Environmental sensing and geoinformatics for reliability-based optimization of RC bridge maintenance

This paper presents a methodology for managing reinforced concrete (RC) bridges sustainably. It merges environmental monitoring, reliability analysis and genetic algorithm (GA) optimization to support informed decision-making in bridge management. Advanced tools such as remote sensing, IoT sensors, and geoinformatics enable real-time monitoring of environmental factors, including chloride (Cl⁻) ion levels, which can significantly affect bridge integrity. GA principles are applied to design an optimization methodology that enhances bridge resilience and extends structural lifespan through strategic management practices. The paper highlights the expected benefits of this methodology, emphasizing its potential to reduce maintenance applications and costs and, by extension, the environmental footprint. The integration of advanced monitoring technologies with intelligent optimization techniques provides a comprehensive framework for sustainable RC bridge management.