Edge AI for Smart Cities Training is a focused two-day program designed to help professionals understand how deploying artificial intelligence at the edge enables real-time, scalable, and secure smart city solutions. This course explores how Edge AI supports intelligent urban infrastructure, traffic management, public safety, energy optimization, and citizen services by processing data locally from sensors, cameras, and IoT devices, enabling faster decision-making and improved urban efficiency.

• Understand Edge AI for smart cities
• Learn smart infrastructure concepts
• Understand real-time urban data processing
• Gain knowledge of intelligent traffic systems
• Learn smart surveillance basics
• Understand IoT and edge integration
• Explore urban automation applications
• Identify smart city AI use cases

• Smart city planners and urban development professionals
• Government and public sector technology teams
• IoT and edge computing engineers
• AI and data science professionals working on city-scale systems
• Infrastructure, mobility, and sustainability leaders

• Basic understanding of smart city concepts or urban infrastructure
• Familiarity with IoT, sensors, or connected systems
• General awareness of artificial intelligence or data analytics
• Interest in real-time and large-scale urban AI solutions

• Understanding Edge AI concepts applied to smart cities
• Awareness of real-time data processing for urban infrastructure
• Knowledge of Edge AI use cases in mobility, safety, and utilities
• Evaluating privacy, security, and governance considerations
• Interpreting real-world Edge AI smart city deployments

By the end of this training, participants will be able to explain how Edge AI powers smart city solutions, understand deployment and operational challenges at city scale, evaluate privacy and governance considerations, and assess how Edge AI improves efficiency, safety, and sustainability in urban environments.

Introduction to Edge AI for Smart Cities
• Definition and scope of Edge AI in urban environments
• Difference between cloud-based and edge-based smart city AI
• Benefits of low latency, scalability, and resilience
• Overview of smart city Edge AI use cases

Smart City Edge Architecture and Infrastructure
• Urban IoT devices, sensors, and edge nodes
• Cameras, traffic systems, and environmental sensors
• Data flow between edge, control centers, and cloud
• Infrastructure design and deployment considerations

AI Models for Smart City Edge Applications
• Selecting models suitable for city-scale edge environments
• Accuracy, latency, and scalability trade-offs
• Computer vision and signal processing at the edge
• Evaluating performance in real-world urban conditions

Deployment, Optimization, and Operations
• Model optimization for large-scale edge deployments
• Managing updates and lifecycle of edge AI systems
• Monitoring performance and operational reliability
• Integrating Edge AI with existing city platforms

Privacy, Security, and Governance
• Citizen data privacy and responsible AI usage
• Security challenges in city-wide edge systems
• Policy, compliance, and governance considerations
• Building public trust in smart city AI initiatives

Smart City Use Cases and Future Trends
• Intelligent traffic and mobility management
• Public safety and surveillance analytics
• Smart energy, utilities, and sustainability
• Future directions of Edge AI in smart urban ecosystems

• Edge AI fundamentals
• Smart city technologies
• Intelligent traffic management
• Smart surveillance systems
• IoT and edge integration
• Real-time data processing
• Urban automation concepts
• Public safety applications
• Data privacy and security basics
• Practical smart city scenarios

• Conceptual understanding assessments
• Smart city use case analysis exercises
• Privacy and governance evaluation activity
• Final knowledge evaluation quiz

Participants will receive course materials, slides, reference materials, exercises and access to resources for further learning.

Participants who successfully complete the training will receive an AcadNXT Certification in Edge AI for Smart Cities Training, validating their expertise in applying Edge AI concepts to intelligent urban infrastructure, real-time analytics, and smart city solutions.