Take Shopping to New Heights with AIoT at the Edge
April 09, 2021
The concept of “shopping” in a brick-and-mortar establishment hasn’t changed much in the last 100 or so years. The means of payment has changed greatly over time, but until recently, the shopping experience has remained mostly the same—you go into the store, pick out the merchandise you’d like to buy, and go up to the register and make the payment.
That experience is about to change in a big way, thanks to AI at the Edge of the IoT, also known as AIoT. These changes pertain to both physical brick-and-mortar stores and on-line (e-commerce) shopping. But for this discussion, we’re going to stick to the brick-and-mortar stores. Such shopping still represents the lion’s share of all shopping, more than 80% according to industry experts. And that number could potentially grow, thanks to the AIoT-enhanced shopping experience, where consumers are given an experience to shop faster, safer, and smarter. And hopefully, will be enticed to make more purchases.
AIoT combines with the increased use of robotics and automation to provide consumers with a more satisfying shopping experience. Behind the scenes, retailers are adopting big data analytics, machine learning, and blockchain to achieve these goals. One example is the smart-fitting mirror offered by Gigabyte. It lets customers “try on” clothes without actually trying them on, and can send images to people anyplace in the world for suggestions. It should be noted that such an experience has become crucial in the pandemic era, where trying on clothes in the real sense is forbidden in many establishments.
For smart retail to be successful, a series of boxes must be checked. These include, but are not limited to:
Elevating the customer experience
Simple to deploy
Customer segmentation (at a level that’s deemed to be “politically correct”
The ability to provide real-time promotions and discounts
The ability to provide interactivity
While the potential for such solutions is huge, the burden placed on the retailer must be extremely small—the retailer is obviously not a developer or engineer. Hence, a straight-froward process would be required. Today, that technology is wrapped into a GPU-based platform, such as those offered by Aetina.
For example, Aetina’s NVIDIA Jetson-based edge computing platform has the potential to drive retail-oriented AI applications whole keeping the power at a minimum. It could include identity management to help with customer preferences, a robotic clerk to simplify picking out products, and object detection for self-checkout. With the company’s EdgeEye remote management platform, based on NVIDIA’s Jetson, retailers can have real-time monitoring through a customizable dashboard.
If multiple displays are needed, that’s not a problem, as the Jetson is more than up to the task. In fact, the video wall is now a reality, using higher pixel counts and compute-intensive GPUs. For that application, Aetina offers the MDS-DP16H-20 all-in-one player, which is a complete hardware-software platform. Powered by both an NVIDIA discrete GPU and an Intel 9th generation Coffee Lake processor, up to 16 displays can be driven.
Tying all the hardware together is Aetina’s MView Power software, which enables applications like the video wall. Powered by the advanced GPU-accelerated hardware, it supports an editable player, scheduling, local control, and remote monitoring, resulting in brilliant and intuitive content, with easy installation and editing. MView Power enables setup in three quick steps: selecting objects, editing, and playing.