Smarter and cooler: How AI is rewriting the urban heat map

Jay Sadiq, CEO, FortyGuard

Abu Dhabi is seen as a hub for sustainable innovation. Even so, extreme heat remains an invisible threat. To fight it, forward-thinking real estate developers are turning to new tools, including those developed by FortyGuard, which uses artificial intelligence to measure, predict, and manage the city's temperatures.

FortyGuard has created a new class of large AI models that understand heat at a street-by-street, block-by-block level. The data collected by these Large Temperature Models (LTMs) has contributed to upgrades in surface materials, shading patterns, and vegetation placement – reducing the city’s ambient temperature by up to 5 degrees Celsius, decreasing dangerous-heat days by 25%, and improving its overall energy efficiency.

Preparing cities for extreme heat

Cities are on the frontlines of climate change, and traditional planning tools such as satellite data often fall short of predicting how heat behaves across complex urban environments.

A new generation of LTMs can simulate how temperature patterns evolve over hours and days, by using input from sensors, satellite imagery, and local environmental data to pinpoint hyper-local hot spots that traditional tools overlook.

When integrated into digital twins, these predictive models allow planners to visualize and manage thermal risks dynamically. Infrastructure decisions can then be guided not just by blueprints, but by continuously updated environmental intelligence. In effect, cities gain a living model of their climate that evolves as conditions change.

What's more, insights from FortyGuard's AI systems are being integrated into live sustainability dashboards, where they inform infrastructure design, pedestrian comfort strategies, and longer-term cooling policies. This is increasingly seen as an important step in climate technology: turning temperature intelligence into a foundational part of urban resilience.

Addressing heat equity through data

While technology can make cities cooler, it can also make them fairer. Hyper-local temperature mapping reveals how heat is often concentrated in communities with fewer resources, allowing policymakers to see where interventions are needed most urgently.

The importance of heat equity came into focus during Climate Week NYC, where FortyGuard partnered with Cornell Tech for the Health in Climate AI Hackathon. The winning team built Care Cast, a prototype app that uses neighborhood-level temperature feeds to send personalized alerts to people most vulnerable during periods of extreme heat.

Temperature Sense and the rise of physical AI

FortyGuard’s new Temperature Sense platform extends temperature intelligence beyond urban planning and into fields like robotics and automation. Integrated into our core AI system, it gives autonomous machines a new layer of environmental awareness. Temperature Sense combines real-time and predictive heat data from distributed sensors—including those on robots, drones, and fixed nodes. This creates a real-time city heat map and lets machines consider temperature as a factor when they perceive their surroundings and make decisions. By linking temperature data to robotic decision-making, Temperature Sense shows how climate intelligence can inform the next generation of machine behavior.

Looking ahead

FortyGuard’s vision is to make temperature intelligence an integral part of urban planning and operations, as essential as energy or mobility data. By merging AI, sensing, and real-world applications, the company is helping cities become both smarter and cooler, and reimagining how technology can help humanity adapt to heat. In a century defined by climate challenges, its work points to a future where cities can move beyond prediction and put meaningful, real-world cooling strategies into practice.