Romanian Pilot

Pilot Leader

Contributors

Field Crops Monitoring

The pilot focuses on edge computing to process agriculture data near its source to overcome limitations of cost, timeliness, and privacy associated with cloud-based processing. The pilot in rural Southern Romania aims to assist farmers in reducing production costs by providing data on crop uniformity, water levels, and weather-related damages. The key performance indicators (KPIs) include reduction in latency, automation, uniform management of infrastructure, energy optimization, data security, and the development of a decision support system tailored to farmers in rural communities.

Pilot's Technology

 The AGRARIAN Pilot 2 focuses on field crop monitoring through an integrated edge farming infrastructure that leverages a dynamic, programmable environment combining satellite, aerial, and ground data. The core innovation lies in the development of advanced algorithms that provide real-time recommendations and alerts for critical agricultural activities such as sowing, irrigation, pest control, and treatment applications. These algorithms use weather station data, soil parameters, and crop-specific growth models to trigger actions that optimize yield and resource usage.

 Key technologies include soil heat accumulation models for determining sowing windows, DTT and HTT models (daily and hourly thermal time) for growth stage monitoring, and pest development forecasting based on GDD (growing degree days). For irrigation, the system calculates crop evapotranspiration and compares it with soil water levels to provide precise watering alerts. All computations are dynamically adjusted using sensor input and weather forecasts, ensuring accuracy and relevance. The platform enables data-driven decisions that increase crop efficiency while reducing water and chemical inputs.

Challenges

Calibration

Accurate calibration of soil temperature and moisture sensors for diverse field conditions.

Weather Forecast

Integration of real-time weather forecasts with locally collected data.

Modelling

Designing crop-specific models adaptable to varying regional practices.

Interface

Ensuring farmer-friendly interfaces despite the system's technical complexity.

Results so far

  • Identification of test farms and installation of weather stations – ✔️
  • Farmer consultations and KPI definition – ✔️
  • Algorithm development for all four functionalities – ✔️
  • Public presentations to farmers and stakeholders – ✔️
  • Integration with app platform – In progress
  • Field demo sessions – In progress
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