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The Michigan Institute for Data Science at the University of Michigan will partner with Microsoft and the city of Detroit to expand digital equality by improving broadband internet access and affordability in underserved areas across the Motor City.

As the first academic partner in Microsoft’s Airband Initiative to expand digital equality in metropolitan areas, MIDAS will assist with comprehensive data acquisition to improve data quality and the application of statistical and machine learning models to generate granular indicators of digital access needs.

“Partnering with MIDAS brings deep rigor to guide evidence-based policies, actions and learnings to address the digital divide in Detroit, grounded in an understanding of local context,” said Vickie Robinson, general manager of the Airband Initiative. “These insights will be very valuable as we seek to increase access to affordable broadband, low-cost devices, and digital skilling resources in Detroit, and potentially establish replicable data tools that can be adapted for other places.”

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A UM-Dearborn professor has developed a bike-mounted lidar system that could help researchers and engineers design new strategies for safer streets.

Normally when one of our stories mentions lidar — the laser-powered locating technology that’s similar to radar or sonar — we’re talking about autonomous vehicle navigation. But UM-Dearborn Assistant Professor Fred Feng, who studies non-motorized mobility safety issues, recently developed an application for lidar that could be a big help for those working in the active mobility space.

In the name of research, Feng has been strapping various sensors to bicycles and vehicles for years, and to date, that’s typically meant GPS and video cameras. They all work pretty well, especially if you’re looking to capture intimate observational data about bicycle riders’ real-world experiences. But Feng says this technology cocktail has a few important limitations. For example, if you want to take a detailed look at “overtaking” — a common high-risk scenario in which a driver passes a cyclist on the road — camera systems can’t really give you an accurate measurement of how close the car got to the cyclist. And even if you’ve equipped your bike with a proximity sensor, it can only record a single measurement at the moment the car temporarily draws even with the cyclist.

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On Friday, July 16, 2021 at 10:00 AM ET, University of Michigan Professor Shobita Parthasarathy to testify before the House Science Committee: Fostering Equity in Energy Innovation.

Watch the testimony here