Development of an IoT based smart potato leaf diseases monitoring and controlling system with image processing

Abstract

Potato (Solanum tuberosum L.) is a key crop and a major source of livelihood for a vast population of the world after wheat and rice. However, diseases have diverse effects on potato fields, leading to damage to crops and reducing crop production. The two major diseases that afflict potato plants are referred to as early blight and late blight. Protection of this crop yield from blight diseases is one of the foremost challenges. Therefore, detection of these leaf diseases at appropriate time is very essential to prevent the damage. This study intends an Internet of Things (IoT)-based smart potato leaf diseases monitoring and control system that combines IoT technology with eco-sensing and image processing to identify and categorize these diseases. Studies have found that blight diseases are directly related to temperature and humidity of the planted area. This study measures environmental information using a sensor network installed in the planted area. After sensing and measuring environmental information, acquired values are displayed and farmers get these acquired values via message notification. The system obtains a 97% accuracy rate in recognizing these diseases by using our fine-tuned model of ResNet-50 for image processing.