TLDR: Arizona State University researchers, led by Assistant Professor Hua Wei, are leveraging artificial intelligence to develop innovative solutions for mitigating extreme urban heat. Their work includes ‘Shaded Route Planning,’ an AI tool that helps pedestrians and cyclists find cooler routes in real-time, successfully piloted at the 2024 Paris Olympics. Complementing this is ‘DeepShade,’ a generative AI system that simulates and predicts shade patterns throughout the day and across seasons, providing crucial data for urban planners to design more resilient and comfortable cities. This research aims to bridge the gap between AI simulations and real-world impact, enhancing public health and well-being.
As cities worldwide grapple with escalating extreme heat events, innovative solutions are emerging from the intersection of urban planning and artificial intelligence. Researchers at Arizona State University (ASU), under the leadership of Assistant Professor Hua Wei, are pioneering AI-driven tools designed to harness the power of shade in combating rising urban temperatures. This initiative comes into sharp focus following events like the 2024 Paris Olympics, where athletes and spectators alike faced the daunting challenge of scorching heat, underscoring the critical need for effective heat mitigation strategies.
Shade, a seemingly simple element, proves to be a vital defense against intense heat, capable of lowering surface temperatures by 20 degrees Fahrenheit or more. However, accurately predicting and utilizing shade in complex urban environments has historically been a challenge. This is precisely where Wei and his team, based in the School of Computing and Augmented Intelligence within ASU’s Ira A. Fulton Schools of Engineering, are making significant strides.
Wei’s research encompasses two primary, complementary projects aimed at making shade information practical, accessible, and actionable for both individuals and urban planners.
Shaded Route Planning: Staying Cool on the Move
The first project, ‘Shaded Route Planning,’ is a human-centered AI tool designed for pedestrians and cyclists. Unlike traditional navigation apps that prioritize speed or distance, Wei’s system integrates shade as a crucial third factor. The technology works by analyzing satellite imagery to identify shade cast by buildings, trees, and other structures. This data is then overlaid onto maps of sidewalks and streets to calculate the shade coverage of various paths. Users are presented with multiple route options, allowing them to choose the fastest, shadiest, or a balanced combination of both.
This prototype demonstrated its effectiveness during the 2024 Paris Olympics, where it assisted visitors in navigating between venues via cooler routes. A demonstration highlighted how a shortest route might cut through sun-drenched boulevards (glowing orange on the map), while a slightly longer, shaded path would wind through tree-lined streets and alleys (appearing green). Wei emphasizes the impact, stating, “Even a small change in the route can make a big difference. It could mean fewer cases of heat exhaustion and a much more pleasant experience for thousands of travelers.”
DeepShade: Predicting Tomorrow’s Shadows Today
The second project, ‘DeepShade,’ addresses the broader urban planning challenge. This generative AI system predicts how shade patterns evolve in urban areas over time. Traditional satellite photos often fall short due to outdated information, low resolution, or inconsistent capture times, which can misrepresent actual shade conditions. DeepShade overcomes these limitations by generating realistic ‘what-if’ scenarios of shadows across different times of day and seasons. It leverages data on building structures and the sun’s position to simulate accurate shade distribution.
The AI model is trained to generate detailed shade maps on demand. For instance, a user could query the system to visualize an area’s shadows at 6 p.m. in July, and DeepShade would render the precise shadow locations. To ensure high accuracy, the model incorporates edge detection for sharp building outlines and employs contrastive learning to ensure the realistic evolution of shadows over time. In trials conducted across 12 diverse cities, including Beijing and Tempe, Arizona, DeepShade consistently outperformed other AI methods in generating accurate shade predictions.
This capability empowers city planners to make data-driven decisions. They can use DeepShade to evaluate the impact of proposed urban interventions, such as planting new rows of trees, adjusting building heights, or relocating bus stops, on pedestrian shade availability. This facilitates the creation of ‘cool corridors’ and public spaces designed to protect vulnerable populations from extreme heat.
AI for Social Good: Bridging the Simulation-to-Reality Gap
Hua Wei’s work is part of a growing portfolio that integrates advanced AI expertise with tangible societal benefits. His contributions to decision-making systems have garnered significant recognition, including a prestigious 2025 National Science Foundation (NSF) Faculty Early Career Development Program (CAREER) Award, support from Amazon, and collaborations with city governments.
Wei is particularly focused on addressing the ‘simulation-to-reality gap’ – the challenge where algorithms perform well in controlled simulated environments but struggle with the unpredictable complexities of the real world. Urban shade, influenced by dynamic factors like weather, seasons, and urban form, serves as an ideal testbed for this challenge.
He collaborates with other leading researchers, including Yezhou ‘YZ’ Yang, an associate professor of computer science and engineering in the Fulton Schools and a prominent figure in computer vision. Yang underscores the human-centric philosophy behind their work: “For me, the promise of AI has always been about more than algorithms. It’s about creating tools that touch people’s lives in meaningful ways. I’ve long believed that AI for social good means designing systems that don’t just push technology forward, but bring comfort, dignity and well-being to the communities we serve.”
Also Read:
- Singapore Businesses Achieve Significant Savings and Sustainability Gains Through AI and Digital Twin Adoption
- ASU Professor Vidya Chhabria Honored with Google Award for Pioneering AI in Chip Design
Ultimately, Wei’s projects aim to empower individuals and communities to adapt to a warming world. As extreme heat becomes a critical public health concern, tools like Shaded Route Planning and DeepShade offer practical glimpses into how AI can foster more resilient cities, improving the daily lives and health of their inhabitants.
