DRISHTI

AI-Driven Sustainability Operating System for Urban Water Systems (particularly the Yamuna)

Delhi contributes a majority of the Yamuna’s pollution despite covering only a small stretch of the river.
Current interventions are reactive, fragmented, and lack continuous monitoring.

DRISHTI is a lightweight, real-time decision support platform that helps authorities detect pollution early, predict risks, and take targeted action.

Instead of waiting for damage, we enable a monitor → predict → intervene strategy.

🚨 Problem

• Untreated sewage enters through multiple drains
• Monitoring is sparse and manual
• Illegal/ intermittent dumping goes unnoticed
• STPs are overloaded or bypassed
• Agencies lack coordinated, real-time data

Result:
By the time pollution is noticed, it’s already too late.

💡 Our Solution

We built a smart environmental monitoring system that:

• Continuously collects sensor data
• Detects anomalies automatically
• Simulates pollution risk
• Tracks issues
• Visualizes everything on one dashboard

It acts as the control center for river health.

🧠 System Flow

Sensors → Database → AI/ML → Backend API → Dashboard → Action

• Sensors send water quality data
• ML detects abnormal spikes
• Alerts are generated automatically
• Officials raise issues and take action
• Policies can be simulated before deployment

✨ Features

📊 Real-Time Monitoring

• Live sensor readings
• Time-series charts
• Water quality metrics (pH, DO, BOD, COD, turbidity, ammonia, temperature, conductivity)

🚨 Intelligent Alerts

• Automatic anomaly detection
• Severity-based warnings
• Location-specific flags

🔮 Prediction / Simulation Engine

• Short-term pollution forecasting
• Risk scoring for drains/segments

📝 Issue Tracker

• Raise issues
• Track resolution status

🗺 Interactive Dashboard

• Sensor map
• Alerts table
• Charts & analytics
• Authentication