Smart Farming using IoT and Machine Learning for Crop Monitoring and Disease Prediction

The involvement of the Internet of Things (IoT)in the agricultural field has introduced the new chances of involving the innovative adoption of the old farming strategies replacing them with the intelligent, information-oriented practices. In this work, authors present a smart farming system and Martoize it with the help of IoT technologies that provide real-time monitoring of the environment and automatize some significant farming processes. The offered system is based on ESP32 microcontroller which can support both Wi-Fi and Bluetooth and connect the chain of the sensors that measure the elementary parameter of temperature, humidity, soil water, amount of water. To support the various field situations, the system provides and installs systems such as fans, heating coils, electric water pump and plowing motors that automatically work with the reactions of sensors. This makes it possible to provide the best environmental management to ensure the crops with the best growing conditions. Mobile application is chosen as the user interface: it is developed through Blynk IoT platform and assists farmers in monitoring sensor values and accepting notifications and controlling equipment remotely. This enhances the ability of the farmer being in a position to manage the field when he is not at the field. The major advantage of the system is that it is simple to install and inexpensive particularly to the small and medium farmers who may not be in a position to access the expensive systems of farming. The ability of the technology to work across multiple farming sizes and types of crops is also provided by the modularity and scalability of the makeup. The system not only benefits in the increased production and use of resources in producing a better crop but also helps to maintain the farming practice by minimizing wastage of water and fertilizers. All roundly, this research can be applicable in advertising the idea of precision agriculture that will guarantee a reasonably economical system and an intelligent and automated agriculture equipment which will endure in line with the projection of food security and environmental appropriacy. The outcomes show the manners in which IoT can empower farmers with smart action and automatic response besides eventually growing another era of shrewd and persistent agricultures.