IoT-For-Beginners/translations/en/5-retail

Retail - using IoT to manage stock levels

The final stage before food reaches consumers is retail—markets, greengrocers, supermarkets, and stores that sell products to customers. These businesses aim to ensure their shelves are stocked with items for customers to see and purchase.

One of the most labor-intensive and time-consuming tasks in food stores, especially large supermarkets, is keeping shelves stocked. Employees often need to manually check shelves and fill any gaps with items from storage rooms.

IoT can simplify this process by using AI models on IoT devices to count stock. These machine learning models go beyond simple image classification—they can identify individual items and count them.

In these two lessons, you'll learn how to train AI models based on images to count stock and deploy these models on IoT devices.

💁 These lessons will use some cloud resources. If you don't complete all the lessons in this project, make sure you clean up your project.

Topics

1. Train a stock detector
2. Check stock from an IoT device

Credits

All lessons were created with ♥️ by Jim Bennett

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Disclaimer:
This document has been translated using the AI translation service Co-op Translator. While we aim for accuracy, please note that automated translations may include errors or inaccuracies. The original document in its native language should be regarded as the authoritative source. For critical information, professional human translation is advised. We are not responsible for any misunderstandings or misinterpretations resulting from the use of this translation.