Smart Parking
Parking Optimisation System
Challenge
Our client wanted to build a system to reduce time needed to find a parking spot in the city. The goal of the system is to intelligently calculate route in a way that maximises the chance of finding a parking spot close to user’s destination. The system should include advanced predictive analysis and recognition of behaviour 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 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.
Development
January 2019 — still being developed
Tool used
Kotlin, Kafka, Spring, Cassandra, Redis, Swift
Solution
We have implemented mobile applications that collect the telematic data and detect crashes as well as a backend platform that performs data analysis, calculates predictions and implements custom routing algorithms. We have applied deep learning to solve the crash detection problem. 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.
See also
