Abstract
In the current environmental context, characterized by an ever-increasing focus on ecosystem protection and climate change, there is a need to develop new technologies capable of monitoring environmental protection and potential adverse scenarios. Resilient Artificial Intelligence (Resilient AI) is a new technology useful for ensuring the operational continuity, accuracy, and safety of critical systems. It enables the detection of anomalies, predicting extreme events, and enabling timely decisions to support environmental protection. Resilient AI promotes the adoption of renewable energy sources, such as photovoltaics, by integrating them into smart grids, improving their efficiency and stability, reducing the risk of outages, minimizing false alarms, and supporting the energy transition towards more sustainable, reliable, and safe systems. The goal of this paper is to provide a comprehensive overview of current and future developments in Resilient AI, highlighting its potential, key challenges, and application prospects in various sectors. Through targeted simulations, the vulnerabilities of AI systems deployed in critical infrastructures essential to daily life (e.g., electricity grids, water, transportation, and telecommunications) will be analyzed, and strategies to improve their security and operational robustness will be evaluated.
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Cirillo, E., Del Prete, A., Mashaallah, Z., Moccardi, A. (2026). Resilient Artificial Intelligence for Environmental Protection and Renewable Energy. In: Barolli, L., Ishida, T., Dantas, M. (eds) Advances on P2P, Parallel, Grid, Cloud and Internet Computing. 3PGCIC 2025. Lecture Notes on Data Engineering and Communications Technologies, vol 277. Springer, Cham. https://doi.org/10.1007/978-3-032-10344-4_7
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