Aging infrastructure and delayed maintenance responses cost global economies billions annually. Traditional inspection methods are reactive and labor-intensive. The IGI Project proposes an intelligent, automated system that fuses geospatial data (GIS) with live sensor streams to detect anomalies—such as structural stress, thermal leaks, or subsidence—before failure occurs.
For collaboration or access to the technical whitepaper, please contact the project lead at [name@institution.edu] or visit igiproject.org/dashboard (demo sandbox available). Let me know which “IGI” you meant, and I can tailor the write-up even further. igi project
| Phase | Focus | Deliverable | |-------|-------|--------------| | 1 | Data Integration | Unified API for ingressing satellite, drone, and fixed sensor data | | 2 | Anomaly Detection | ML model (CNN + LSTM) for pattern recognition in geospatial time-series | | 3 | Alert Dashboard | Real-time 3D visualization (CesiumJS) with risk-scored alerts | | 4 | Pilot Deployment | Live test on 10 km of metro rail track and 3 electrical substations | For collaboration or access to the technical whitepaper,