Follow

Why Choose Social Bicycles?

Social Bicycles is the next generation of bike share at ½ the cost of conventional systems. Our innovation is produced by combining advanced technology and software integrated directly onto our custom designed bicycle. We provide this platform to municipalities, campuses, and local communities to launch the most flexible and functional bike share programs available. The conventional dock-based systems lack flexibility and robustness due to outdated technology and and reliance on single failure points such as kiosks. With our smart-bikes, each bicycle communicates individually through a reliable GPS and wireless connection.

This enables new features for users such as advanced reservations, holds, out-of-station locking, location-based promotions, and much more. It also avoids common dock-based problems such as exponential Dock Block.

The key difference between Social Bicycles and dock-based providers is the smart-bike system architecture. Our smart-bike’s onboard GPS communicates via a GSM connection, with stations and system areas defined by GPS geofences. Existing groups of bike racks can be leveraged as bike share infrastructure with the click of a mouse. Our station infrastructure is low-cost and modular. Instead of $900 per dock, Social Bicycles racks cost $175. The Social Bicycles system architecture is allowing large cities to launch at higher density and is enabling the possibility of bike share for smaller cities, hotels, campuses, and even individual communities.

Our industry leading mobile and web platforms bring bike share into the 21st century with an engaging user experience. Web and mobile users can interact with smart-bikes on a real-time map, manage accounts, purchase memberships, record routes, and reserve a bicycle in advance. For operators and cities, Social Bicycles smart-bikes are constantly collecting active GPS data. Competing systems often only record origin and destination data, but nothing in between. Our full route data is valuable for City planning efforts and enables a predictive rebalancing platform that leverages historical information.

Was this article helpful?
1 out of 1 found this helpful