Online/ e-LMS
Self Paced
Moderate
3 Weeks
About
Participants will learn how AI is applied in developing smart cities, from optimizing urban infrastructure and traffic management to enhancing public safety and sustainability efforts. The course focuses on real-time data analysis, predictive modeling, and IoT integration for smart city infrastructure.
Aim
This program explores how AI technologies are transforming urban planning, management, and infrastructure, focusing on intelligent systems for energy, transportation, security, and waste management. It equips learners with the knowledge to integrate AI into smart city frameworks.
Program Objectives
- Understand AI’s role in transforming urban infrastructure and services.
- Learn to implement AI systems for traffic, energy, and waste management.
- Gain skills in AI-based public safety and urban sustainability.
- Explore predictive analytics for smart city infrastructure optimization.
- Develop practical experience through real-world case studies.
Program Structure
Program Structure: Smart Cities and AI
Module 1: Introduction to Smart Cities and AI
- Chapter 1: Overview of Smart Cities: Concepts and Components
- Lesson 1.1: Definition and Key Characteristics of Smart Cities
- Lesson 1.2: Core Components: Infrastructure, Technology, and Services
- 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
- Lesson 2.1: AI and its Role in Urban Management
- Lesson 2.2: AI-Enabled Urban Services: From Traffic to Healthcare
- Lesson 2.3: The Evolution of AI Applications in City Planning
- Chapter 3: Case Studies: Smart Cities Worldwide
- Lesson 3.1: Singapore: A Global Leader in Smart City Innovation
- Lesson 3.2: Barcelona: A Blueprint for Smart Urban Living
- Lesson 3.3: Dubai: Pioneering Smart Governance and Technology-Driven Services
Module 2: AI for Traffic Management and Smart Mobility
- Chapter 4: AI for Traffic Management and Transportation
- Lesson 4.1: AI for Real-Time Traffic Flow Analysis
- Lesson 4.2: Predictive Traffic Control Systems and Congestion Reduction
- Chapter 5: Optimizing Public Transportation Networks with AI
- Lesson 5.1: AI for Route Optimization and Schedule Prediction
- Lesson 5.2: Enhancing Commuter Experience with AI Tools
- Chapter 6: Autonomous Vehicles and Smart Mobility Solutions
- Lesson 6.1: Autonomous Vehicles: AI and the Future of Mobility
- Lesson 6.2: AI for Smart Mobility Ecosystems and Ride-Sharing Optimization
Module 3: AI in Energy Management and Sustainability
- Chapter 7: AI for Energy Consumption Monitoring and Optimization
- Lesson 7.1: AI Tools for Real-Time Energy Consumption Tracking
- Lesson 7.2: Predictive Maintenance in Energy Systems with AI
- Chapter 8: Smart Grids: AI for Demand Forecasting and Load Balancing
- Lesson 8.1: AI-Driven Smart Grids: An Overview
- Lesson 8.2: Energy Load Balancing with AI: Challenges and Solutions
- Chapter 9: AI in Renewable Energy Integration
- Lesson 9.1: AI for Renewable Energy Forecasting and Grid Integration
- Lesson 9.2: Enhancing Energy Efficiency Through AI
Module 4: AI in Waste Management and Urban Sustainability
- Chapter 10: Smart Waste Collection Systems Using AI
- Lesson 10.1: AI in Waste Collection Route Optimization
- Lesson 10.2: Reducing Waste with Data-Driven AI Solutions
- Chapter 11: AI for Sorting and Recycling
- Lesson 11.1: Computer Vision in Recycling: Automating Sorting Processes
- Lesson 11.2: Robotics in Waste Management: AI Applications
- Chapter 12: AI-Driven Sustainability Initiatives in Urban Environments
- Lesson 12.1: Leveraging AI for Urban Sustainability Metrics
- 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
- Lesson 13.1: AI-Powered Surveillance: Technologies and Ethics
- Lesson 13.2: AI in Threat Detection and Urban Safety
- Chapter 14: AI-Powered Emergency Response Systems
- Lesson 14.1: AI-Driven Emergency Dispatch and First Responder Systems
- Lesson 14.2: AI Applications in Predicting and Managing Urban Disasters
- Chapter 15: Facial Recognition, Threat Detection, and Privacy Concerns
- Lesson 15.1: The Role of Facial Recognition in Smart City Security
- Lesson 15.2: Balancing Safety and Privacy: Ethical Implications
Module 6: AI for Environmental Monitoring and Climate Action
- Chapter 16: AI for Air Quality and Pollution Monitoring
- Lesson 16.1: Monitoring Air Quality with AI Sensors
- Lesson 16.2: Predictive Analytics for Pollution Control
- Chapter 17: Climate Change Modeling and Mitigation with AI
