13 Applied Artificial Intelligence & & Internet of Things Industrial Use Cases in Retail Industry


“We used computer vision, deep knowing algorithms and sensing unit fusion, much like you ‘d discover in self-driving automobiles. We call it -Just Walk Out’ innovation”


Much to the surprise of everyone in the retail market, Amazon launched a brand-new format of shops called “Amazon Go.” The most interesting function of these shops is that shoppers will not need to inspect out at a counter with a clerk or perhaps with an automated kiosk. Consumers simply need to swipe into the store with an app, then leave with their desired products– no checkout necessary. Amazon’s “Just Walk Out” ability is based upon the twin technological combination of IOT and AI innovations.

While “Just Walk Out” technology represents the future of what AI and IOT can do for retail, traditionally, retail has actually been an entrance for enterprise adoptions of IOT innovations. One prominent example is RFID’s, a crucial IOT version which was introduced for real-time tracking and identification of products using SKUs on retail racks or inventory products in trucks, rail freight or ships. As an early adopter of IOT innovations, retail can be viewed as a leading sign for what’s to come in the AI and IOT domains.

AI researchers are pioneering sophisticated methods for cross-selling and up-selling that look to transform retail by analyzing market baskets and client sections in such a way that will improve the shopping experience for consumers and optimize worth for sellers. It can be definitively mentioned that the retail market has a much faster rate of adoption for AI and IOT innovations than other market verticals.

Some special possibilities used by integrating AI and IOT technologies follow:

  1. Clerk-less Stores: Extending the concept of “Just Walk out Technology,” we will see the emergence of completely automated stores, offering the convenience of checkout-free shopping made possible by the combination of RFID personalized trackers and AI, digitally–enabled vision powered by deep learning and sensor analytics (sensor fusion).
  2. Supply Chain Optimization: Retail is heavily dependent on efficient supply chains. AI combined with IOT has tremendous potential in this space. Here are two use cases:

Use Case B. 1: Real-time tracking of transport automobiles improves fleet or route usage which in turn enhances the replenishment schedule

Use case B. 2: Shipping and delivery lead time, especially for e-tailers, can not only be precisely anticipated, it can also be optimized by AI algorithms which eventually increases clients’ confidence in e-tailing outfits.

  1. Inventory Management Optimization: AI can be used to lower inventory costs by analyzing consumption data and making predictive inventory control decisions based on data run through AI algorithms
  2. Customer Experience Optimization: Data gleaned from RFID-based object trackers can be analyzed to know when an item is sold out and how fast it needs to be replenished so customers will be able to find what they are looking for or know exactly when it will become available again
  1. Customer Analysis and Segmentation: Given the availability of AI tools and techniques to micro-segment the customers into fine-grained segments offers retails to offer high levels of personalized items and services to different types of customers thereby increasing overall stickiness and increasing overall customer lifetime value.
  2. Marketing Campaign Management: AI can be used to personalize both traditional and digital marketing campaigns by running analyses on customer preferences and personas which will increase the likelihood of marketing campaign success.
  3. Real-time Shipping Trackers: IOT sensors make it possible to track different products at various stages of their shipping journey. Real-time information from the sensors can be passed on to customers and retailers. This has been a boon for e-tailers because digitally savvy customers have come to expect insight into the progress of their order and this technology has let retailers kindly oblige.
  4. Humanoid Robots: Humanoid robots can be used to improve the in-store customer experience by speeding up interactions and personalizing the shopping experience for the customer e.g. Pepper, a humanoid robot that can interact with customers and “perceive human emotions.” Pepper is already popular in Japan, where it’s used as a customer service greeter and representative in 140 SoftBank mobile stores.
  5. Delivery and Transportation: AI-enabled drone and robot delivery systems have already been deployed by various retailers, but optimizing last-mile delivery seems to be the largest hurdle. Such robots and drones will use extensive AI and sensor networks to operate effectively.
  6. Computer Vision Quality Control: Computer vision can detect defects in materials and SKUs before stocking them in retail stores or warehouse shelves. Whether it is physical deformation or spoilage, AI-powered computer vision will enhance retailer image and make sure customers are only purchasing goods that meet acceptable standards.
  7. Efficient Floor Planning: Thorough analysis of floor plans and space design can help retailers and warehousers organize aisles and cross correlate with SKU level sales data to efficiently organize shelves to increase sales throughput and ease of access. AI-based planning and optimization routines can continuously monitor this process.
  8. Warehouse Management Optimization: A recent story emerged of how Alibaba managed to handle $21 billion USD in sales in a single day by using robot-enabled warehouses. AI and IOT robots save space and maximize scale and don’t get tired.

While these are simply a few of the AI and IOT use cases in retail, we expect more innovations currently being established will quickly be available on the market to interfere with existing trends.

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