Founders’ Honors

Universidad de las Fuerzas Armadas ESPE is pioneering an intelligent leak-management system for the underground potable water network serving more than 18,500 people in Sangolquí, Ecuador. The university faced a complex engineering challenge: with very few historical records of verified pipeline failures, traditional AI models lacked the labeled training data needed to detect underground leaks. Furthermore, the engineering team needed to connect real-time hydraulic simulations with AI while contending with limited sensor connectivity below ground. This multi-layered workflow was not achievable by using conventional, disconnected hydraulic modeling tools.

The team deployed OpenFlows Water and OpenFlows Sewer within the Bentley iTwin ecosystem, using live sensor feeds to calibrate a high-fidelity digital twin of the campus pipe network. They then linked the calibrated hydraulic twin to an autoencoder AI trained to instantly detect subtle flow and pressure anomalies that signal hidden subterranean leaks. Automating model calibration reduced hydraulic engineering time by 76% and eliminated the need for three disruptive physical field campaigns. The proposed digital workflow is projected to cut exploratory inspection excavations by 40%.