Parking Optimisation System

  • project: Smart parking solution
  • client: Not disclosed
  • year: 2018
  • website:

challenge:

Our client wanted to build a system to reduce the time needed to find a parking spot in the city. The goal of the system is to intelligently calculate a route in a way that maximizes the chance of finding a parking spot close to the user’s destination. The system should include advanced predictive analysis and recognition of behavior patterns.

The platform should initially be deployed in one city but needed to be designed in a scalable way, so that it can be quickly unlocked for larger areas and a larger number of drivers.

Additionally, the system should offer users features such as finding where they parked their car and crash detection combined with lightweight emergency notification.

tools used:

Kotlin,
Kafka,
Spring,
Cassandra,
Redis,
Swift
Our goal was to create a system that reduces the search time for parking locations availability in the public areas

solution:

We have implemented mobile applications that collect the telematics data and detect crashes as well as a backend platform that performs data analysis, calculates predictions and implements custom routing algorithms.

The system uses Bluetooth low energy devices to pair users with their vehicles.

The system is built using modern technologies, including Kotlin, Kafka, Cassandra, Redis and is deployed to AWS cloud.

We have applied deep learning to solve the crash detection problem.

impact:

We created a system that reduces the search time for parking locations availability in the public areas