What they do: Parknav turns location data from tens of millions of cellphones into actionable insights about how people move through cities. Their first product is an app that predicts which streets have parking available with up to 95% accuracy, and they already make money.
Why it’s a big deal: Accurate data on how people move through cities is invaluable. Retailers use it to site new locations, and drivers want real time data on open parking spots. Parknav uses their machine learning expertise to create the best real time location data available. They’ve started by solving a problem that 50M drivers have every night in US cities. Finding street parking. Their predictions are so accurate that their current customers include service fleets, navigation companies, real estate brokers, and automobile manufacturers.
Parknav is working with Telecom companies to mine location data from tens of millions of devices – giving them enough information to accurately predict parking availability across all cities in Germany and the US. This isn’t just the first accurate parking app, Parknav is laying the foundation to own the first and largest data set of human demographic movement ever.
- BMW will supply Parknav’s real-time street parking insights to all 1.5 million BMWs sold worldwide each year.
- 4 times out of 5 accurately finds available parking.
- 70 cities and two countries covered by the b2b service.
- Amassing the largest human location data set in the world.
- Parknav charges auto companies $9 per new car / year.
- Content partners will soon launch Parknav to 100M users.
Parknav turns location data from tens of millions of cellphones into actionable insights about how people move through cities. Their first product is an app that predicts which streets have parking available with up to 95% accuracy, and they already make money.
Youtube: https://youtu.be/SsQv6p7FHiI, https://youtu.be/50rM4wre_b4, https://youtu.be/nrJx9jJhQBg, https://youtu.be/a8DPOtuA2jQ
See Campaign: https://wefunder.me/parknav
Contact Information:
Eyal Amir
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Source: icnw