AI and Robotics for Smart Public Infrastructure Monitoring

The project aims to develop an advanced AI and robotics-enabled framework for real-time monitoring, assessment, and maintenance of public infrastructure across urban and regional environments. By integrating deep learning, audio-visual processing, sensor fusion, and autonomous robotic systems, the solution will enable continuous inspection of critical assets such as roads, bridges, rail networks, tunnels, and public buildings.

The proposed system will deploy autonomous ground and aerial robots equipped with multimodal sensing capabilities (visual, thermal, acoustic, LiDAR and satellite imaging) to detect structural defects, environmental risks, and safety hazards. AI-driven analytics will process multimodal data streams to enable predictive maintenance, anomaly detection, and early warning of infrastructure failures.

The project strengthens societal resilience, supports sustainable and safe public spaces, and accelerates the digital transformation of public services. It promotes human-centric and trustworthy AI while enhancing efficiency, reducing maintenance costs, and improving safety for citizens. Expected outcomes include scalable robotic inspection systems, interoperable AI platforms, and guidelines for ethical and responsible deployment of autonomous technologies in public infrastructure management.