DrainGuard: AI-Powered Drainage Monitoring System

Admin Page
Langflow Agent to help
Complaint Register Page
Complaint Box

Inspiration

I was motivated by the challenges cities face with slow and manual drainage monitoring and maintenance. I wanted to create a smart, real-time system to improve response times and public safety using AI and simulated sensor data.

What it does

DrainGuard simulates real-time manhole sensor data and visualizes drainage infrastructure on Google Maps. It manages citizen complaints, prioritizes urgent issues, and uses an AI agent to answer natural language queries. The system automatically assigns cleaning vehicles, calculates routes, and animates their movement to complaint locations, streamlining maintenance operations.

How I built it

I developed a Node.js backend to simulate sensors and manage data, and built a frontend using Google Maps API for visualization. Vehicle routing and animation use Google Directions API. LangFlow AI was integrated to handle natural language queries, enabling smarter data interaction. The system updates every 15 seconds to simulate real-time monitoring.

Challenges I ran into

Simulating realistic sensor data, managing smooth vehicle animations, and integrating the AI agent for reliable query understanding were key challenges. Coordinating multiple asynchronous updates without conflicts also required careful design.

Accomplishments that we're proud of

Creating a fully functional, AI-powered real-time monitoring and complaint management system as a solo developer. Successfully integrating sensor simulation, AI-driven natural language queries, and automated vehicle dispatch into a seamless platform.

What I learned

I gained deep experience with Google Maps API, Node.js backend development, AI integration using LangFlow, and asynchronous programming for live updates and animations. I also learned the importance of designing modular, scalable system

What's next for DrainGuard: AI-Powered Drainage Monitoring System

I plan to expand DrainGuard to include monitoring for road and streetlight inspections, integrate real IoT sensors, add predictive analytics, and develop a mobile app for easier reporting and monitoring.