Successful completion of iPredice III, with an intelligent real-time discharge control platform

The project to develop an advanced technological solution for the prediction and management of discharges in sanitation networks, iPredice III, has been successfully completed after overcoming important technical challenges and consolidating itself as a key tool for transforming urban water management. This initiative, coordinated by Smart City Cluster and with the participation of Grupo Energético Port Reial, ITelligent, Anukys and the Catalan Water Partnership, aims to improve the efficiency, resilience and sustainability of public and private services through the use of artificial intelligence (AI) and massive real-time data analysis.

The project, funded through the Grants for Innovative Business Groups (AEI) 2024 program, represents a new step around predictive maintenance and smart management of critical infrastructures. Previous phases of the project applied to photovoltaic installations and water supply networks made it possible to demonstrate the potential of these technologies to anticipate failures, detect anomalies or identify possible fraud and leaks. However, this new phase, focused on the sanitation system, has been challenging due to the complexity of predicting discharges into the environment, especially in changing contexts.

The main result has been an intelligent software platform that allows optimizing, monitoring and managing the discharge points of the sanitation network. The solution developed is based on the massive processing of data collected by sensors distributed in the field and processed using advanced artificial intelligence techniques. The algorithms compare historical data and current data, identifying significant patterns of behavior and detecting anomalies. In this way, it is possible to predict the probability of a spill and activate the necessary mechanisms to prevent it. In addition, the system can detect spills that have already occurred and determine their location and type, facilitating an effective and rapid response.

The development has been carried out in the municipality of Puerto Real (Cádiz), where most of the relief and discharge points are directly connected to the sea. This circumstance, added to phenomena such as saline intrusion due to the effect of the tides, has made the development of reliable prediction models particularly complex. Despite this, it has been successfully designed and implemented a system that allows critical events to be anticipated before they occur, acting proactively to avoid them or, if they occur, to characterise them and identify their origin.

The environmental and social impact of the project is significant: it reduces polluting discharges into the natural environment, protects vulnerable ecosystems, and improves the quality of the service. Its scalable and replicable design facilitates the transfer of the model to other territories and operators in the water cycle, both public and private.