Smart Groundwater and Weather Sensors

Developing a web-based system for agrometeorological and groundwater measurements to ease the transfer of information between different farm applications and smoothen the uptake of precision agriculture.

Concept

Precision farming relies on the collection, storage, sharing and analysis of spatially referenced data. To be used effectively, information must be transferred between different components of the complex farm environment which encompasses hardware and software with various standards. Since these data flows currently present a hurdle to the uptake of precision agriculture, this Flagship Innovation Experiment (FIE) aims to develop a web-based system for the integration, transformation and utilisation of large amounts of data from agrometeorological and groundwater measurements.

Implementation

The application of this information will significantly optimise the intervention time on agricultural farms. Thus, it will support operations on farms by providing alerts based on accurate data analysis. For each different farm operation, a data model alongside cloud application - capable of storing, analysing and publishing both sensor data and relevant spatial information - will be at the end-users disposal. In addition to that, the technology will provide insights on precise climate conditions and vegetation status based on satellite data from groundwater monitored wells. This information will be used to give recommendations for fertiliser application during the season and to plan other necessary interventions. 

Lessons learnt:

Main lesson learnt is related to technical issues. They were related to the development of analytics components where integration of different datasets and types of data from different data providers and preparation of services was complex.  

Another technical lesson was due to measurements of groundwater. When the whole 2019 and 2020-seasons’ level of water was lower than anybody expected, any practical measurements were not obtained. The main season was measured by meteorologic sensors and soil sensors.