Processing data from video directly on the device itself instead of using a cloud server is the latest trend in video analytics in recent years. This technology is called “edge computing'' and has huge potential for retail trade

History and developments

For a long time, video data from cameras was processed on the cloud (on a remote server): it allowed large server capacities to be connected to data analysis for quick and efficient performance.

But technology is evolving, and local servers and even cameras themselves now have enough power to analyze video locally. Now there are video cameras that not only record and stream video, but independently analyze what has been recorded. They also carry out essential functions: for example, sending notifications or displaying images on screens. This significantly expands their capabilities and reduces the company's IT infrastructure costs.

Use edge computing and win

The company can save on:

• Internet traffic. When there are no large amounts of data to transfer, you can choose a more affordable payment plan and save money.

• Cloud technologies. There is no need to pay for connection to a virtual server or install your own, which will require maintenance and personnel.

• You save money and time. When data is analyzed on the camera itself, it only takes a few microseconds - hundreds or even thousands of times faster than cloud computing. This can be a big help in some cases. For example, factory machinery can stop instantly when someone enters a hazard zone.

• Video cameras with edge computing are being used today in various industries, such as robotic cars, factories, and building security. And the scope of their application is constantly expanding, with the latest including retail trade.
  

How Do Smart Video Analytics Benefit Retail?

Store owners strive to cut costs and improve the efficiency of their outlets because retail is a very competitive environment. Another goal is to improve the user experience so as not to lose out to online stores. Smart video analytics helps retail with both objectives.

Smart video analytics as a retail worker

Smart video surveillance has great potential to improve UX. Here are some examples:

• Recognizing VIP clients and giving them special attention.

• Individual advertising. Artificial intelligence determines the gender and age of visitors, selects appropriate items, and displays them in advertisements.

• Safety in the store. Blacklisted visitors will be instantly recognized and the camera will send a warning to the store's security.

• IT infrastructure development. Many large retailers have their own IT infrastructure for analytics and strategic development. Operational and customer data is collected and scrutinized. Hardware video analytics can be an effective part of this infrastructure. It can also be used to synchronize internal store services with online and mobile services.

Making consumer profiles

Edge computing collects data on how shoppers behave both online and in person. Based on the data collected, their behavior can be predicted. Consumer profiles help to build a model of their future behavior. They also help analyze what exactly influences the decision-making of your customers.

Understanding customer motivation and managing the factors that play a key role in it is the path to creating winning development strategies for each retailer and, in the long term, succeeding against the competition while obtaining high profits.