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MIOTA · 41w

Using the Tangle for smart agriculture: The IOTA Foundation teams up with Future Farm consortium…

Tracking the farmer’s round bales is important for the climate and the economy (see demo):

Every project has its surprises. Working with the dairy sector in Norway is no different. The fundamental principle in our collaboration is fairly simple: to utilize the Tangle, IOTA’s underlying data structure, to create a new data infrastructure for a shared truth and higher transparency among all parties in the dairy industry.

The project spans from the grass production to the consumers’ glass of milk. All actors collaborate closer than ever before and use data from the full production cycle to optimize quality and save costs. The Tangle becomes the authenticator of each actor’s input (data set) and takes the role of a data pipeline for each actor to share and capture the data. A positive value is created once an ecosystem starts to behave as one organization with full visibility on all events and relevant data is generated by each ecosystem partner.

The initial drive was to ensure full transparency of all input in the process from the grass to a glass of milk. The expectation was to enhance understanding of how a glass of milk is most effectively produced. We linked the following data to advise on the most efficient production process across the many stakeholders involved:

Data from the fields, the fertilizers used and the quality of the round bales of grass Data from the individual cows consuming the fodder Data with the quality and quantity of the milk produced

The potential for additional gains is enabled by shared access to data. The visibility of the quality of fodder (the round bales of harvested grass) enables better prediction of the milk quality produced at every farm, which can ultimately impact the logistics planning of pick-up milk trucks (as milk is organized and stored accordingly to different levels of quality). Better logistics planning can potentially mean less time and costs spent! Ensuring ...

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