Hardware overview for shared micro-mobility (1/3): scooters, e-bikes and mopeds

Running a rental or sharing business today means delivering a smooth, digital-first experience. Whether you rent cars, bikes, scooters or other vehicles – users expect to book online, pay, verify identity if needed, unlock a vehicle, and ride or drive without extra friction. 

To make that happen reliably, you need good vehicle rental software or platform backing your service. Below are some successful examples of apps and platforms that show how this works and what is possible.

Donkey Republic 

Operates in several European cities offering shared bikes and e‑bikes. Users find a bike in the app, unlock it with a smartphone, ride, then park at a designated drop‑off spot and end the rental. Pay‑as‑you‑go, daily rates or memberships are all handled via the app. 

MOBY Bikes 

Targets electric bicycles and e‑cargo bikes across certain regions, with a “tap‑and‑ride” system that uses its proprietary app for booking, unlocking, and rental management. The platform supports mixed-use fleets (shared bikes, cargo bikes, delivery fleet, even B2B rentals), which illustrates flexibility – useful for operators exploring different business models beyond simple consumer rentals. 

Forest

It is a dockless e‑bike sharing operator in London. It runs a large fleet and offers bike‑sharing through a mobile app. The service demonstrates how a relatively simple, dockless rental model can scale at urban level using app‑based rentals, unlocking, and flexible parking. 

These examples show how micromobility‑focused services already rely on booking, payment, unlocking and fleet management tech – the same core capabilities needed by any modern vehicle rental business.

What makes these apps work – and what to borrow from them

From these operators you can observe several useful traits that a good rental/sharing software should provide:

• Seamless user journey: crate account in seconds → search → book → unlock → ride/drive → return. Users don’t need paper contracts or to meet staff to get a vehicle.‍
• Flexible pricing & rental models: per-minute, hourly, daily, subscription, memberships – enables both occasional users and frequent commuters.‍
• Smart access control and vehicle tracking: unlocking via app or smart lock, GPS tracking, drop‑off in defined zones or docking stations, helps maintain order, reduce theft, and support dockless models.‍
• Support for different vehicle types: from bikes to e‑bikes and cargo bikes – showing that underlying software can be agnostic to vehicle type, useful if you plan a mixed fleet.‍
• Scalable fleet operations and maintenance: availability updates, booking history, maintenance logs, geofencing or parking zones – these help manage many vehicles across zones without chaos.

These are exactly the kinds of features you need when you move from small‑scale operation to proper fleet business.

Why to choose ATOM Mobility

If you plan to just test the market or to operate a larger and more complex fleet - multiple vehicle types, multiple cities, or advanced operational requirements - a full-stack platform like ATOM Mobility becomes essential.

ATOM Mobility is designed for operators who need full control over the entire mobility operation: booking flows, unlocking logic, payments, KYC/ID verification, backend administration, fleet analytics, dynamic pricing, and multi-modal rentals across cars, scooters, bikes, and more.

The platform provides a unified backend that supports cars, scooters, e-bikes, mopeds, and additional vehicle types within a single system. Operators can manage bookings, payments, users, smart locks or connected vehicles, fleet health, and city-level scaling without fragmenting their tech stack as the business grows.

This approach offers far greater flexibility than single-vehicle or bike-only solutions and removes the need to migrate systems when expanding into new vehicle categories or markets. Check out the full service here.

How to choose: when to use franchising vs full platform

Join a franchising when you:

- prefer operating under an established brand
- value a clear operational playbook and central support
- want simpler marketing thanks to brand recognition
- are comfortable with limited control over technology and product decisions
- accept franchise fees or revenue sharing in exchange for convenience
- don’t need heavy customization or experimentation

Use a full platform (like ATOM Mobility) when you:

- aim to manage a larger, mixed fleet (cars, scooters, bikes, e-bikes)
- need full backend control (admin, analytics, pricing, reporting)
- require payments, KYC/ID verification, and automation built in
- want freedom to customize booking flows, pricing, and partnerships
- plan to scale across cities or add new vehicle types over time
- prioritise brand ownership and customer relationship control
- want no revenue sharing or franchise fees

There isn’t a one‑size‑fits‑all solution 

For simple bike or e-bike fleets, the technology barrier is already low. Joining a franchise can be a fast way to get operations running with minimal setup.

