Using stream cameras and video analytics servers (which include Facial Recognition, Queue Detector, People Counter, Activity Visualizer and Analytics system package for retail), rinf.tech has developed this solution to map each client’s needs and solve even the most demanding requests.
The rinf.tech proposed architecture is the following:
- PostgreSQL – fully managed database
- ASP.NET Web Services and Web API
- IIS service for hosting the Web Application and Web API
Furthermore, we employed:
- Windows service for data synchronization Web Application – React JS frontend developed user interface application, in which the users perform actions like setting the store, viewing and comparing data on various criteria.
- Third party software for face recognition analysis, queue and people count data.
- Third party cameras with face recognition, people count and heatmap processing functionalities.
The main features include: people counting, gender and age breakdown, in depth visitor analysis, interval comparison & selection, direction and heatmap analysis, timeline comparison, queue time and waiting number of people.
- cameras with people counting capabilities
- face recognition systems
- third party systems with push notifications events