We leverage computer vision to solve the core safety challenges of micromobility
Sidewalk riding, collisions and disorderly parking present challenges to the growth and scale of micromobility. Luna’s smart camera technology enables operators and cities to understand how riders engage with vehicles and the ability to proactively reduce errant behavior in real time. Our vision data also provides actionable insights for a variety of smart city needs.
Urban Mobility Safety Platform
Sidewalk riding DETECTION
Luna's computer vision AI enables road/sidewalk/cycle lane recognition. Once a rider mounts such a restricted area, Luna emits a beep to encourage the rider to move to a more suitable area. Alternatively, the scooter can also be slowed or stopped depending on operator requirements, providing them with much greater control over where their units are being ridden.
PARKING COMPLIANCE
Luna also provides a variety of AI-powered parking solutions to cater for different city environments and regulations.
Pedestrian & OBSTACLE DETECTION
Luna-enabled vehicles detect pedestrians and obstacles, emitting a beep to alert pedestrians once they enter critical distance. Again, the operator, in partnership with the host city, can select the mode of action in this situation - e.g. decelerating, or bringing the scooter to a safe stop to avoid collision. Luna provides much greater control to cities and operators in how they can react to such situations.
CROWDSourced vision data
Luna enables operators and cities to turn shared micromobility fleets into mobile sensor networks, capable of detecting, monitoring and reporting key parameters - from lane blockages to heat mapping of sidewalk riding, and from critical infrastructure monitoring to road condition surveys.
SOLVING MICROMOBILITY CHALLENGES
OUR TECHNOLOGY
SIDEWALK DETECTION
Is the scooter being ridden on a road, or on a footpath/sidewalk? Should the rider be warned?
PEDESTRIAN/OBJECT DETECTION
How many pedestrians are in the scooters path? Should the rider and/or pedestrians be alerted?
AI/Computer Vision
We trust our eyes to find a location more than we trust the GPS blue dot on our screen. Luna computer vision/AI technology is far more accurate than the standard GNSS technology being used in the micromobility industry. Operators and municipalities simply cannot be sure that its rental fleet can be governed correctly by GNSS.
Operators globally are scrambling to improve the accuracy of the positioning of their fleets, and are experimenting with higher accuracy GNSS, new positioning algorithms (dead reckoning), as well as ‘sensor fusion’ methods to collect multiple data points from other sensors on the scooter, in order to more accurately ‘guesstimate’ its position.
These improvements still fall down when compared to computer vision/AI, because they are ultimately based on legacy GPS, which is an inherently inaccurate technology for a variety of reasons. Most shared scooter operators are starting to realise this, and more importantly most large cities are starting to reject GPS based solutions as they see them as entirely inadequate.
Luna technology can give stakeholders real time, accurate confirmation and control of how scooters are being ridden.
AI parking selfie
This is a new, very low cost, highly effective way to ensure riders park their free floating scooters/bikes correctly in virtual docks, at the end of each ride. The computer vision enabled parking verification algorithms, are creating irrefutable and real-time ‘virtual docks’ for operators, using predefined visual clues.
This is an app-based solution (no hardware requirement), but we will also be offering this parking verification/compliance capability as part of the Luna sidewalk riding detection hardware module.
The ‘AI parking selfie’ tech obviates the need for expensive fixed corrals, removes the perceived need for lock-to ordinances by cities, and also avoids docking station RFP stipulations from municipalities that lower utilization rates.
There is no need to LiDAR map thousands of parking locations in each city, and no need to rely on highly inaccurate geofences in order to manage your parking locations. You just need some painted markings on the ground – whether they be an operators bay markings or an existing city car park space with scooter signage.
AI parking detection
Selected participant of EIT Urban Mobility's 2023 Scale-up programme. EIT Urban Mobility is supported by the European Institute of Innovation and Technology (EIT), a body of the European Union
Luna is a unique mix of telematics, cloud, AI/computer vision software, hardware, electronics & smart city skills
About us
Founding team
Andrew Fleury
CEO
Andrew has spent the last two decades exclusively dedicated to the fields of telematics, fleet management and intelligent vehicles. This includes 15 years as the CEO of Transpoco, the leading telematics provider in the Irish market, with customers is more than 60 countries.
Andrew has a keen interest in the future of transport, mobility and unmanned autonomy.
He is currently the president of the 1-Telematics Alliance, a European thought leadership group. He is also on the steering committee of both the “Vehicle Of The Future” (VOTF), and the “Connected and Autonomous Vehicles” (CAV) industry groups in Ireland.
Ronan Furlong
CBO
Ronan is the Executive Director of DCU Alpha, Dublin City University’s Innovation Campus, which is Ireland’s leading cluster of IoT, M2M, Data Analytics and e-mobility companies.
Ronan is a qualified Architect and Smart Cities/Sustainability expert and sits on the advisory committee of Smart Dublin. He also advises governments, municipalities and real estate developers on innovation district/cluster and e-mobility policy development.
Ronan has a B.Arch from UCD, a MBA from Trinity College Dublin and a Dip. Sustainable Development from DCU.
