AI for Sustainable Cities

HydraX Rainwater Intelligence for London

HydraX is a sustainability intelligence platform focused on maximizing London’s rainwater potential. By combining rooftop geometry with predictive rainfall analytics, HydraX estimates how much rainwater can be captured by each household — helping residents, planners, and policymakers understand their water-saving potential. The tool supports long-term feasibility planning for installing rooftop water reclamation systems, turning rainfall into a practical, sustainable water source for the city.

Aligned with SDG 6, 11 & 13 • Designed for planners, sustainability teams & citizens.

Powered by open environmental datasets, rooftop detection and geospatial analytics.

About HydraX

Turning London's rooftops into a hidden water reservoir

Urban areas lose millions of litres of clean rainwater every year due to inefficient drainage and the absence of localized collection systems. HydraX empowers city planners, sustainability teams, and homeowners to quantify rooftop rainwater potential using predictive rainfall analytics — providing clear insights before investing in large-scale infrastructure.

Data-driven insight for real decisions

HydraX uses open-source rainfall data, building footprints and rooftop area estimates to model how much water can be captured across London. The result is a geospatial layer that highlights:

  • How much rainwater can be harvested city-wide or by address.
  • How much water collection potential your rooftop has.
  • How rainfall patterns and urban density affect sustainable water planning.

Why it matters

By revealing untapped rainwater resources, HydraX supports:

  • Communities gaining better access to clean water by reducing dependence on overburdened municipal water systems. (SDG 6)
  • The Development of resilient, water-smart cities that can better handle flooding and drought conditions. (SDG 11)
  • Cities adapting to the impacts of climate change through solutions that reduce urban flooding from poor drainage systems. (SDG 13)

The Problem

Millions of litres of rainwater wasted. Streets still flood.

London receives significant annual rainfall, yet most of it rushes straight into drains. Families face water stress, cities face overwhelmed drainage systems, and home owners lack a clear map of where water can be stored at the building scale.

Without a clear view of rooftop potential, rainwater harvesting decisions are slow, fragmented and reactive. HydraX replaces guesswork with actionable geospatial intelligence that supports Clean Water (SDG 6), Sustainable Cities (SDG 11) and Climate Action (SDG 13).

Our Solution

HydraX: AI + geospatial analytics for rooftop rainwater

HydraX layers rainfall data, rooftop geometry and urban characteristics into a single interactive map, showing where the city can store water before it becomes stormwater.

Step 1 · Ingest

Rooftop and Area detection.

HydraX identifies rooftop footprints at a specified address using open geospatial datasets. It calculates the total rooftop coverage area (in square meters) to estimate potential water collection surfaces.

Step 2 · Analyse

Predict rainfall

Using historical rainfall data and a 20-year projection model, HydraX predicts future precipitation trends. The system estimates expected rainfall volume per square meter of rooftop and computes potential harvestable water for each building as well as for the city of London as a whole.

Step 3 · Visualize

Rainwater impact simulation

The results are visualized on an interactive city-scale map, showing water capture potential, stormwater reduction, and household support capacity for different districts across London city.

Impact

From wasted rainfall to resilient, water-smart neighbourhoods

HydraX helps families gain more access to clean water, supports cities in reducing stormwater waste, and informs investments in green infrastructure.

Clean Water Access

Estimate how many households could be supported with rooftop rainwater storage during dry periods.

Stormwater Relief

Visualize reductions in runoff volume for extreme rainfall scenarios at borough or city scale.

Green Coverage

Identify rooftops where green roofs + harvesting systems can boost canopy and cooling.

Investment Planning

Prioritize districts where every litre captured delivers the greatest climate and social benefit.

Prototype Impact Scenario

Example scenario if high-potential rooftops installed harvesting systems:

Rainwater captured

Runoff reduction

Households supported

These values are placeholders for the datathon prototype and can be updated with real model outputs.

Meet The Team

We’re a team of computer and data scientists building AI tools that drive real-world impact — one breakthrough at a time.

Frontend & Visualization Engineer

Sanad Nassar

Frontend development and UI integration for rainfall modeling, rooftop potential, and spatial analysis tools.

ReactHTMLCSSJavaScriptNext.jsGitHub

Full-stack Engineer

Shaun Malhotra

Backend APIs, integration with mapping libraries. Git version control and collaborative workflow management.

PythonFastAPIFlaskNext.jsGitHub

AI Engineer

Ethan Wang

Model training, data preprocessing, and API deployment for rainfall and spatial prediction systems.

PythonFastAPIFlaskNext.jsGitHub

Data Engineer

Lopey Soleye

Data collection, cleaning, and structuring. Development of data pipelines and preparation of datasets for AI analysis.

PythonSQLiteFlaskNext.jsGitHub

Database Architect

Hana

Implements spatial indexing and efficient data retrieval for large-scale building and rainfall datasets.

PythonSQLiteFlaskNext.jsGitHub