Project Mission

Built to tackle urban resilience.

The Problem

Every monsoon, Delhi faces severe urban flooding due to clogged drainage and unpredictable rainfall distribution. Authorities often lack real-time, ward-level visibility to deploy resources effectively.


Our Solution

Pravah calculates a dynamic Risk Score for every ward by combining live rainfall data, infrastructure capacity, and citizen complaints. This allows the administration to move from "Reactive" to "Predictive" management.

How It Works

The Logic Behind the Risk Engine

1. Data Ingestion

We aggregate rainfall (mm) and drainage capacity (%) for all 250 wards.

2. Weighted Algorithm

Score = (Drainage × 0.5) + (Rain × 0.3) + (Complaints × 0.2)

3. Action

Admins get a prioritized list of High-Risk zones to deploy pumps immediately.

Technology Stack

FastAPI (Python)
Vanilla JS
Leaflet.js
Render Cloud
Vercel

Meet the Builders

Prabhat Bhatia

Prabhat Bhatia

Full Stack Developer

Backend Architecture, API Design, & Deployment Strategy.

Suhani Yadav

Suhani Yadav

Frontend Developer

UI/UX Design, Map Visualizations, and Dashboard Logic.