Resumen del producto

The designs of homemade weather and soil monitoring stations for recording, processing, calibration, and forecasting applications like sustainable agriculture, have shown significant improvements. The quick technological development has facilitated the adoption of low-cost air/soil sensors to obtain databases. Hence, current investigations are focused on improving the accuracy of both weather/soil measurements and their spatial-temporal predictions. Advanced approaches in forecasting models based on mathematical, statistical, and artificial intelligence methods have been proposed to calibrate air/soil sensors to obtain reliable and useful records. These records have been used to predict weather/soil conditions and future nutrient and pollutant levels by the union of two or more (hybrid) forecasting methods and different sensors in weather/soil stations. Based on published research papers, statistical analyses, and data mining (hierarchical cluster), the document comprehensively discusses the main technological configurations, applications, trends, quality, and research needs for further advancements in recording and forecasting air/soil variables.

Abstract del producto

The designs of homemade weather and soil monitoring stations for recording, processing, calibration, and forecasting applications like sustainable agriculture, have shown significant improvements. The quick technological development has facilitated the adoption of low-cost air/soil sensors to obtain databases. Hence, current investigations are focused on improving the accuracy of both weather/soil measurements and their spatial-temporal predictions. Advanced approaches in forecasting models based on mathematical, statistical, and artificial intelligence methods have been proposed to calibrate air/soil sensors to obtain reliable and useful records. These records have been used to predict weather/soil conditions and future nutrient and pollutant levels by the union of two or more (hybrid) forecasting methods and different sensors in weather/soil stations. Based on published research papers, statistical analyses, and data mining (hierarchical cluster), the document comprehensively discusses the main technological configurations, applications, trends, quality, and research needs for further advancements in recording and forecasting air/soil variables.

Palabras clave

Weather forecasting, Soil forecasting, monitoring station, data mining, artificial intelligence