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README.md

Transport from farm to factory - using IoT to track food deliveries

Many farmers grow food to sell—either they are commercial farmers who sell everything they grow, or they are subsistence farmers who sell their surplus to buy necessities. Somehow, the food needs to get from the farm to the consumer, and this usually involves bulk transport from farms to hubs or processing plants, and then to stores. For example, a tomato farmer will harvest tomatoes, pack them into boxes, load the boxes onto a truck, and deliver them to a processing plant. The tomatoes are then sorted and delivered to consumers as processed food, retail products, or served in restaurants.

IoT can assist in this supply chain by tracking food during transit—ensuring drivers follow the correct routes, monitoring vehicle locations, and sending alerts when vehicles arrive so the food can be unloaded and prepared for processing as quickly as possible.

🎓 A supply chain refers to the sequence of activities involved in producing and delivering something. For example, in tomato farming, it includes seed, soil, fertilizer, and water supply; growing tomatoes; delivering them to a central hub; transporting them to a supermarket's local hub; moving them to individual supermarkets; displaying them for sale; and finally, selling them to consumers who take them home to eat. Each step is like a link in a chain.

🎓 The transportation aspect of the supply chain is called logistics.

In these four lessons, you'll learn how to use the Internet of Things to enhance the supply chain by monitoring food as it is loaded onto a (virtual) truck, tracking the truck as it moves to its destination, and receiving alerts when the truck arrives. You'll explore GPS tracking, storing and visualizing GPS data, and setting up notifications for arrivals.

💁 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. Location tracking
  2. Store location data
  3. Visualize location data
  4. Geofences

Credits

All the lessons were written with ♥️ by Jen Looper and Jim Bennett


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.