AI-Driven Resilience for Public Sector Networks
Problem: Public sector networks in underserved regions face crippling energy costs (40-60% of budgets), frequent outages (15-20% downtime), and reactive maintenance models that drain resources. Solution: GridGuardians leverages AI to: • Predict equipment failures 72hrs in advance using Prophet time-series forecasting • Reduce energy waste by 22% via anomaly detection (Isolation Forest) • Prioritize repairs using cost-benefit simulations (Random Forest regression) Target Audience: Governments, NGOs, and institutions managing connectivity for: • Rural schools (Giga partnership focus) • Healthcare facilities (HealthSites integration) • Low-income urban communities Unique Features: • Offline-first design for low-bandwidth areas • Open-source core with federated learning • Carbon credit reporting for sustainability grants
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