CCTV Analytics

Client: European retail business​

Technology​

Facial Recognition, Queue Detector, People Counter, Activity Visualizer and Analytics

PostgreSQL, ASP.NET Web Services, Web API, IIS service for hosting the Web Application and Web API, Windows service for data synchronization Web Application, React JS

Services

Dashboard development

Challenges

  1. High inefficiency in defining customer clusters by gender and age, resulting in slow follow-ups across departments and locations due to variability in operations.
  2. Inability to implement immediate response programs.
  3. Lack of understanding of customer behavior.
  4. Multiple delays in feature approval leading to loss of potential business opportunities.

Solution​​

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 a high-tech solution to map each client’s needs and solve even the most demanding requests.

The rinf.tech proposed the following architecture:

  • 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 ) to store, view and compare customer data against various criteria.
  • Third party software integration for face recognition, queue and people count data analysis.
  • Third party cameras with face recognition, people count and heatmap processing functionalities.

 

The main features include:

  • people counter,
  • gender and age breakdown,
  • in depth visitor analytics,
  • interval comparison and selection, direction and heatmap analysis,
  • timeline comparison, queue time and number of people waiting,
  • cameras with people counting capabilities,
  • face recognition systems,
  • third party systems with push notifications events

Methodology

Problem definition

rinf.tech assembled a team of technology experts to understand the problem areas to be addressed with the custom solution.

Testing the focus group

Based on the requirements & solutions discussed, mockups with single process flows were created. The mockups helped the client visualize the system before it was built. This helped collect feedback for further improvement.

Designing the Solution

The solution architect created and introduced a configurable dashboard based on defined rules and conditions. This dashboard is scalable to meet the client’s ever-evolving reporting needs.

Application Launch
After the client’s sign-off on the dashboard, the analytics solutions were launched and tested for effectiveness and efficiency at client sites with a pilot run in a supervised group of participants.

Results

  • 90% increase in customer insights 
  • 50% increase of the immediate response rate 
  • 60% increase in accuracy of customer patterns by using direction and heatmap analysis
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Optimized lines of code
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Hours of work
(development, QA, design)
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Targeted location
CCTV solutions development

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