Dutch-French vehicle hire startup Dott is using the internet of things (IoT) to manage its fleet of electric scooters and bikes in major cities across Europe.
According to Kristina Gibson, chief product officer at Dott, responsible for product engineering and user design teams at the company, the easiest way to think about its service is “as a connected system, which is headquartered in Amsterdam”.
“We have a mobile application that you can download on the Google Play and Apple App Store, and you can use that to hire one of our vehicles to move easily around a city,” she says. “Each vehicle has technology that communicates back to systems on the back end to make sure you’re having a safe ride.”
Dott has 50,000 shared electric scooters and bikes, which are charged per minute on top of a small unlock fee. In most cities, it offers scooters or bikes, but not both. In a few cities – such as Brussels, Milan and Rome – both options are available.
“Our goal for micro-mobility is to have high frequency of use, and that is happening,” says Gibson. “Those who enjoy the Dott service ride frequently throughout the month. To do so affordably, they opt for a monthly pass.”
Managing the fleet through IoT
Each vehicle has an internet of things system, which includes components that read vehicle states and communicate that information to the back-end platform. If the battery is low, that information is sent back to the operations team, which goes out to the vehicle and swaps the battery on its daily runs.
Each scooter or bike has technology that communicates back to systems on the back end to make sure you’re having a safe ride Kristina Gibson, Dott
On-vehicle GPS allows app users to locate the nearest e-bike or e-scooter when and where they need one. Once they’re riding, the GPS shows users where they are and lets Dott know where each vehicle is and how fast it’s travelling.
“In parts of a city, like shopping streets where there are a lot of pedestrians, we are required to lower the speed limit to help create a safe environment for both pedestrians and riders,” says Gibson. “When we know the vehicle has entered a geofenced area, we communicate to the user in the mobile application that this is a low-speed zone, both on the map and through messaging. We also prevent the vehicle from going over the limit.”
While existing users can find a ride through the app, others might notice an e-bike or e-scooter on the street and decide to try it out. Each vehicle has a QR code people can scan with their phone, which redirects them to the app store where they can download the app and register on the spot. Dott guides new users through that process, explaining how to safely ride the vehicle and informing them of local city rules and regulations. “And then they’re on their way,” says Gibson.
Users can also send information back to Dott through the app. For example, they might report that the seat is not positioned correctly on an e-bike. The operations team can locate vehicles that need repairs and bring them back to the warehouse for remedial work.
Local operations teams know the cities very well and have an idea of where there will be more requests for rides and what times of year are busiest. Dott complements that information with data it collects from rides and through other means. Its data science team takes all that information and builds algorithms to work out the right balance of supply and demand for each location in each city.
“Our goal is to make sure that when riders want to ride, there’s a vehicle available for them,” says Gibson.
Encouraging good rider behaviour
Dott has to ensure the vehicles don’t violate local laws, which means keeping to local speed limits and respecting areas that cities consider off-limits. For example, a city might not want the vehicles going through certain parks.
Another behaviour cities want to avoid is riders going on pavements, which disturbs pedestrians. To address this, Dott conducted a study with Luna Systems, a computer vision firm that installed artificial intelligence (AI)-powered cameras on Dott’s e-scooters to follow trips in Brussels, Grenoble and Tel Aviv. What it found was that in 71% of the cases where riders went on the pavement, it was because of road conditions. To minimise the problem in the other 29% of the cases, Dott now sends signals to users through the app when they ride on the pavement and continues to educate riders on correct behaviour.
The IoT system on the bike can also determine when a vehicle has been out too long. “We know how long a ride is running and if it’s in a normal state,” says Gibson. “We can detect if a vehicle is not moving and for how long. Based on business logic we can decide to terminate the ride, but we only do so when we have signals that it’s not moving, because you can imagine if you were riding a bike and suddenly it stops, it would create an unsafe situation.”
Dott has started experimenting with artificial intelligence (AI) to improve customer service. With the help of third-party partners, it developed a pilot project to provide quick answers to questions from users. For example, AI-based photo scanning helps users find the right parking spot. Customers who have doubts about where to leave a vehicle can send in a picture, and a computer vision algorithm responds.
Thanks to IoT and mobile apps, Dott can provide an environmentally friendly and convenient micro-mobility service – and make a nice profit along the way.