Edge AI for Smart Cities

• An understanding of AI and machine learning concepts
• Basic knowledge of urban planning and smart city technologies
• Experience with project management or engineering principles

Audience

• Urban planners
• Civil engineers
• Smart city project managers

Edge AI for Smart Cities focuses on the implementation of Edge AI technologies in smart city infrastructures, covering applications such as traffic management, surveillance, and resource optimization. This course provides practical knowledge and strategies to integrate Edge AI into urban environments, enhancing the efficiency and functionality of smart city projects.

This instructor-led, live training (online or onsite) is aimed at intermediate-level urban planners, civil engineers, and smart city project managers who wish to leverage Edge AI for smart city initiatives.

By the end of this training, participants will be able to:

• Understand the role of Edge AI in smart city infrastructures.
• Implement Edge AI solutions for traffic management and surveillance.
• Optimize urban resources using Edge AI technologies.
• Integrate Edge AI with existing smart city systems.
• Address ethical and regulatory considerations in smart city deployments.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Introduction to Edge AI in Smart Cities

• Overview of Edge AI and its applications in smart cities
• Key benefits and challenges of Edge AI in urban environments
• Current trends and innovations in smart city technologies
• Case studies of successful Edge AI implementations in smart cities

Traffic Management with Edge AI

• Real-time traffic monitoring and analysis
• Adaptive traffic signal control and congestion management
• Integration with transportation networks and systems
• Case studies of Edge AI in traffic management

Surveillance and Public Safety

• Intelligent video surveillance systems
• Real-time incident detection and response
• Enhancing public safety with Edge AI
• Case studies of Edge AI in surveillance and public safety

Resource Optimization in Smart Cities

• Energy management and optimization
• Water and waste management using Edge AI
• Smart lighting and infrastructure management
• Case studies of resource optimization with Edge AI

Integrating Edge AI with Smart City Systems

• Architectural considerations for Edge AI integration
• Interoperability with existing smart city technologies
• Data management and analytics
• Case studies of integrated smart city solutions

Ethical and Regulatory Considerations

• Addressing privacy concerns in Edge AI applications
• Ensuring compliance with regulations and standards
• Ethical implications of Edge AI in smart cities
• Case studies of ethical Edge AI implementations

Innovative Use Cases and Applications

• Exploring cutting-edge applications of Edge AI in smart cities
• In-depth case studies and success stories
• Future trends and opportunities in smart city technologies

Hands-On Projects and Exercises

• Designing and implementing an Edge AI solution for a smart city scenario
• Collaborative group exercises and projects
• Project presentations and feedback

Summary and Next Steps