The use of AI technologies has the potential to fundamentally optimize warehouse inventory. Automated recognition of products in a warehouse can be implemented in a number of ways. In particular, the identification and classification of products is a challenge. Common and widely used solutions are reading product labels or using sensor technology. Reading product labels is generally a suitable approach for identifying specific products.
The prerequisite for reading product labels is that the products to be captured have labels and that these labels are visible. This is not always the case, especially with very inexpensive goods or equipment such as containers or empties. There may also be storage conditions, e.g. in outdoor warehouses, where the application of printed labels is not suitable, e.g. due to weather conditions. The use of sensors also has its drawbacks: By no means all products are already equipped with sensor labels (e.g. RFID or NFC); in practice, this is usually only the case for certain products, usually high-priced or particularly important materials. In addition, there may be interference factors in the warehouse that make reading the tags even more difficult.