SecurityWorldMarket

18/04/2019

People counting for increased retail success

Hoofddorp, The Netherlands

Smart people-counting cameras can double as security protection for retailers - at the same time as providing a way to look after customers and assets they can also be used to  accurately count people coming into the store for various analytical purposes to improve the business – and all with a single investment.

Smart people counting cameras can help retailers to improve operations in a number of ways.

For example it is possible to precisely increase the number of staff during busy times to improve service on the shop floor, and to reduce staff during quieter times to increase operating efficiencies. More accurate predictions can also be made on what may happen in terms of demand over the coming days, weeks and months and accurate plans can be made for future activities based on staff and inventory.

As a result, counting people in store can help retailers optimise their strategies and maximise conversion and revenues. However, the task of accurately counting customers over an extended period of time is a difficult one, particularly as legacy camera technologies are not always up to the task.

People counting for health and safety

People counting provides valuable insights across a range of industries and use cases. It can help to ensure crowd safety in high-traffic-flow areas such as stadia, for example, as well as ensuring that the number of people entering clubs, exhibition halls and other locations does not exceed fire safety guidelines.

Overcoming historical people-counting challenges

In the past, retailers often attempted to count people in store using single lens cameras. These were often prone to mistakes, confusing people with other objects, leading to inaccurate counts and misleading information about who has visited the store and what they did there.

One major problem with single lens cameras is that they have no 3D perspective, which makes it impossible to understand how tall an object or person is. This means that all kinds of inanimate objects can be mistaken for people, from shopping carts to baby carriages. The problem can be exacerbated when there is a change in lighting conditions, and even shadows have contributed to inaccurate people counts in some cases.

To overcome all of these challenges, forward-thinking retailers are installing next-generation dual-lens cameras in store. These record and process two images of a person concurrently, allowing a 3D image to be created. This accurately records the person’s height and shape, identifying them positively as a human being, rather than an object or shadow, for example.

Delivering even more customer value with AI and ML

The best dual-lens cameras are also equipped with Artificial Intelligence (AI) and Machine Learning (ML) technologies that allow cameras to ‘learn’ over time. It becomes possible, for example, to gain new insights into customer preferences based on their demographics and in-store behaviours, leading to more effective merchandising decisions.

Covering security requirements with the same smart camera

The other major benefit of smart people-counting cameras is that they can double as security protection. This means that retailers can look after customers and assets, and accurately count people coming into the store – all with a single investment. With only one set of cameras, retailers can make significant savings on installation, energy consumption, maintenance and support – while also getting the very best in surveillance and smart retail insights.

Accuracy and precision is key

Hikvision’s people counting cameras deliver major benefits. They offer accuracy, with a dual-lens configuration that provides 3D imaging to distinguish people from inanimate objects and shadows, and also incorporate Deep Learning algorithms that can be continuously trained and improved with new data sets to count people more preciously.

Hikvision has helped organisations in a number of industries to count and monitor people entering their facilities.


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