SMAIL-AI
SMAIL-AI (Sistema di Monitoraggio Avanzato di Infrastrutture di Linea in Artificial Intelligence) is an advanced research and development project focused on enabling autonomous and intelligent monitoring of distributed infrastructure networks in mountainous or hard-to-reach environments. Jointly developed by Blue Engineering and the 3D LAB of Politecnico di Torino, the project is part of the Regional Innovation Strategy for Ecological Transition and combines state-of-the-art drone technology, artificial intelligence (AI), and extended reality (XR) to transform traditional maintenance and inspection methods.
The core innovation of SMAIL-AI lies in its autonomous aerial monitoring platform. Equipped with advanced sensors and computer vision algorithms, the system can detect and predict potential failures in infrastructure, such as vegetation overgrowth, physical obstructions, and structural anomalies. This drastically reduces the reliance on manual inspections, especially in areas that pose safety risks for human operators. The use of AI enables not only real-time diagnostics but also predictive analytics, leveraging historical data to forecast future failures and support preventive maintenance strategies.
The drone fleet is designed to operate independently, guided by recharge stations distributed along the monitored routes. These stations also serve as data repositories and emergency communication hubs, offering both environmental sustainability and increased resilience in remote regions. On the software side, the project includes the development of a modular AI platform capable of evolving through continuous training, as well as a user interface enhanced by XR technologies for technician training and human-system interaction.
SMAIL-AI represents a leap forward in the fields of Digital Twin technologies. The 3D LAB contributes expertise in immersive data visualization and AI-driven scene understanding, ensuring that both technical operators and decision-makers have access to accurate, actionable information. The project is expected to reach a TRL 6/7 through pilot deployment in collaboration with infrastructure operators in the Aosta Valley, such as electric grid managers and ski lift operators.
With significant potential for national and international scalability, SMAIL-AI positions itself at the forefront of sustainable infrastructure monitoring, offering a blueprint for smart, autonomous, and eco-friendly maintenance solutions.