30. Introduction to Machine Learning and AI
The chapter provides an extensive overview of Artificial Intelligence (AI) and Machine Learning (ML), focusing on their integral role within civil engineering and construction automation. It discusses the definitions, applications, historical evolution, and current trends of AI and ML, while also addressing various algorithms and their implementation challenges. Key themes include the use of smart robotics, predictive analytics, and data management for improving construction efficiency and safety.
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What we have learnt
- Artificial Intelligence enables machines to perform tasks that typically require human intelligence.
- Machine Learning allows systems to learn from data and enhance performance without explicit programming.
- AI and ML are leveraged in civil engineering for applications including construction automation, structural health monitoring, and urban planning.
Key Concepts
- -- Artificial Intelligence (AI)
- A branch of computer science that aims to create systems capable of performing tasks that would typically require human intelligence.
- -- Machine Learning (ML)
- A subset of AI focused on developing systems that improve their performance on tasks through experience or data.
- -- Deep Learning
- A specialized form of ML that utilizes deep neural networks to analyze large amounts of data, particularly effective with unstructured data like images and sounds.
- -- Natural Language Processing (NLP)
- A field of AI that enables machines to understand and generate human language, often applied in automation and project management in civil engineering.
- -- Digital Twin
- A virtual representation of a physical object or system, used for real-time monitoring and predictive analytics to optimize performance.
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