CCTV Analytics

Analytics solution created for the EUROPEAN retail business

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Software Development

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.

Technical Architecture

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
  • Windows service for data synchronizationWeb 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.
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Custom code

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Frontend

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Technology

Key Features

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
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Conclusions

The retail analytics application can help you:

  • Get better insight about the customers that enter your store with gender and age breakdown
  • Improve your service by analyzing queue data and act immediately
  • Better understand customer patterns by using direction and heatmap analysis