Data Annotation is Paving the Way for a Convenient Future

Despite the COVID-19 pandemic in-person shopping is still a part of our daily life. Even now it is difficult for online shopping to compete with the convenience of picking up food and essentials from a local store. The continued popularity of convenience stores means that they are also a focus for innovation.

Computer vision AI leaders are developing technology that will make cashierless, frictionless convenience store shopping commonplace. However, a number of challenges still need to be overcome. The computer vision models that power cashierless stores depend on high quality training data to learn and perform optimally.

Accessing the right amount of precise data can be a daunting challenge for AI developers. Consequently, many AI companies collaborate with data annotation providers with experience of producing high performance training datasets.

Firstly, this blog will look at why many companies and consumers want cashierless stores. Secondly, we show how computer vision based AI models make frictionless shopping possible. And finally, we will detail the key advantages of image and video annotation services for this sector.

The demand of cashierless convenience

Cashierless convenience stores allow consumers to shop and leave the store without having to put their items on a conveyor belt for scanning. The first advantage of cashierless stores is ease of access for consumers.

Paying with an app as you leave the store is much faster than queuing for a checkout. Additionally, cashierless stores can be truly 24/7. This makes them ideal for customers with different work schedules or who prefer to shop in the evening.

For convenience store companies, cashierless technology helps to reduce staffing costs and ease the burden of finding workers in a competitive labour market. 24/7 shopping also extends the time during which profits can be made. For smaller businesses cashierless technology means that they can keep their stores open during holidays and vacations.

How computer vision enables frictionless shopping

Cashierless convenience stores are powered by computer vision based AI models. Firstly, cameras in shelving units and on the store ceiling capture each item that is selected by a shopper.

Secondly, computer vision algorithms determine what kind of item has been picked up using object recognition capabilities.

Thirdly, the in-store system recognises the shopper so that they can be tracked around the store. Shopper identification can be done with facial recognition models or with systems that track individuals’ heights and clothing types.

Finally, shoppers leave the store and pay through a mobile app for the items that have already been recorded. This frictionless process saves a large majority of the time that customers spend queuing for conveyor belts or using self-scanning checkouts.

Preventing theft

In-store cashierless systems like the one described above can help to stop shoplifting. Customers need to scan into the store and everything that they take from the shelves is charged to them automatically when they leave. As a result, it is much easier for retailers to keep track of stock and know what has and hasn’t been paid for.

Data annotation and computer vision innovation

Keymakr is a data annotation provider that works with computer vision industry leaders. Keymakr supports innovative AI projects by offering unique advantages:

• Creating data: Keymakr has production facilities and the capacity to create training data for specific needs.
• Managed teams: An in-house team of experienced annotators means higher levels of accuracy. Centrally located annotation teams are also easier to manage than crowdsourced, remote workers.
• Secure data: Keymakr uses a range of security procedures, including encryption, data expiration and VPNs, to keep your data safe.