The GIANT Project: AI-Driven Optimization of Cathodic Protection in Gas Networks
Abstract
Abstract The challenges associated with the operation of gas distribution networks are multidimensional due to their complexity: environmental, operational, financial, and safety related. In this context, impressed current cathodic protection (ICCP), used to prevent corrosion of steel pipelines, is crucial to ensure the safety and integrity of the network. Despite the energy consumption and associated CO2 equivalent emissions, the benefits offered by the ICCP in terms of preventing infrastructure damage and safety (avoiding gas leaks) more than justify the associated environmental costs. The GIANT (Gas Integrated and Automated Network Technology) project proposes innovative solutions to optimize cathodic protection management, integrating remote monitoring devices, centralized software for data analysis and remote-control systems. In particular, the application of artificial intelligence enables dynamic regulation of the cathodic protection current. This optimized regulation allows a significant reduction in the energy consumption of cathodic protection power supplies, improving their efficiency and contributing to the reduction of CO2 equivalent emissions. Thanks to continuous monitoring of field conditions and automatic corrective interventions, the GIANT project enables digital and automated management of cathodic protection. In addition, the introduction of AI-powered predictive maintenance further optimizes the system, predicting failures or inefficiencies before they occur. This approach helps prevent malfunctions and reduce the need for costly field interventions. The complete digitization of the operational management process ensures cost savings, increased productivity and an overall increase in network reliability and security.
Fields of Study & Subjects
Structural Integrity and Reliability Analysis
Engineering Diagnostics and Reliability
Corrosion Behavior and Inhibition
Publication details
- Journal / source
- IEEE Lasers and Electro-Optics Society Annual Meeting (LEOS)
- Pages
- 1–9
- Publication date
- 6 March 2026
- Language
- EN