All of us who drive and live in urban metropolitan areas have had a frustrating parking experience, be it spending too much time looking for an available parking spot, or getting our car towed after overlooking the parking restriction. SpotAngels is a company aiming to solve those two parking problems, for current drivers but also ultimately in the self-driving world.
SpotAngels is a San-Francisco based start-up founded in 2014 and a graduate of Y-Combinator summer 2014 batch. The company focuses on solving the car parking problem. While it is still at its early stage, SpotAngels is developing an innovative way of leveraging crowds to solve the car parking issues for car owners.
Currently the company has an iPhone consumer App that is made available to users for free. The App automatically detects when a car is parked, and sends notifications to the users regarding parking restrictions (e.g. “Street cleaning in 20 minutes”). In the near future, the App will also allow users to see a real-time map of parking availability.
Crowdsourcing Parking Restrictions
Parking restrictions are complicated, not uniform across cities, and there is no public central database making them available – not even cities can provide a database of their own parking regulations. In order to build a database of parking restrictions in a short period of time, SpotAngels have used a combination of proprietary computer vision technology to read parking regulation signs, which provided a majority of the data, combined with a crowd-sourcing model where users can take a picture of the parking sign and share it with the company. The snapshots below show how the user can send a picture on the App. Despite the recent re-launch of the App, the team has been receiving a large number of data from its users – which have made processing the data in a timely manner challenging.
Next Step – Crowdsourcing Parking Availability
Parking restrictions are just one part of the problem. The other key problem is the ability to identify available slots for parking in real-time. Multiple innovative crowd-sourcing approaches are currently being explored by the team.
One approach would be to collect data in real-time from the App users when they park their car, and use predictive models to predict how likely is that street / area to be busy at that time. The challenge with this approach resides in the fact of reaching a critical size in order to be able to make useful predictions.
Another way to crowdsource parking availability would be to partner with a pool of car owners who ideally spend a lot of time driving around (e.g. taxis, ride-sharing companies) and ask them to scan the streets in real time and collect data when they see a free parking spot. The challenge with this approach would be the need to develop a new ‘scanning’ technology as well as the ability to reward the pool of scanning cars – which would typically involve paying a small fee to them.
Business Model and Value Capture
As mentioned above, the B2C App is made available to users for free. The company has basically two options in terms of value capture:
The first option is to continue focusing on the B2C space and develop new innovative ways of monetizing the app usage (Just like Waze did through advertising or may be up-selling new features).
The second option would be to keep the B2C App free of charge without advertising, and selling the parking availability and restrictions data to businesses who want to integrate it in their own software (e.g. just like Google Maps is selling the mapping service to apps like Uber).