Detection of Organic Tomato Diseases and Monitoring of Climate-Soil Through a Combination of IoT, Big Data, and Machine Learning
摘要
The proposed system integrates various services into a common platform for digital agriculture, linking various IoT sensor nodes distributed in the field and connected via LoRaWAN technology to collect soil and climate data that will be processed using a kappa Big Data architecture to display the data collected by the sensors in real-time and provide control and monitoring of tomato crop through notifications to the farmer via a mobile application. In addition, the system offers the ability to detect tomato diseases, using an image-based classification model. This model is able to detect leaf diseases with an accuracy of 86%. The goal is to provide farmers with an accurate view of their crops and mitigate disease and environmental damage.