Real Time Application of IoT for the Agriculture in the Field along with Machine Learning Algorithm

Abstract

With the daily increase of Internet of Things(IoT) devices, which have reached tens of billions these days. The term IoT has become popular and available in our daily life even if we sometimes don’t know and feel that. This work presented a friendly IoT system to help farmers, especially in the rural areas to visualize their farm data remotely, results in saving time, increasing crops productivity, and irrigating precisely. Everyone is capable to cultivate with the help of this system, contributing in solving issues like farmers leaving agriculture for mining. The design is done by using Blynk IoT platform to connect the physical devices in the field with the user mobile application, which makes the farmer visualizing the data. Raspberry pi 3 is the controller that is responsible for all processes such as sending and receiving the data with the help of sensors of temperature and humidity, soil moisture, pH, Passive Infrared (PIR), and camera, in addition to water pump as an actuator. This system capable to perform three operations, firstly auto irrigation, which will help in watering crops precisely and saving water. Secondly, suggesting fertilizers based on the soil’spH level helping farmers in determining the suitable fertilizers. Finally, objects detection, if there is any motion in the field, the system directly informs the user with a notification in the mobile application, and simultaneously the camera captures objects and the machine learning algorithm responsible for detecting the objects and tells the user via mobile application exactly which type of an object.