Driving in circles, searching in vain for an open parking spot, is a stressful experience we all dread. Coupled with the uncertainties of traffic and trip-planning, parking adds another layer of frustration to a hectic commute.
But what if we could use real-time traffic data to make on-street parking easier and more predictable? Using machine learning and real-time data, that’s what ParkNav hoped to accomplish — taking the stress out of parking.
To make their idea a reality, the team of data scientists, engineers, and entrepreneurs behind ParkNav came to Forte Group.
Comprehensive SDKs for building and running IoT software
Transportation and Logistics
Type of work:
Technology and Platforms:
Machine learning, Artificial intelligence
Build an application from scratch to solve a variety
of day-to-day traffic challenges
Design a convenient tool people can use on the move
Take into account all parking areas’ parameters that might be important for the driver
Optimize the user experience that supports on-the-go decisions
Integrate real-time monitoring and predictive analytics
Enable user preferences for more personalized and safe parking experiences
This predictive parking data is updated in real time. Users can filter the results according to the type of parking they’re looking for, as the map includes free, zoned, and metered spots or they can search for nearby parking garages.
Users can enter their desired parking area, and the application displays the results in green, orange, and red. Based on data, each color represents a different level of predicted parking difficulty. Green areas have the most open parking spots, orange zones are less ideal than green, and red sections are unlikely to have available spots.
Because ParkNav is a tool that needs to be used quickly by people on the move, the user interface (UI) and usability were essential. The Forte UI team improved the app’s usability to optimize the user experience.
An application combines the company’s database of parking information with traffic data to create precise, accurate, and real-time recommendations.
Users can also save their preferences in the app, making the whole search experience more pleasant and stress-free.
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SXSW Conference Accelerator Enterprise and Smart Data award winner