Design and analytics lab for urban artificial intelligence
Big data and computational algorithms have gradually become integrated with the built environment and within human’s daily lives, leading to a significant rise in Urban Artificial Intelligence (AI) research and applications. As such, the proposed Design & Analytics Lab for Urban AI (DAL) will develop digital twins and virtual/augmented reality (VR/AR) for multi-scaled simulations and scenarios for cities and regions. Further, such a platform will facilitate a collective understanding of existing urban infrastructure conditions and demonstrate innovative capabilities for how to increase urban resilience and efficacy beyond the technology integration. The DAL will develop and support free and open-source software tools for reproducible urban problem solving. We will provide contextualized modeling of cities to dynamically analyze real-time built environments and test existing and future scenarios for sustainable growth and climate action, involving eight founding members and 48 other members across nine colleges at TAMU, including Galveston campus, TEES, AgriLife Research, and TTI. We also aim to make the urban data FAIR (Findable, Accessible, Interoperable, and Reusable) through an AI-based data sharing platform.
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Built env. talk series: Justin Golbabai
Cultivating Community Through Planning & Design Summary This seminar will explore the challenges, opportunities, and best practices in building places that facilitate a sense of community and belonging. By discussing the relationship between community housing design and social connectedness, the seminar will deep dive into historical and current economic, technological, and urban planning trends that…
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Pilot Project 1: Smart Information Services
Pilot Project 1: Smart Information Services for Building Equitable Active Transportation Culture Problem description, novelty, and fit with thematic area: Walking and bicycling are the most popular means of getting a healthy dose of physical activities, which can bring numerous health benefits by reducing the risks of premature death, obesity, cardiovascular diseases, type II diabetes,…
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Built env. talk series: Dr. Dapeng Li
Towards a Computational Framework for Data-driven Wildfire Evacuation Planning in the Wildland-urban Interface Summary Wildfire poses a significant risk to the people living in the wildland-urban interface (WUI) in the American West. Computerized modeling of wildfire evacuation can help evacuation researchers and practitioners develop a better understanding of the complex wildfire evacuation process and improve…