Improving Crop Recommendations with Augmented Reality and Sensor Data Analysis

Abstract

The decision about the selection of crops for agricultural production is closely related to many different aspects, such as the features of the soil and the surrounding environment. Using state-of-the-art sensor technology, these factors are measured with extreme caution, some significant metrics include soil pH, moisture level, and the surrounding temperature. These sensor-driven collected information are analyzed by expertly deploying robust machine learning algorithms, which leads to an accurate estimation of the best crop categories for the climatic circumstances. In this agricultural paradigm, augmented reality perceived as a game-changing tool that offers a fully immersive display of the sensor data, providing farmers an extensive awareness of the crop environment. In addition to automating the crop selection process, this smart combination of sensor technologies, machine learning with overall accuracy of 97%, and augmented reality offers farmers the insights they need to make appropriate choices and ensures sustainable agricultural practices.