However, operators with long-term ambitions - expanding into multiple vehicle types, scaling across locations, or maintaining consistent service quality - typically outgrow narrow tools. In those cases, a full-stack platform like ATOM Mobility offers the flexibility and control needed to support growth without rebuilding the tech foundation later.

Some operators start small and migrate as complexity increases. Others choose to build on a full platform from day one to avoid future transitions. The right choice depends on how clearly you define your growth path, desired level of control, and operational complexity from the start.

Artificial intelligence is no longer just a trend in mobility. For modern vehicle sharing and rental services, AI is already solving real operational problems and unlocking new ways to grow. At ATOM Mobility, several AI-powered features have already been implemented into live products and tested by operators across Europe.

This article shares three real-world AI use cases that are already helping operators reduce manual work, improve asset control, and better match vehicle availability to demand. 

1. Vision AI: Camera-based parking control for micromobility

Micromobility parking continues to be a challenge in cities where dockless vehicles can end up blocking sidewalks, crossings or entrances. Manual checks are costly and often too slow to solve the problem in real time.

ATOM Mobility now uses computer vision to solve this. With Vision AI, riders take a photo when ending their ride. The system analyses the image using a neural network to understand if the vehicle is parked correctly – within a designated zone and without creating obstructions. If not, the app notifies the user and prevents trip completion until the parking is corrected.Each parking photo is automatically tagged as “Good parking”, “Improvable parking” (the user receives guidance on how to improve the parking), or “Bad parking” (the user is asked to re-park).

If the user fails to submit a “Good parking” photo after several attempts, the system will accept the photo with its current tag (“Improvable” or “Bad parking”) and flag it in the dashboard for further customer support review.

This solution has been live with many operators already. It helps reduce complaints, improve compliance with city regulations, and lowers the need for manual reviews.

2. Precision AI: Detecting car rental damages with cameras and machine learning

In traditional car rental, damage inspection is slow, manual, and often inconsistent. With self-service rentals becoming more popular, operators need a smarter and faster way to verify a vehicle’s condition between trips.

ATOM Mobility has integrated AI-powered damage detection using computer vision. Customers scan the vehicle at pick-up and drop-off. The app compares images and flags scratches, dents, or other visible damage with high accuracy. This allows operators to quickly assess responsibility and reduce disputes.

The system helps protect the fleet, lowers repair costs, and adds trust for both users and operators. It’s especially useful for car sharing and self-service rental models where physical handovers are skipped.

3. Prediction AI: Forecasting demand and automating vehicle relocation

One of the biggest cost factors in shared mobility is rebalancing the fleet. If scooters or cars are idle in the wrong location, revenue is lost. At the same time, relocating vehicles manually is expensive and not always efficient.

ATOM’s AI models use historical trip data, usage trends and contextual signals (such as day of the week or weather) to forecast demand and suggest the best relocation zones. This gives operators a map of where and when to move vehicles – improving utilisation and saving time.

The system can even be combined with automated relocation logic, where users are incentivised to park in high-demand areas. This shifts part of the rebalancing cost from operators to riders and keeps the fleet productive.

Why this matters now

AI tools are finally reaching the stage where they can operate reliably, even in complex environments like cities. These examples are not abstract ideas or lab tests. They’re active features helping ourcustomers run leaner, smarter fleets today.

For micromobility operators, Vision AI reduces complaints and ensures regulatory compliance. For car rental providers, Precision AI saves hours of staff time and improves trust. And for both, Prediction AI improves margins by making sure vehicles are where users need them.

What’s up next?

These are just the first steps. AI in mobility will continue to expand with smarter pricing engines, voice-based support, predictive maintenance, and more. But the examples above already prove that even small AI integrations can bring major improvements.

At ATOM Mobility, we continue building these tools directly into our platform so that operators don’t need to develop them in-house. If you want to see how these AI-powered features work in action, get in touch with our team.

AI in shared mobility is not about replacing people. It’s about giving operators better tools to run faster, smarter, and more efficient services.