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Built atop its Smart Corridor infrastructure, the testbed as a service will allow researchers to access and test algorithms using data from the city’s connected urban environment.
Chattanooga is building a testbed as a service (TaaS) on top of its Smart Corridor infrastructure that will allow researchers to access and test algorithms using data from the city’s connected urban environment.
Funded by a $1.37 million grant from the National Science Foundation, “Smart Corridor+” includes both an urban road segment and a freeway segment, and will be assembled on Chattanooga’s citywide 10 gigabit/sec fiber-optic network.
Developed by the University of Tennessee at Chattanooga’s Center for Urban Informatics and Progress, the urban portion will be built on an existing downtown stretch of the city’s M.L. King Boulevard. The grant will allow CUIP to expand its coverage to a connected 2.5-mile portion of U.S. Route 27, including the on and off ramps.
Once the testbed is deployed, researchers will log into an online portal that will allow them to access continuously updated data, video, analysis and performance-measuring tools as well as other technologies as they develop ways to reduce pedestrian injuries and integrate autonomous and connected vehicles into urban settings. The proposed heterogeneous TaaS infrastructure will be programmable and able to deliver data on internet-of-things devices, diverse communications, edge computing and software services.
Research will focus on IoT applications addressing improved urban mobility, public safety, smart infrastructure, and human/device behavioral analysis that cannot be otherwise performed, according to the NSF grant summary.
Smart Corridor+ is also designed to “support multiple STEM education and research opportunities for all levels of students” in the Chattanooga area, with the goal of developing a competitive and diverse workforce for smart cities in the future.
CUIP was also recently recognized as a winner of IDC Government Insights’ fourth annual Smart Cities North America Awards for a project that uses LiDAR, the advanced imaging technology, to better understand pedestrian and vehicle interactions.
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