AgriDataValue – Environmental Data Useful for Smart Irrigation

AgriDataValue aims to establish itself as the “Game Changer” in Smart Farming digital transformation and agri-environmental monitoring, and strengthen the smart-farming capacities, competitiveness and fair income by introducing an innovative, open source, intelligent and multi-technology, fully distributed Agri-Environment Data Space (ADS). To achieve technological maturity, fast and massive acceptance, AgriDataValue adopts and adapts a multidimensional approach that combines state of the art big data and data-spaces’ technologies (BDVA/ IDSA/ GAIA-X) with agricultural knowledge, monetization, new business models and agri-environment policies, leverages on existing platforms, edge computing and network/ services, and introduces novel concepts, methods, tools, pilot facilities and engagement campaigns to go beyond today’s state of the art, perform breakthrough research and create sustainable innovation in upscaling (real-time) agricultural sensor data, already evident within the project lifetime.

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This dataset contains IoT environmental data useful for developing a smart irrigation ML model. These data files were provided from Pilot 18 of AgriDataValue.

The files “P18_BIORO_WeatherStationData_AgriDataValue_2024″ and “P18_BIORO_WeatherStationData_AgriDataValue_2025″ include the following features:

• air temperature
• air humidity
• air pressure
• dew point
• precipitation
• earth humidity (soil moisture)
• earth (soil) temperature

The excel file P18_BIORO_WeatherStationData_AgriDataValue_2024 contains two tabs, the first one (3233333332303334) is about a field seeded with Sorghum (Jumbo Star variety), and the second one (3233333332303335) is about a field seeded with Corn (Forturio variety). The excel file P18_BIORO_WeatherStationData_AgriDataValue_2025 also contains the same two tabs but both of them are about a field seeded with Corn.

Along with the Pilot 18 provided data, some more excel files are included to the dataset; these are data requested from OpenMeteo. In order to compute Evapotranspiration, a necessary parameter for the computation of the optimal amount of irrigation water for a specific crop, some more features were needed so the solution of getting them from OpenMeteo was chosen. 

OpenMeteo data were requested giventhe latitude and longitude of the two fields seeded with Corn, 4599-2049 and 4598-2047 respectively.