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Sustainability / Google Cloud / AI for Good

Althil - Urban Thermal Comfort Decision-Support Platform

Designing cooler cities, one shaded street at a time.

A decision-support platform for improving urban thermal comfort by helping planners identify effective shade canopy locations based on sun paths, heat exposure, and location data.

Context

Developed during the Intelligent Planet Hackathon hosted by KFUPM in collaboration with Google Cloud.

Problem

Urban planners need better tools to understand heat exposure and identify where shade canopies can improve thermal comfort over time. Traditional planning may not fully account for sun paths, location data, and changing heat exposure patterns.

Solution

Althil helps planners identify where shade canopies would be most effective based on sun paths, heat exposure, and location data.

My Role

Backend Developer & Cloud Architecture Contributor

Impact

Althil supports sustainable cooling strategies by helping cities improve comfort without increasing energy consumption.

My role

Backend Developer & Cloud Architecture Contributor

Responsibilities focused on shaping the solution, connecting technical choices to user needs, and helping move the idea into a coherent working concept.

Contributed to backend development
Supported the cloud architecture direction
Integrated analysis services across the platform
Worked with the team under hackathon constraints
Helped connect location data, analysis, and explainable insights

Technical architecture

How the solution was structured

Each case study is grounded in a practical technical approach, from local AI knowledge design to cloud-native analysis and behavioral analytics.

Source

Location & sun data

01
Processing

BigQuery analysis

02
Intelligence

Vertex AI scoring

03
Experience

Shade recommendation

04

Engineering notes

Google Cloud Run for scalable backend services
BigQuery for analytical data processing
Cloud Storage for reports and assets
Vertex AI for intelligent analysis and recommendations
Map-based interaction and heat visualization
Conversational agent for explaining insights

Decisions

The calls that shaped it

The choices that mattered most — and the thinking behind each one.

01

Cloud-native on Google Cloud

Built on Cloud Run, BigQuery, and Vertex AI so the analysis could scale and stay maintainable — and so the team could move fast inside hackathon time limits.

02

Explain, don't just compute

Added a conversational layer so planners get the reasoning behind each shade recommendation, not just a score they have to trust blindly.

Key features

What the project enables

Interactive map-based planning
Heat exposure visualization
Shade canopy recommendation support
AI-powered analysis
Report and asset storage
Conversational explanation layer

Impact

Applied value

Althil supports sustainable cooling strategies by helping cities improve comfort without increasing energy consumption.

After shipping
This project strengthened experience in cloud-native design, data-driven decision-making, and cross-functional collaboration under real constraints.

Inside the product

A look at how it works

A handcrafted preview of the experience — drawn to show the idea, not a stock screenshot.

AlthilThermal comfort

Google Cloud

Run · BigQuery · Vertex AI

KFUPM × GC

Intelligent Planet Hackathon

Cooling, not cost

Comfort without more energy

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