- Lesson 17.1: AI for Climate Data Analysis and Forecasting
- Lesson 17.2: AI in Urban Climate Resilience Planning
- Chapter 18: AI in Disaster Management
- Lesson 18.1: Predicting Natural Disasters with AI
- 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
- Lesson 19.1: AI for Disease Detection and Epidemic Tracking
- Lesson 19.2: AI-Enhanced Urban Healthcare Infrastructure
- Chapter 20: AI Applications for Mental Health and Wellbeing
- Lesson 20.1: AI-Driven Mental Health Monitoring Tools
- 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
- Lesson 21.1: Real-Time Water Usage Monitoring with AI
- Lesson 21.2: AI in Predictive Maintenance for Water Networks
- Chapter 22: AI for Leak Detection and Maintenance Planning
- Lesson 22.1: AI Solutions for Leak Detection in Smart Cities
- 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
- Lesson 23.1: Role of IoT in Smart Cities: Sensors, Data, and AI
- Lesson 23.2: Integrating AI and IoT for Building Management Systems
- Chapter 24: AI-IoT Solutions in Transportation, Security, and Energy Management
- Lesson 24.1: Use Cases of AI and IoT in Smart Transportation
- 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
- Lesson 25.1: Responsible AI in Smart City Development
- Lesson 25.2: Case Studies in Ethical AI Implementations
- Chapter 26: Ensuring Data Privacy in AI-Driven Smart Cities
- Lesson 26.1: AI and Data Privacy Regulations
- Lesson 26.2: Protecting Citizen Data in Smart Cities
- Chapter 27: AI Governance and Regulation in Smart Cities
- Lesson 27.1: Regulatory Frameworks for AI in Urban Management
- 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
- Lesson 28.1: AI Tools for Community Engagement and Urban Decision-Making
- Lesson 28.2: Case Studies of AI-Driven Civic Participation
- Chapter 29: AI Tools for Urban Planning and Decision-Making
- Lesson 29.1: AI for Urban Planning: Tools and Techniques
- Lesson 29.2: Smart City Data Platforms for Transparency and Participation
Module 12: Final Project
- Chapter 30: Final Project
- Lesson 30.1: Introduction to the Final Project: Problem-Solving in Smart Cities with AI
- Lesson 30.2: Example Projects: Traffic Optimization, Predictive Maintenance, or Public Health Systems
- Lesson 30.3: Project Development: From Ideation to Implementation
Participant’s Eligibility
Urban planners, data scientists, city management professionals, engineers, and AI specialists.
Program Outcomes
- Expertise in designing and implementing AI systems for smart city projects.
- Ability to optimize urban infrastructure through AI-powered technologies.
- Knowledge of integrating AI with IoT and real-time data for smart city management.
- Skills in applying AI to public safety, energy management, and sustainable urban development.
Fee Structure
Standard Fee: INR 4,998 USD 78
Discounted Fee: INR 2499 USD 39
We are excited to announce that we now accept payments in over 20 global currencies, in addition to USD. Check out our list to see if your preferred currency is supported. Enjoy the convenience and flexibility of paying in your local currency!
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Key Takeaways
Program Assessment
Certification to this program will be based on the evaluation of following assignment (s)/ examinations:
Exam | Weightage |
---|---|
Mid Term Assignments | 50 % |
Project Report Submission (Includes Mandatory Paper Publication) | 50 % |
To study the printed/online course material, submit and clear, the mid term assignments, project work/research study (in completion of project work/research study, a final report must be submitted) and the online examination, you are allotted a 1-month period. You will be awarded a certificate, only after successful completion/ and clearance of all the aforesaid assignment(s) and examinations.
Program Deliverables
- Access to e-LMS
- Real Time Project for Dissertation
- Project Guidance
- Paper Publication Opportunity
- Self Assessment
- Final Examination
- e-Certification
- e-Marksheet
Future Career Prospects
- Smart City Planner
- AI Solutions Architect for Infrastructure
- Urban Data Scientist
- Smart Transportation Manager
- Sustainability Consultant
- AI Infrastructure Specialist
Job Opportunities
- City governments integrating AI in smart city initiatives.
- Urban planning and architecture firms implementing AI-based infrastructure.
- Tech companies building AI-powered solutions for smart transportation and utilities.
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