AI for Sustainability
How AI Can Support Smarter Urban Planning
Data, cloud services, and explainable AI can help cities make more informed decisions about thermal comfort.
May 28, 20266 min readFor Cities, Students, Decision-makers
Cities face practical questions that sit at the intersection of data, environment, and human experience. Where would shade improve pedestrian comfort most? How can planners compare locations over time? AI is useful here when it supports a decision rather than pretending to replace the planner.
Urban comfort is a decision problem
Heat exposure is not uniform. Different locations experience different patterns based on time, sun paths, surrounding structures, and how people move through a place. Planning better shade requires a view that is both spatial and analytical.
What Althil explored
Althil was developed during the KFUPM x Google Cloud Intelligent Planet Hackathon. The platform concept helps planners identify effective shade canopy locations using heat exposure, sun paths, location data, visual analysis, and conversational explanations.
- Maps for place-based interaction.
- Heat visualization for clearer planning conversations.
- Cloud analysis for handling structured location data.
- AI-supported recommendations that remain explainable to users.
Cloud AI can connect the layers
A cloud-native architecture can connect analytics, reports, storage, visualization, and an explanation layer. In Althil, services such as Cloud Run, BigQuery, Cloud Storage, and Vertex AI shaped the proposed technical direction.
AI should make the decision easier to inspect
The most valuable planning systems do not hide behind a score. They help users understand why a location may matter, compare scenarios, and bring human judgment into the final decision.