Making cities safer and cleaner using micro-mobility and machine learning

The use of micro-mobility (e-bikes and scooters) has been growing significantly with a **projected market size of $500bn by 2030** (McKinsey 2021). The use of e-bikes and scooters, both shared and private, are already beginning to form a significant part of the urban transport network, with journeys doubling each consecutive year from 2019 to 2021\. **micro-mobility will be key to reducing traffic and achieving Net Zero by 2030**.

This growth in micro-mobility has not been without its challenges - in particular, **safety and parking compliance**. Several initial trials led to streets being cluttered and thoroughfares obstructed which in turn led to **clamp-downs on use and parking bay requirements being mandated.** Residents and businesses are unhappy. Visually impaired and blind people in particular have suffered with **charities calling for micro-mobility schemes to be terminated** (The Guardian 27/04/2022).

**Suppliers and local authorities still struggle to incentivise and police parking.** We know that we can do better. Captur and Unitary want to make micro-mobility work for everyone by providing suppliers, customers and local authorities with **AI-enabled technology to de-clutter the streets.** By building **safety verification algorithms** to automatically check the context of where vehicles are parked based on images taken by users post-ride, we will help to improve parking compliance, **make streets safer and help reduce friction.** Ultimately, this will contribute considerably to micro-mobility uptake and eventually **reduce car use and emissions in urban areas.**