Using Artificial Intelligence for monitoring critical scenarios

Challenge

The ACCOLADES project aimed to develop Artificial Intelligence (AI) algorithms applied to a cognitive SAR (Synthetic Aperture Radar) system for monitoring of critical scenarios such as landslides, earthquakes, floods, and civil security, by automatically identifying the type of scenario observed. 

The goal was to enable the radar to autonomously recognize the scenario and optimally adjust its operational parameters, such as frequency, instantaneous bandwidth, and PRI, based on the specific requirements and functionalities to be implemented. 

To complete this process, a multi-frequency airborne SAR technology demonstrator was designed and built, allowing the validation of the developed techniques. 

Applied expertise 

To address this challenge, a wide range of skills were needed, from project management and activity monitoring to the collection and analysis of user and scenario requirements and constraints. The work included the development and implementation of AI algorithms, support for the validation of the demonstrator, and the definition of an evolutionary roadmap. 

Additionally, the project involved the identification and characterization of relevant scenarios for AI model training, the design of Big Data architectures for SAR data management and processing, and the development of software to integrate AI algorithms into the overall system. 

Impact 

This project paved the way for technological advancements in robotics and artificial intelligence, promoted the analysis and management of big data, and introduced cutting-edge solutions based on high-resolution sensors and digital signal processing techniques. 

The innovations also encompassed the design of embedded systems and cognitive multi-band radars, with applications in strategic sectors such as security, defense, aviation, agriculture, meteorology, and transportation.  

Project Consortium

1) RINA 2) NHAZCA 3) ECHOES 4) CNIT