Monitoring land parcels, sensor nodes and field data

“Farmers have already begun employing some high-tech farming techniques and technologies in order to improve the efficiency of their day-to-day work. For example, sensors placed in fields allow farmers to obtain detailed maps of both the topography and resources in the area, as well as variables such as acidity and temperature of the soil. They can also access climate forecasts to predict weather patterns in the coming days and weeks.” (1)

According to IBM an average farm can generate and collect half a million data points per day. This large and complex amount of data comes from very different sources such as private sensor nodes for microclimatic conditions, public nodes that publish general climate forecasts and pathogenic element spread, satellite imagery etc..
All these data can help farmers to improve yields and increase profits, but their meaning must be understood in order to make better decisions.
In this context maps connected to analytic tools are a really powerful solution capable of representing complex information in a simple and useful manner.

Organizational, functional and commercial network analysis for agri-food systems.
Model based analytics – Microsoft Power BI

Continuous data collection of local sensors on land parcels.
Data visualization (Microsoft Power BI)
Mapping and monitoring of private and public field devices in agri-food systems.
Data visualization (Microsoft Power BI)

(1) Andrew Meola, ”Smart Farming in 2020: How IoT sensors are creating a more efficient precision agriculture industry” BUSINESS INSIDER, March 2020.

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