Home News Artificial intelligence uses computer vision to keep scooter riders off the sidewalk

Artificial intelligence uses computer vision to keep scooter riders off the sidewalk

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Shared microtransit companies have been employing amazingly advanced technology to correct the city’s most annoying thing, riding on the sidewalk. Some companies, such as Bird, Neuron and Superpedestrian, have relied on ultra-precise GPS systems to determine if riders are behaving in a compliant manner. Other companies, such as Lime, have begun integrating camera-based computer vision systems that rely on artificial intelligence and machine learning to accurately detect a rider’s location.

The latter relies heavily on innovation from Drover AI, a Los Angeles-based startup that has tested and sold its attachable IoT modules to companies like Spin, Voi, Helbiz, Beam and Fenix to help operators improve scooter safety and, most importantly, win city permits.

Drover, which was founded in May 2020, closed a $5.4 million Series A round of funding on Wednesday. The startup will use the funding to continue developing the next-generation PathPilot, Drover’s IoT module that includes a camera and a computing system that analyzes visual data and sends commands directly to the scooters. Depending on the needs of the city, the scooter will make sounds to alert riders that they are traveling on the sidewalk or to slow them down.

Drover has a beta dashboard that shows trips broken down by infrastructure, the time each vehicle spent in each segment, and a summary of the entire fleet, where operators can see any vehicle deployed in the city, where the ride ends, where the AI rates stops, and a photo. drover also sells its data to cities and is exploring the use of distributed cameras moving around the city to build a suite of tools that could potentially provide a city-oriented dashboard showing information such as the condition of infrastructure or bike lane violations.

Drover has received interest from transportation agencies such as Transport for London, as well as insurance companies, who want access to this granular data to understand how the new mobility model is being used in infrastructure.

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