I-FARM U: Internet of Things
Current farmers conduct manual scouting to determine field growing conditions and take appropriate actions whenever necessary. This activity is tedious, time-consuming, and subjective. Therefore, there is an urgent need to automate this process by providing farmers with smart data driven decision-making models or tools, which will inform them on what action to take based on the current field conditions. To do so, there is a need to collect a large amount of data to feed the model. Real-time remote-sensing techniques remain an efficient option to measure, collect and save large amounts of data that can be used for models and/or decision-making tools.
Things that can be measured in agricultural environments:
- Soil moisture content
- Leaf area index (LAI): amount of leaves
- Land surface temperature
- Plant growth, morphology, architecture, function, and composition
- Carbon and water fluxes
- Crop water use, crop nitrogen condition, crop yield
At the I-FARM testbed, we will mature real-time remote-sensing-based monitoring techniques and integrate them into decision support tools for farmers’ planning and management. Using these data, the My Farm app will advise precision farming actions including seed selection, reseeding, side-dressing, and cover-crop planting. This will be significantly faster, lower cost, and more precise than prevalent manual scouting techniques.
I-FARM will integrate the monitoring of field condition by combining ground-based soil sampling, IoT, and remote sensing. The following variables would be measured: soil carbon, soil bulk density, available N (NO3-N and NH4-N), P, CEC, pH, organic matter, other macro- and micronutrients, crop growth and soil conditions, soil temperature, soil and plant nitrate, canopy structure, leaf color and crop phenology, leaf nitrogen and chlorophyll contents. Finally, machine learning models trained on all these measurements/images will be integrated into a data-model integration to support side-dressing and cover-crop planting decisions.
Types of instruments
Moisture content measurement instruments
Leaf area index (LAI) measurement instruments
Land surface temperature measurement instruments
Crop water use measurement instruments