for proposal Requirements • Using natural language processing (NLP) requirements are extracted Mapping to offering • Identified requirements are mapped to offerings Pricing • Using predictive algorithm, estimation of price is performed Outcome • Predicting bidding outcome with high level of confidence Win/No Win
- 34. Next Steps Our plan • Monthly Meetup • Survey for other plans • Workshops • Hackathons • Training Sessions • Open Data Initiative (ODI)
- 35. • This community is owned by everyone. Hence, we are expecting community. • Promoting the community to your contacts • Propose Speakers • Volunteers for organising • Venues to host upcoming events. Next event is planned on 9th July. Details to follow Your Contributions
- 36. Q&A
- 37. Amsterdam Birmingham Brisbane Dublin Hong Kong London Perth Sydney