ValetEZ

ValetEZ – Building products for the real world

As part of our TechSpeak series, our CEO – Smit Kant Raturi talks about how building a product that works well in the real world is central to our mission of making parking efficient and easy.

What are some of the use cases and on ground challenges that you solve for at ValetEZ through technology?
Our smart parking tech solution works with multiple use cases and on ground challenges on a day to day basis:

  • Use cases: Working with multiple kinds of hardware to integrate the ValetEZ ‘parking-in-a-box’ solution and make the overall solution IoT and AI enabled. Handles parking traffic across all formats of parking and different use cases including self-park as well as assisted valet parking
  • On ground challenges: These include low internet speeds / Intermittent internet connectivity, non standard system integrators, legacy equipment such as access control barriers, kiosks etc. 


Why is it important for the product/ technology to work seamlessly and why does it matter in parking? 
Most locations and parking setups require real time data collection at the Entry and Exit, digital payments, and updating of the parking inventory/ slots available in a location. Many of these locations experience high burst of traffic over a very short duration (eg. metro stations) or continuous stream of traffic 24*7 (eg. hospitals) or are the first/ last point for customer experience (eg. malls). Hence, it becomes important for the technology to work seamlessly to service our parking lot partners and end users in the best possible way.

What role does reliability of data play here? eg. for building AI/ML systems
Data reliability is a big part of the ‘Parking-in-a-box’ solution at ValetEZ. Data collected from the parking operation, be it at the Entry and Exit or at the slot level of a parking lot, helps determine multiple data points about the user and feeds into the partner analytics dashboards on footfalls and parking inventory utilization. Reliable data plays a key role in building predictive AI/ML models for forecasting parking availability and other such data points. 

What does it take for the engineering team and yourself to ensure this high quality of product delivery?
The biggest ask is around agility and speed of learning. We need to continuously work with and learn about unique on-ground challenges across different parking formats, work with new system integrators and  hardware providers, and integrate with different digital payment providers, all to ensure that our solutions deliver an efficient and reliable parking management solution for lot owners/operators and an easy (‘EZ’) experience for users.

What are some of the areas where technology can make a big difference in parking going forward? 
As we bring physical parking inventory onto a digital platform, multiple aspects will have to be improved: 

  • User experience to allow end user to explore and interact with such inventory
  • Remote monitoring, support and maintenance of hardware and software using OTA software uploads and cloud based logging could be important as scale and presence transcends different geographies
  • Leveraging data to predict utilization of resources using ML /AI, improving usage for partners and better data and services for end users
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