32, AI-Driven Decision-Making in Civil Engineering Projects
The chapter discusses the revolutionary impact of Artificial Intelligence (AI) on civil engineering, emphasizing its capacity to refine decision-making processes throughout infrastructure projects. It covers various AI technologies, their applications in decision-making models, data sources, and the integration of AI with traditional systems like BIM and GIS. Additionally, challenges and future directions are highlighted, showcasing AI's transformative potential in enhancing efficiency and sustainability in civil engineering practices.
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Sections
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32.4.4Quality Assurance And Defect Detection
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32.16.3Disaster Resilience Planning
What we have learnt
- AI significantly enhances decision-making processes in civil engineering projects.
- AI technologies such as machine learning and neural networks are crucial for predictive modeling and project management.
- Integration of AI with existing frameworks like BIM and GIS leads to improved project outcomes and efficiency.
Key Concepts
- -- Machine Learning
- A subset of AI that enables systems to learn from data and improve their performance over time without being explicitly programmed.
- -- Predictive Modeling
- Using statistical techniques and algorithms to forecast future outcomes based on historical data.
- -- Digital Twin
- A digital replica of a physical entity that utilizes real-time data to simulate, predict, and optimize performance.
- -- Intelligent Decision Support Systems (IDSS)
- Systems that aid in decision-making by combining data analysis, predictive modeling, and user interaction.
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