Potholes, Machine Learning, and Compelling Content

Potholes, Machine Learning, and Compelling Content

It’s no secret that universities create a lot of content for dissemination on digital channels. Tweets, Facebook updates, Instagram Stories, LinkedIn updates, TikTok posts, and YouTube videos are just a few of the ways in which institutions share their stories.

Recently, I stumbled upon a rather interesting YouTube clip about a student-led project at Loyola Marymount University (LMU). While I’m always watching, reading, and curating, this particular video stood out from that day’s digital debris.

Engineering students at LMU were interested in how a new technology – machine learning – could be used to help detect potholes using camera footage in Los Angeles. It was a fascinating premise. With thousands of potholes, the state of L.A.’s roads are like that of any major city…cracked and pitted.

Using an open-source machine learning platform from Google, LMU’s students were able to train a model (an algorithm + data) to detect road cracks and potholes.

Produced by Google, the video that accompanied the original story is incredibly good. For anyone creating content at a university/college, this is a great how-to. It’s all about introducing a problem, sharing a novel way of fixing it, and creating a sense of purpose by way of pacing, sound, and camerawork.

Plus, if you’re a prospective student looking at engineering programs, how awesome is it to see students creating solutions to real-world problems as part of their student experience? This pothole video is both informative and engaging!



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