Topics: Physical, Browsing, System, Retail, Information, Track
Consider a typical retail store scenario: a customer walks into a store and walks purposefully to a location that she has in mind when she arrives. She might spend some time in that section, browsing the aisle. Are you looking for welding supplies? She might linger over some items or inspect them more attentively before deciding whether to purchase them. Each of these physical characteristics of the user’s buying behaviour could indicate her interest in tracking physical browsing features such as walking the Gacy residence, reaching out, and so on. It could provide us with a wealth of information about users’ preferences. This is referred to as “physical analytics.” This is like the online version. How can we design a system that would track users’ physical browsing when they visit web pages, when a portion of them click on certain links while ignoring others? We could use mobile devices such as smartphones or smart glasses for this demonstration. We mix smart glasses with other technologies. Smart classes using inertial sensing to classify users’ physical behaviour enable the first person’s vision. By combining information from inertial sensors and the camera with an accelerometer, we can determine if the user took a step or not. We can also identify the object by studying the users’ perspective. The user in this demonstration was a single individual who processed the photograph.
A mock-up of a retail store has been constructed. Let’s have a look at how our system works today. We can employ the third eye to track users’ physical processing. They can analyse and develop inferences from the data collected by our system. Which product was viewed, for example? the most. In addition to video, it demonstrates how a system can be used to track users. Physical browsing and other interior areas, such as those available at a conference or trade show. For example, during a conference, you could want to keep track of a username poster session. We can utilise the posters and OCR to figure out which poster the user is looking at. We assessed our sister in retail outlets in the United States with the help of seven people.