Flooding in metropolitan areas poses significant challenges, including disruption, displacement, financial costs, and even loss of life. City officials in a European city wanted to measure groundwater levels and sewer system status along a river.

They wanted to establish effective methods for controlling damage. They also wanted to ensure that evacuation notices were distributed promptly. The goal was to prevent flooding and mitigate its consequences. This study shows how our partner served as an AI consultant and used a model and data to help solve these challenges.

The first challenge faced by city officials was the need to accurately measure groundwater saturation and sewer system status in real time. Timely and precise data collection was crucial to implement proactive measures.

The complexity of the urban environment and the potential risks associated with flooding require a comprehensive solution.

The task was to create a model. The model could use data from sensors in groundwater and sewer systems. It could also use European weather forecasts. The purpose of the model was to predict areas at risk of flooding.

Our partner collaborated closely with city officials and their team of data scientists to develop an innovative predictive model. Using data from groundwater and sewer sensors, as well as European weather agencies, our partner accurately predicted flood-prone areas. With a rigorous approach, the team tested multiple data modeling algorithms to identify the highest accuracy model for deployment.

Thanks to the help of AI consulting services, the city now knows about flooding and can take action to prevent damage.

The predictive model developed by our partner has provided city officials with valuable insights to implement timely repair efforts and infrastructural improvements. By using data-driven approaches and advanced analytics, this city has significantly improved its flood control capabilities.