Tackling Heavy Rainstorms with AI

The first challenge is climate adaptation. Our infrastructure needs to be strengthened to withstand extreme weather events such as heavy rains, flooding, and storms. Even in crisis situations, roads, water, and electricity supplies must continue to function to keep society running.

The second challenge is the maintenance backlog. For a long time, investments in maintenance and renewal have been insufficient. For example, Svenskt Vatten estimates that around SEK 12 billion too little is invested annually in the water and sewage (VA) sector. The result is that facilities gradually deteriorate in function, making them more vulnerable when extreme weather strikes.

Although these two challenges are often treated as separate problems, there are clear synergies when they are addressed together. One of the most cost-effective climate adaptation measures is simply to maintain infrastructure so that it functions as intended. Well-maintained infrastructure withstands heavy rain far better than weakened facilities such as broken culverts or uncleared ditches.

Predictive Maintenance with AI

Within initiatives such as the research program Mistra InfraMaint, led by RISE, AI-based solutions for predictive maintenance are being developed. The program brings together researchers, municipalities, and companies to find long-term sustainable solutions for Sweden’s infrastructure. Methods and strategies are being developed that both reduce the maintenance backlog and strengthen climate adaptation. RISE contributes with research, testbeds, and pilot projects that make it possible to quickly translate new ideas into practice.

By combining sensor data, weather forecasts, geodata, and historical maintenance data, machine learning models can be built to predict risks before they become acute. The result is digital decision support tools that help municipalities and road authorities prioritize the right actions at the right time. In this way, resources can be used more efficiently – while making communities more resilient to future extreme weather.

How AI Is Used in Practice

In projects run within the framework of Mistra InfraMaint, advanced methods are being developed for condition assessment, forecasting, and decision support – with AI and machine learning at the core. Some of the technical building blocks include:

• Sensor and IoT data integration – measurements of moisture, water levels, deformation, and flows fed into AI models to detect patterns and anomalies.
• Predictive analytics and condition-based maintenance – forecasts that anticipate when and where interventions are needed, based on historical data, past failures, and real-time data.
• Multiple data sources and multimodal input – combinations of sensor data, geodata, satellite imagery, rainfall history, and hydraulic models to increase accuracy.
• AI roadmap for the water sector – an initiative to bridge the gap between available AI technology and actual use in municipal operations, with a focus on data quality, security levels, algorithm choices, and system integration.

By combining AI technology with proactive maintenance and gradual climate adaptation, we can create infrastructure that reduces the maintenance backlog, withstands extreme weather events, and is prepared for the future.

More information

Smart maintenance to help municipalities fix infrastructure

Mistra InfraMaint