Funded Project
Start Date : 01 Jul 2026-01 Jul 2027
Aging bridge infrastructure represents one of Egypt’s most pressing engineering and economic challenges. With more than 44,928 bridges nationwide, the country depends heavily on a system in which inspection is still predominantly manual, subjective, and infrequent. As a result, hidden damage may accumulate between inspections, increasing the risk of failure and driving up maintenance costs. Current commercial Structural Health Monitoring (SHM) systems, although effective, remain prohibitively expensive for widespread deployment. This creates an urgent need for a low-cost, automated, and intelligent SHM solution. SmartBridges addresses this challenge by integrating three transformative technologies Internet of Things (IoT), Machine Learning (ML), and Bridge Information Modeling (BrIM) into a unified framework. The project adopts a “Sim-to-Real” strategy to address the data scarcity challenge commonly encountered in civil engineering applications. A detailed Finite Element Model (FEM) will be used as a "Data Factory" to simulate thousands of damage scenarios, generating a synthetic dataset to train a Deep Learning model. This pre-trained model will then be deployed via a custom-designed, low-cost Wireless Sensor Network (WSN) installed on the Alternative Bridge for Aswan Reservoir. Real-time sensor data (strain, acceleration, temperature) will be continuously streamed to a BrIM-based Digital Twin, providing an intuitive, 3D visualization of bridge behavior for asset managers.