Deep Learning-Based Automated System for Multi-Classification of Plant Diseases in Real-Time Environments

Agriculture provides food for the world's expanding population. Several developing nations are going through this period, and agriculture has been developed to fulfil the rising food demand. While agriculture seeks to feed the world's rapidly growing population, plant disease reduces the amount and quality of food, fiber, and biofuel crops. Although losses can be severe, they normally account for 42% of the yield of the six most important food crops. Managing illnesses costs farmers sometimes without enough professional assistance, which has unfavorable outcomes including pollution and subpar disease control. Deep learning algorithms are helping farmers all around the world identify and categories the illness. In order to identify disease in plant leaves, it employs techniques like Convolutional Neural Networks (CNN). This research discussed the preset and user specified models that were employed to identify diseases in plant leaves. We are transmitting the Driver circuit to power the pump motors to Arduino Uno using UART protocols. Determine the different soil types using an NPK sensor. At the end, we are using Arduino to control the motor model with a server motor.