eParkomat: Three Questions for the IoT Startup

  • Published: November 4, 2016
  • Categories: M2M/IoT, Smart City, Big Data
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Many young entrepreneurs are now bringing new startup ideas to the market especially in the area of parking – including Pavel and Petr from eParkomat who have a unique approach to on-street parking availability prediction. They are attempting to bring a real global product into the Smart City and Automotive spaces to enable easier parking for drivers by utilizing everyday real-time mobile telecommunication data.

eParkomat is a Big Data platform applying a unique algorithm using anonimized cellular/mobile network data to predict the actual parking situation both on-street and off-street with a really high accuracy of up to 96 %. To make it simple, instead of installing hardware sensors or cameras on all of the streets, cities can rely on the fact that a mobile phone can act as a sensor in each and every drivers pocket. According to the eParkomat trial in Prague last year, drivers were able to find an available parking spot in their desired location within three and a half minutes.

We interviewed Petr Hais and Pavel Vrba (the co-founders of eParkomat) during the third ChallengeUp! session in Amsterdam on 12th October.

The eParkomat idea is slightly different to the other startups in ChallengeUp!. It is not about sensors or hardware and it’s also not just another smart application – it is about big data. Why did you think exactly about big data?
Yes, correct, we are not bringing new hardware to the table and we strongly believe, that the future is in data – in fact in big data. There are already tons or better to say pentabytes of data around us that can be used in real time instead of just collecting it and sporadically analyzing it and this was the original reason why we tried to find a non-hardware solution for the parking problem. We knew it happened to everyone – missing business or private meetings as a convenient parking spot was not available in the city center. Nevertheless, our solution is also open to work with other data sources from fleets, parking sensors, cameras etc. When we also have this additional information we are able to calibrate our algorithm even more faster.

Who are or will be your target customers?

We are primary focusing on the B2B, B2C and B2G markets and especially in the Automotive industry For the Automotive OEM we are solving the problem of how to bring to the end-user “last mile” information as a part of comprehensive solution. We also found a big opportunity as a part of the Smart City Initiatives because current solutions are not able to fully cover a whole city as deploying a full Hardware rollout solution is quite expensive for them. The eParkomat solution can bring them roughly a 90% total cost of ownership (TCO) reduction.

Was it an advantage for you to come up with your idea while working for DTAG?
Yes, from the point of view of the first steps it was much easier. We had first hand easy access to the technology and had seen the latest trends. Deutsche Telekom and T-Mobiles culture also supported the process for the creation of internal start-ups, however, the beginning was not easy as we were not creating a typical Telco product. It took a longer time than we expected to set up the company but it was time well spent. Our previous experience also helped us to qualify as one of the Top12 startups at ChallengeUp 2016! where we are now working together with Telekom, Cisco and Intel on our European Go To Market strategy implementation.

Author: Angus Emery Product IoT Presales Manager and Mentor, Deutsche Telekom
  • Published: November 4, 2016
  • Categories: M2M/IoT, Smart City, Big Data
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