UDAAN_AI is a unified, AI-powered GPS, drone, and air traffic intelligence platform designed to revolutionize how government and aviation agencies manage real-time logistics. By seamlessly integrating high-frequency telemetry data into a single ecosystem, the platform delivers real-time tracking, predictive analytics, and smart alerting. It bridges the gap between ground fleets and unmanned aerial vehicles (UAVs), providing next-generation transparency, efficiency, and automation for complex operational systems.
Utilizes trajectory and weather data to forecast flight path conflicts and air traffic congestion.
Visualizes active drones, air routes, and historical trail playbacks with timestamped coordinates via interactive maps.
Instantly detects boundary violations and unauthorized drones entering restricted no-fly zones using ML and computer vision.
Forecasts vehicle and drone component failures by analyzing telemetry data (e.g., battery levels, vibration metrics).
Capable of handling over 1 million GPS/UAV events per day while maintaining 99.99% uptime.
Features Role-Based Access Control (RBAC), JWT authentication, and multi-agency data isolation.
An Apache Kafka event streaming layer captures and buffers massive volumes of real-time GPS and telemetry data from ground fleets and UAVs.
Scalable Node.js and Express APIs process operational logic and interact with a MySQL database optimized by Drizzle ORM (achieving 70% faster query execution). Redis is used for caching active session and geospatial data.
Specialized ML models consume aggregated event data to perform predictive maintenance, anomaly detection, and collision predictions asynchronously.
A responsive Next.js frontend dynamically renders real-time tracking data using Leaflet and visually graphs analytics via Recharts, tailored precisely to the user's RBAC role.
Deploy lightweight anomaly detection and collision avoidance models directly onto drone hardware to reduce latency.
Dynamically overlay real-time meteorological data onto the dashboard to enable automated, safe rerouting of UAVs in transit.
Implement an autonomous dispatch engine that can automatically assign and route drones based on battery life, payload capacity, and proximity to an incident.