With the state of the world today and the many supply chain problems we are currently experiencing, inventory management has never been more important.

What is Inventory Management?

Inventory management, a strategic element of the supply chain, refers to the tracking of inventory from manufacturers to warehouses and then to a point of sale. The goal of inventory management is to have the right products in the right place at the right time and it is where all elements of the supply chain converge.

How Computer Vision Works?

Computer vision works the same way as human vision, except humans are one step ahead. Human sight has the advantage of being able to train itself to distinguish objects, to determine their distance, to know if they are in motion and if something is wrong in an image. Computer vision trains machines to perform these functions, but it must do so in much less time with cameras, data, and algorithms than with retinas, optic nerves, and visual cortex and can quickly overwhelm human abilities.

Inventory Management Challenges

Different concerns loom large in the world of inventory management. Different industries face different struggles, although a basic level of uncertainty remains one of the most prominent issues at the moment. Many challenges arise together, creating an increase in struggle for small businesses and large corporations alike. These challenges include inconsistent tracking, changing demand, limited visibility, manual documentation, supply chain complexity, overstocking, inventory loss among others. 

How computer vision can help

To say that artificial intelligence is part of our daily lives and logistics is obvious. It is also evident that technology is an ally to further improve all supply chain processes. AI opens an infinite number of scenarios to explore and develop. Most companies have opted for automation to support their development. However, the latest advances in AI show that companies need to go further and make better use of the potential of machine intelligence if they want to differentiate themselves from their competitors.

Examples of businesses that integrate computer vision into their workflow

1. Unilever: The consumer goods company also uses computer vision to audit stores. It sent a crowd-based workforce to a number of stores selling its goods to grab pictures of store shelves. The pictures were then processed by a computer vision-enabled platform. The goal was to provide its managers with an accurate picture of in-store shelf conditions. The analytics and insights received from shelf images analyzed with CV allowed Unilever to identify irregularities in store, respond accordingly, and measure results. 

2. Amazon: Amazon launched its fully automated Amazon Go stores based on algorithms and computer vision. The stores filled with cameras and sensors are capable, autonomously, of tracing the customer's journey between the shelves and of recording the products that they put in their carts. When the customer goes to one of the automated checkouts, he will automatically be debited with the total amount of his purchases.

3. Car manufacturers: Autonomous CV vehicle systems continuously process a lot of visual data like traffic signs, other vehicles, and pedestrians to determine the right course of action.

4. Auchan: One of Europe’s biggest grocery retailers, Auchan deployed computer vision-enabled robots for shelf-monitoring in 34 of its stores in Portugal. The robots, which use computer vision and Internet of Things (IoT) technology, captured pictures of every shelf in each aisle of a store three times a day. Computers then digitized the data to generate reports with actionable metrics and insights. 

The future of AI in inventory management

In the future of inventory, we are going to see even more updates in technology. From virtual reality, to artificial intelligence and even inventory-less stores, there are constant changes being made to improve business and attract customers. Inventory management systems have become more real-time, giving retailers more data about demographics, spending habits, shopping preferences, etc. This will help retailers improve their efficiency with their inventory, and continue to serve their consumers better.

Conclusion

Computer vision will continue to drive automation and the convergence of solutions. Computer vision specialists are constantly innovating to offer the market cutting-edge solutions with a high return on investment. And this is what allows their customers to gain in efficiency and competitiveness thanks to more automation and better logistics management which is an undeniable asset for the year to come. With good inventory management, a business has a better chance of profitability and survival.