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How to Use Image Processing in Shopping Malls?

People Counting / Store Density Maps / Vandalism Recognition / Crowd Counting

Deep learning, one of today's most popular topics, has been used effectively in various fields of technology in the last few years. In connection with this, one of the most interesting topics is "Computer Vision".

Computer vision solutions focus on building and using digital systems to process, analyze, and interpret visual data. This field is a sub-category of artificial intelligence. The goal of computer vision is to enable computers or devices to accurately identify an object or person in a digital image.

Computer vision technology uses convolutional neural networks to process visual data at the pixel level. It uses deep learning—recurrent neural networks—to understand how the pixels it processes are related to others.

Nowadays, computer vision technologies are widely used for various purposes in almost every sector.  In line with their intended use, computer vision solutions have become frequently used in shopping malls.

Since shopping malls are places that people visit frequently, computer vision applications provide support to businesses in managing shopping malls efficiently and safely with their usage areas and advanced data analytics.

To give some examples of the usage areas of computerized vision in shopping malls:

  • Accurate data can be obtained by counting shopping mall visitors, and density maps can be created with computer vision applications.

  • Optimum locations for advertising and promotion points can be determined.

  • Data such as the number of visitors limited during epidemic periods can be accessed.

  • Contribution to floor planning is provided by learning the duration of visitors' stays in various parts of the shopping center.

  • By identifying the points where visitors routinely visit, the customer's waiting time at busy points can be prevented. In this way, improvements can be made in terms of crowd formation, especially during rush hours.

In addition to these, we can give vandalism recognition as an example of the use of computer vision in shopping malls. With a system that creates a great advantage in terms of security, crowd formation can be analyzed using security camera images, and quick action can be taken through security units. In addition, suspicious behavior by customers in stores can be monitored.

Dataguess Observer is a computer vision solution designed for shopping malls and similar venues. This product is equipped with features such as people counting, density mapping, and vandalism tracking. Dataguess Observer, which monitors human movements using camera images and sensor networks, analyzes customer flow and provides businesses with information about customer behavior. Additionally, it protects personal privacy with its face-blurring feature, preventing security cameras from violating individuals' rights. Thanks to this technology, businesses can increase customer satisfaction and improve their operational efficiency.

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