Open weather data evaluation for crop irrigation prediction mechanisms in the AUGEIAS project

Abstract

Treated wastewater reuse is increasingly important for efficient and sustainable management of water resources due to increased water demands. Motivated by the above, AUGEIAS proposes an Internet of Things (IoT) approach for clean and treated wastewater usage in precision agriculture. In this context, real-time measurements for wastewater treatment plant and field are correlated with open data to improve crop water needs prediction mechanisms. This paper presents the open weather sources that are used and evaluates their reliability. After the open data is evaluated, it is integrated with the data collected by IoT sensors/devices. By using the mean absolute percentage error metric, we evaluate the forecasting performance of open weather sources. According to our study, OpenWeatherMap’s forecast data proved more accurate, with a success rate at 83.3%.