Servo Security

People Counting & Real World
Visitor Traffic Analysis System
People Counting & Real World Visitor Traffic Analysis System

Visitor counting and attribute classification

Why there is a need

Classification of visitors is an important part of any retail business. People counting systems are used to estimate trends of attendance, to schedule staff work, to manage sales staff performance, to evaluate the effectiveness of promotions and marketing activities, as well for optimal organization of the sales object, in accordance with trends in attendance.

  • Count customer enter/exit, people count
  • Generate factional business insight and intelligence
  • Sales against people counting statistics
  • Age and gender statistics
  • Predicting sales based on location
  • Analytics triggers and alerts. (High occupancy, Long Queue, Age group)
  • Marketing campaign statistics
  • Face similarity statistics
  • Conversion Ratio
  • Vaccination Status
  • Vehicle Counting and profiling

People Counting Integration to POS

Integration to POS System to combine footfall traffic data with POS data to calculate the conversion rates.

Marketing Campaigns KPI Measurement

PCS helps you run marketing campaigns. Enter the dates, locations and budget of your campaign, then watch how the stores and dates you are targeting perform compared to your other times and locations. It’s the best way to measure how effective your marketing is.

People Traffic Analysis Platform

The following are some of the customer using the system

What the system can do?

  • Understand location traffic
  • Staff Resource Planning
  • Manage occupancy capacity
  • Identify the average duration of visit
  • Breakdown of statistics on zone
  • Historical statistics for analysis
  • Discover the low and high demand hours
  • Planning of traffic flow to obtain best occupancy impact to business
  • Simultaneous multiple face processing from single source.
  • Partially occluded faces recognition
  • Live face detection
  • Emotions recognition (anger, disgust, fear, happiness, sadness and surprise)
  • Facial attributes (smile, open-mouth, closed-eyes, glasses, dark-glasses, beard and moustache)
  • Age and Gender classification
  • Identification capability, 1-to-many mode (identification) – Cloud processing 40,000 faces per second
  • Queue limit alert
  • Queue traffic historical charts
  • Average waiting time per person
  • Staff resource planning