AI-powered vehicle identification system
Featuring insights from:
Software Development
SRC Factory Sp. z o.o.
About the client
Automatic car identification system with a web-based user dashboard. Polar Night Software was involved in the implementation of frontend and cloud-based backend solutions, as well as cloud vision algorithms aimed at seamless vehicle identification.
Project type
Ai, Web, Automotive
Industry
Automotive & Computer Vision
Location
Poland
Problem
Operators needed a reliable way to identify vehicles automatically and review results in a simple web console.
Approach
We implemented a cloud-backed vision pipeline with a responsive dashboard for monitoring, review, and exception handling.
Outcomes
Higher identification accuracy with human-in-the-loop review
Clear dashboards for ops and auditing
Scalable cloud setup for peak loads
Project overview
Partnership Goal
Deliver an accurate, auditable vehicle-identification flow that operators trust - automate what’s repeatable, keep a simple console for edge cases, and scale reliably as new cameras and traffic peaks are added.
From camera to confirmed vehicle
A clear path from captured frames to a verified identification.
Incoming images are processed in the cloud, where the vision pipeline detects vehicles and assigns confidence. Results move into a review queue so operators can confirm or correct when needed. The flow keeps latency low for routine cases and makes exceptions obvious instead of noisy.
This balance means the system handles the bulk automatically while keeping humans in control of the tough calls.
A console built for operations
The dashboard focuses on what ops teams do all day.
Operators can monitor live throughput, open any detection to review details, and resolve exceptions with clear context. Search and filtering help with audits, while an activity trail shows who changed what and when. The UI stays fast under load so teams can keep pace during peak hours.
Small quality-of-life touches - sensible defaults, keyboard actions, instant feedback - add up to fewer mistakes and quicker shifts.
Ready for real-world conditions
Built to cope with glare, weather, and rush hours.
The pipeline scales horizontally during traffic spikes and degrades gracefully if inputs get messy. Night images, partial occlusions, or unusual angles route to human review rather than blocking the queue. Feedback from confirmed corrections loops back into model improvement, so accuracy keeps trending up without risky big-bang changes.
The result is a system that performs day to day and keeps getting better with real operational data.
“Polar Night Software company is one of the best software providers that we had the pleasure to work with. The company was supporting us with the development of our own product related to automatic vehicle identification and they were involved in full-stack development. They were preparing machine learning algorithms that were used to teach the system about particular characteristic features of the vehicles and they also helped us with designing and developing web-based dashboard application for end users. We will definitely return to Polar Night Software with further products ideas.”
How our team turned ideas into a working, scalable solution
What we worked on
Services
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