Segway partners with Drover AI, Luna to bring computer vision to e-scooters

Segway partners with Drover AI, Luna to bring computer vision to e-scooters

Segway-Ninebot is partnering with Drover AI and Luna Systems — two startups that build computer vision technology to detect and correct improper electric scooter riding — to integrate their technologies into its AI-enabled e-scooters.

The partnerships, announced at the Micromobility Europe event in Amsterdam, are something of a pivot for Segway. This time last year, the scooter manufacturer launched an AI-powered scooter, the S90L, as the vertically integrated solution to scooter advanced rider assistance systems (ARAS). Rather than retrofitting third party hardware and software systems onto scooters, shared micromobility operators were offered a unified platform that included everything from the scooter itself to intelligent sensors to computer vision models.

Segway’s offering came as almost every major e-scooter operator began implementing some form of scooter ARAS that would prevent sidewalk riding in a bid to win over cities.

While Segway has managed to sell about 20,000 S90Ls to shared micromobility operators (mainly to Lyft), the company realized that it was spreading itself a bit thin, according to Tony Ho, Segway’s vice president of business development. Like many tech companies, Segway spent the last year re-strategizing and came away with a reaffirmed commitment to focus on core competencies. For Segway, that means building the hardware and working with partners to provide the software.

Los Angeles-based Drover and Dublin-based Luna have been leading the camera-focused scooter ARAS movement by testing and selling attachable IoT modules to companies like Spin, Voi, Helbiz, Beam, Fenix and others.

“When you deploy AI-based scooters in new cities, you need to train the computer vision system to learn the city, the pavements, the parking systems, the bike lanes,” Ho told TechCrunch. “So in every city where you deploy these scooters, there’s actually a huge amount of data you need to collect, and you also have to build the model in a way that’s suitable for each city.”

Ho said Segway didn’t have the brand bandwidth and resources to deal with that scale. Which is where Luna and Drover come in.

The non-exclusive partnerships with the startups will work in two ways. Customers that purchase S90L models — which are equipped with cameras, processors, CPU and GPU — can choose to implement either Drover’s or Luna’s scooter ARAS algorithms from the factory floor. Segway’s software will also be available, but it won’t be something the company focuses on or spends much time promoting.

“It’s almost like we’re building a mini app store for our scooters,” said Ho. “We’re opening the platform to developers or startups or operators, so they can basically take our vehicles, train them with their algorithm, and we become the computer on which they can run their algorithm.”

Operators that don’t already have S90L models but want scooter ARAS capability will have the option to retrofit Segway’s new modular AI system called Pilot Edge. Pilot Edge is essentially an add-on box with all of the necessary sensors for scooter ARAS, into which Drover or Luna’s tech can be integrated.

While Segway is open to any software that its operator customers choose, the company has a deal with Drover as its preferred software partner. Similarly, Drover will also recommend that customers purchase Segway’s hardware platform both for integrated vehicles and stand-alone computer vision modules.

For Drover and Luna, partnering with Segway means they no longer have to worry about building and deploying hardware, and can instead focus on software development and charging monthly fees for scooter ARAS. Which is good because, as Ho says, “hardware is hard.” It’s expensive to build and to store inventory that might not sell, and for small startups, dealing with supply chains can really cut into profits.

“It’s dirty work, but we can do it because we have huge scale,” said Ho. “So if we aggregate everybody’s demand, we can afford to do this at a bigger scale and therefore a lower cost.”

Source @TechCrunch

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