Use Cases
Smart Industry
Modern industries rely on Industrial Control Systems (ICSs) for monitoring and controlling industrial processes. They are widely used in industries such as manufacturing, energy, water treatment, and transportation to ensure efficient and reliable operation.
An ICS consists of several components that work together to monitor, control, and manage industrial processes, ensuring efficiency, safety, and reliability. These include: Human-Machine Interfaces, Control Units, Programmable Logic Controllers (PLCs), Networks, Sensors and actuators.
Modern ICSs are increasingly leveraging the edge-to-cloud continuum to enhance operational efficiency, scalability, and real-time decision-making:
Real-Time Processing: Critical tasks are handled at the edge, minimizing delays.
Scalability: Cloud infrastructure handles larger, more complex workloads.
AI/ML Integration: Cloud-hosted models are deployed at the edge for real-time inference.
Smart Cities
The Smart City Use Case focuses on deploying and validating advanced AI and cybersecurity technologies within an urban environment by leveraging the cloud-edge continuum. The goal is to enhance the efficiency, scalability, and security of smart city operations while ensuring compliance with privacy regulations and addressing the needs of diverse stakeholders such as municipalities, law enforcement agencies, and citizens.
Key aspects are:
Multi-modal Sensing and Data Processing: A smart city testbed typically integrates a variety of sensing devices, including cameras, environmental sensors, and audio devices. These devices collect data to support diverse AI tasks such as people/object detection and tracking, traffic monitoring, sound event detection, scene and behavior understanding, and coordination of autonomous vehicles. Data processing occurs across the cloud-edge continuum to ensure real-time decision-making and efficient resource use.
Heterogeneous infrastructure, data and technology: The testbed requires a scalable, heterogeneous infrastructure that spans from low-power IoT devices at the edge to powerful cloud servers, passing through technology embedded in vehicles. Therefore, the AI tasks and security services must adapt to varying resource availability and operational conditions. Similarly, data heterogeneity must be taken into account.
Privacy-preserving processing. Privacy-by-design principles are central to the development of smart city services, safeguarding sensitive data collected by sensors while enabling stakeholders to access meaningful insights.