A Geospatial AI framework to ensure education continuity for IDP children in Sudan using ACLED and IOM open data.
# BridgeGuards4EducatedSudan
### Predictive Capacity Planning for Education Continuity in Sudan’s IDP Corridors
## 🔗 Project Artifacts & Live Links
* **Visual Artifact (Live Interactive Map):**
melisturker7.github.io
* **GitHub Repository:**
github.com
## 📝 Executive Summary
**BridgeGuards4EducatedSudan** is a strategic, data-driven initiative designed to secure education continuity for internally displaced children in conflict-affected Sudan. By triangulating open-source spatial data with predictive AI-powered risk analysis, the project maps "safe educational corridors" and pinpoints host-community schools facing severe demographic strain.
This predictive framework empowers the **Education Bridge Initiative (EBI)** to proactively allocate resources, prevent the collapse of local school infrastructures, and physically protect vulnerable children from systemic risks like forced recruitment and early marriage.
## 🎯 Core Objectives
* **Needs Assessment:** Correlate open-source conflict data (ACLED) with population movement metrics (IOM DTM) to dynamically isolate safe educational corridors.
* **Resource Prioritization:** Identify specific, operational facilities in low-risk, high-influx areas that are prime candidates for immediate infrastructure and financial backing.
* **Capacity Building & Co-Design:** Equipping EBI field teams with an intuitive, non-technical visual dashboard to rapidly deploy resource funding based on real-time field insights.
## 🛠️ Strategic Operational Methodology (EBI Framework)
Rather than acting as a static data-processing engine, this framework outlines a 4-stage strategic pipeline executed directly by and with EBI field teams:
1. **Field Methodology Validation:** EBI headquarters conducts localized validation workshops with field staff in receiving regions (e.g., Gedaref, Kassala) to cross-check mathematical models against ground-truth security reality …