As smart energy systems and cities generate vast amounts of sensor and IoT data, processing it at the edge — closer to the source — is essential for fast, autonomous response. PA 1 advances real-time anomaly detection using Edge AI, enabling infrastructure systems to identify and respond to incidents without cloud dependency.

Key innovations include federated machine learning across distributed edge nodes, adaptive algorithms for continuous monitoring, and autonomous decision-making for both energy grids and urban environments.

Secure, uninterrupted data flow is the backbone of resilient infrastructure. PA 2 develops a modular IoT connectivity management platform integrating multiple communication channels — cellular, satellite, LoRaWAN, and more — with a unified authentication and profile management system.

The cybersecurity component introduces continuous threat monitoring and vulnerability assessment, advancing beyond traditional static security frameworks to provide adaptive, proactive protection for critical infrastructure networks.

PA 3 develops the scalable middleware that ties together the RESCUE system — enabling interoperability between edge devices and cloud services, managing distributed federated AI models, and ensuring the platform remains operational even when parts of the infrastructure are down or compromised.

This includes standardised APIs, data model frameworks, and the distributed architecture needed for mission-critical applications to continue running during disruptions.