1. Predictive Maintenance
- AI-driven models analyze data from IoT devices and SCADA systems to predict equipment failures before they occur.
Reduces downtime and optimizes maintenance schedules.
2. Water Management Optimization
- ML algorithms forecast water demand based on historical data and usage patterns.
- Ensures efficient distribution and minimizes wastage.
3. Smart Metering Analytics
- AI enhances the analysis of data from AMR and smart meters, identifying anomalies like leaks or unauthorized usage.
- Provides actionable insights for better resource management.
4. Solid Waste Management
- AI-powered systems optimize waste collection routes, reducing fuel consumption and operational costs.
- ML predicts waste generation trends to improve planning and resource allocation.
5. Energy Efficiency in Substations
- AI algorithms monitor and optimize energy distribution in real-time.
- Identifies inefficiencies and suggests corrective measures to improve performance.
6. Vehicle Tracking and Routing
- AI-powered systems optimize vehicle routes for milk, water, and oil delivery, reducing travel time and costs.
- ML models predict maintenance needs based on vehicle usage data.
7. Flood and Leak Detection
- AI systems in water pipelines and reservoirs detect leaks and potential flood scenarios early.
- Real-time alerts enable immediate action.
8. Smart City Management
- AI integrates data from diverse urban systems like water, waste, and traffic to provide a unified management solution.
- Enhances decision-making with predictive analytics and scenario simulations.
9. Oxygen Monitoring Systems
- AI ensures optimal oxygen levels in industrial setups by analyzing real-time sensor data.
- ML algorithms identify patterns for precise adjustments.
10. Agriculture and Irrigation
- AI optimizes water usage in irrigation systems, improving crop yield while conserving resources.
- ML predicts weather patterns and water requirements for proactive irrigation management.
