People Counting & Video Analysis

Traditionally private retailers, major stores, Museums, corporate businesses and sports stadiums used crude counters with a single, horizontal infrared beam across an entrance that counts when a person or object passes and breaks its beam.

People counting systems in the retail environment are used to calculate the conversion rate, i.e. the percentage of visitors that make purchases. This is a key indicator of a store’s performance and may provide more valuable information than traditional methods, which only take into account sales data. Taken together, traffic counts and conversion rates can reveal important sales information, such as why a specific store is experiencing more sales, whether or not year-over-year sales are down, why fewer people are visiting a store, or why fewer people are making purchases.

Accurate visitor counting is also useful for optimizing staff shifts. Staff requirements are often directly related to the density of visitor traffic, and services such as cleaning and maintenance are typically undertaken when traffic is at its lowest.

Shopping centers use people counters to measure the number of visitors. People counters also assist in measuring the areas of ‘hot spots’, where statistics gathered by people counters are often used to justify rental rates.

Crowd Management:

There are often large traffic flows before and after an event. People counters are used to measure the traffic flows of previous events, and the traffic patterns are used to improve traffic flow, particularly when entering and exiting.

Energy Usage Optimization:

Commercial buildings utilize people counters to measure the use of different parts of the building at different times. This information can then be used to intelligently optimize the energy usage in the building (e.g. air conditioning needs, etc.).

File Management:

In the case of fire, people counters are one of the tools used to approximate the number of people inside the building

Footfall measures the number of people entering and exiting a venue.

Window Conversion Rate is the percentage of shoppers who enter a store over in relation to the number of people who walk by it. With WiFi Counting, shops can estimate the number of people who walk past a store. A more accurate method is video counting. While revenue and footfall are important, the number of people who walk past a store often reflects the true potential of the store location. The Window Conversion Rate often depends on the attractiveness of the shop window design and the effectiveness of marketing campaigns.

Visit duration is the amount of time visitors stay in a venue. WiFi Countin has the ability to track both the time a person carrying a smartphone has entered the venue and when that same person has left the venue.

This metric looks at the number of people entering a store who had visited the store previously. WiFi counting has the ability to remember the Unique WiFi beacon signal ID emitted by shoppers, so if a shopper has previously visited a store, the counter flags the person as a returning customer.

This is the number of shoppers who enter a store who have previously visited other stores of the same chain. This is available for third-generation people counters that have WiFi Counting functionalities.

Many different technologies are used in people counting devices, such as infrared beams, thermal imaging, computer imaging, and WiFi Counting

Beam counters usually require a receiver or a reflector mounted opposite the unit with a typical range from 2.5 metres (8 ft 2 in) to 6 metres (20 ft). Despite its limitations, infrared counters are still widely used, primarily due to their low cost and simplicity of installation.

Thermal Imaging systems use array sensors that detect heat sources. These systems are typically implemented using embedded technology and are mounted overhead for high accuracy.

Thermal imaging systems use array sensors which detect heat sources from human body.

Before the advance of computer technology that allows complex algorithms to perform video counting, thermal counters were the main choice for most businesses.

With the advance of computer technology, complex image processing algorithms can now be used to perform counting using camera imaging. The third generation counters also include Wifi Counting functionality, which collects WiFi Probe Request signals from shoppers’ smartphones and adds a number of important metrics for businesses, especially for the retail industry. Many business are now deploying people counters to help them to gain insight into their clients.

Computer Vision works via an embedded device. This reduces the network bandwidth requirements as only the counting data has to be sent over the network. Robust and adaptive algorithms have been developed to provide excellent counting accuracy for both outdoor and indoor counting using computer vision. Multilayer Background Subtraction, based on colour and texture, is considered the most robust algorithm available for varying shadows and lighting conditions. With the advances in image processing, video count can achieve 98% accuracy in various lighting environments. The use of artificial intelligence and pattern recognition functions can further enhance its accuracy.

WiFi Counting uses a WiFi receiver to pick up unique WiFi management frames emitted from smartphones with a range of up to 100 meters. While not all people carry a smartphone, WiFi counting can produce statistically significant metrics due to the large sample size available. Apple iOS8 attempts to randomise MAC address, however it makes little impact on the effectiveness of WiFi counting. Apple iOS9 and Android 6.0 Marshmallow use more aggressive MAC rotation schemes, making WiFi counting impractical in the future.