The service provides the possibility to recognize faces using video streams from HTTP/RTSP connections with outdoor cameras. The system can identify persons, their age and gender. It easily integrates with existing camera systems. Using the AI and Computer Vision technology it can gather and analyze massive amounts of data.
The client had an old semi-working prototype system running on Django templates with no front-end frameworks. The task was to create a new visual template, run the code, add the ability to view all cameras connected to the system in real time, then rewrite the system using the framework.
We delivered recognition dashboard MVP in 2 months
We delivered V2FA MVP in 1 month
We delivered iOS Chek-in App MVP in 2 weeks
We used Django REST API as the basis for the backend of the new version of the system, Angular framework to build the frontend application. This combination allows rational use of hardware capacity. It also optimizes system performance, allowing easy scaling in the future.
For V2FA were used:
In iOS Check-in App we used:
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