Lesson 6.2: Smart Grids – AI for Demand Forecasting and Load Balancing

AI in Smart Cities and Infrastructure

Lesson 6.2: Smart Grids – AI for Demand Forecasting and Load Balancing

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Module 1: Introduction to Smart Cities and AI

Chapter 1: Overview of Smart Cities: Concepts and Components

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Lesson 1.1 Definition and Key Characteristics of Smart Cities

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Lesson 1.2: Core Components: Infrastructure, Technology, and Services

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Lesson 1.3: The Role of Data in Smart Cities: Big Data, IoT, and AI

Chapter 2: Role of AI in Building and Managing Smart Cities

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Lesson 2.1: AI and Its Role in Urban Management

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Lesson 2.2: AI-Enabled Urban Services: From Traffic to Healthcare

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Lesson 2.3: The Evolution of AI Applications in City Planning

Chapter 3: Case Studies – Smart Cities Worldwide

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Lesson 3.1: Singapore: A Global Leader in Smart City Innovation

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Lesson 3.2: Barcelona: A Blueprint for Smart Urban Living

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Lesson 3.3: Dubai – Pioneering Smart Governance and Technology-Driven Services

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Video Lecture-1

Module 2: AI for Traffic Management and Smart Mobility

Chapter 4: AI for Traffic Management and Transportation

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Lesson 4.1: AI for Real-Time Traffic Flow Analysis

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Lesson 4.2: Predictive Traffic Control Systems and Congestion Reduction

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Lesson 4.3: Optimizing Public Transportation Networks with AI

Chapter 5: Autonomous Vehicles and Smart Mobility Solutions

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Lesson 5.1: The Role of AI in Autonomous Vehicles

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Lesson 5.2: AI and Smart Mobility Solutions for Sustainable Cities

Chapter 6: Energy Management and Sustainability with AI

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Lesson 6.1: AI for Energy Consumption Monitoring and Optimization

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Lesson 6.2: Smart Grids – AI for Demand Forecasting and Load Balancing

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Video Lecture - 2

Module 3: AI in Energy Management and Sustainability

Chapter 7: AI for Energy Consumption Monitoring and Optimization

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Lesson 7.1: AI Tools for Real-Time Energy Consumption Tracking

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Lesson 7.2: AI for Predictive Energy Management and Efficiency

Chapter 8: AI in Renewable Energy Integration and Efficiency

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Lesson 8.1: AI for Renewable Energy Forecasting and Optimization

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Lesson 8.2: AI for Renewable Energy Integration and Grid Stability

Chapter 9: AI in Public Safety and Security in Smart Cities

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Lesson 9.1: AI for Real-Time Surveillance and Monitoring

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Lesson 9.2: AI-Powered Emergency Response Systems

Module 4: AI in Waste Management and Urban Sustainability

Chapter 10: Smart Waste Collection Systems Using AI

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Lesson 10.1: AI in Waste Collection Route Optimization

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Lesson 10.2: Reducing Waste with Data-Driven AI Solutions

Chapter 11: AI for Sorting and Recycling

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Lesson 11.1: Computer Vision in Recycling – Automating Sorting Processes

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Lesson 11.2: Robotics in Waste Management – AI Applications

Chapter 12: AI-Driven Sustainability Initiatives in Urban Environments

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Lesson 12.1: Leveraging AI for Urban Sustainability Metrics

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Lesson 12.2: AI for Resource Optimization and Circular Economy Initiatives

Module 5: Public Safety and Security in Smart Cities

Chapter 13: AI for Real-Time Surveillance and Monitoring

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Lesson 13.1: AI-Powered Surveillance Systems for Enhanced Urban Security

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Lesson 13.2: AI in Threat Detection and Urban Safety

Chapter 14: AI-Powered Emergency Response Systems

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Lesson 14.1: AI-Enhanced Emergency Services for Faster and Smarter Crisis Management

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Lesson 14.2: AI for Real-Time Disaster Prediction and Mitigation

Chapter 15: Facial Recognition, Threat Detection, and Privacy Concerns

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Lesson 15.1: The Role of Facial Recognition in Smart City Security

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Lesson 15.2: Balancing Safety and Privacy: Ethical Implications

Module 6: AI in Environmental Monitoring and Climate Action

Chapter 16: AI for Air Quality and Pollution Monitoring

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Lesson 16.1: AI in Real-Time Air Quality Monitoring Systems

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Lesson 16.2: Predictive Analytics for Pollution Control

Chapter 17: Climate Change Modeling and Mitigation with AI

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Lesson 17.1: AI for Climate Data Analysis and Forecasting

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Lesson 17.2: AI in Urban Climate Resilience Planning

Chapter 18: AI in Disaster Management

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Lesson 18.1: Predicting Natural Disasters with AI

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Lesson 18.2: AI Tools for Response and Recovery Planning

Module 7: AI in Public Health and Urban Wellbeing

Chapter 19: AI for Monitoring Public Health Trends

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Lesson 19.1: AI for Disease Detection and Epidemic Tracking

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Lesson 19.2: AI-Enhanced Urban Healthcare Infrastructure

Chapter 20: AI Applications for Mental Health and Wellbeing

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Lesson 20.1: AI-Driven Mental Health Monitoring Tools

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Lesson 20.2: Enhancing Urban Wellbeing with AI-Enabled Solutions

Module 8: AI for Water Management and Smart Infrastructure

Chapter 21: Optimizing Water Distribution Systems with AI

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Lesson 21.1: Real-Time Water Usage Monitoring with AI

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Lesson 21.2: AI in Predictive Maintenance for Water Networks

Chapter 22: AI for Leak Detection and Maintenance Planning

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Lesson 22.1: AI Solutions for Leak Detection in Smart Cities

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Lesson 22.2: AI for Efficient Water Resource Management

Module 9: Smart Buildings and AI-Driven Infrastructure Management

Chapter 23: AI and IoT Integration in Smart Cities

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Lesson 23.1: Role of IoT in Smart Cities: Sensors, Data, and AI

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Lesson 23.2: Integrating AI and IoT for Building Management Systems

Chapter 24: AI-IoT Solutions in Transportation, Security, and Energy Management

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Lesson 24.1: Use Cases of AI and IoT in Smart Transportation

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Lesson 24.2: AI for Smart Energy and Security Solutions in Urban Spaces

Module 10: Ethics, Privacy, and Security in AI-Driven Smart Cities

Chapter 25: Ethical Considerations for AI in Public Spaces

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Lesson 25.1: Responsible AI in Smart City Development

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Lesson 25.2: Case Studies in Ethical AI Implementations

Chapter 26: Ensuring Data Privacy in AI-Driven Smart Cities

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Lesson 26.1: AI and Data Privacy Regulations

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Lesson 26.2: Protecting Citizen Data in Smart Cities

Chapter 27: AI Governance and Regulation in Smart Cities

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Lesson 27.1: Regulatory Frameworks for AI in Urban Management

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Lesson 27.2: AI Governance Challenges in Smart Cities

Module 11: AI and Citizen Engagement in Smart Cities

Chapter 28: AI for Enhancing Civic Participation

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Lesson 28.1: AI Tools for Community Engagement and Urban Decision-Making

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Lesson 28.2: Case Studies of AI-Driven Civic Participation

Chapter 29: AI Tools for Urban Planning and Decision-Making

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Lesson 29.1: AI for Urban Planning: Tools and Techniques

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Lesson 29.2: Smart City Data Platforms for Transparency and Participation

Assessments

AI in Smart Cities and Infrastructure 40 MCQs