IoT-Based Smart Agriculture Monitoring System

Abstract

farmer manually collects data from the farming fields in a traditional agriculture system. Sometimes these data may not be accurate, and the collection process is time and human labor-consuming. Also, during irrigation, water is tremendously wasted. Eventually, an Internet of Things-based smart agriculture monitoring system can reduce manual labor and water wastage. In this proposed system, a Node MicroController Unit integrates all of the sensors and sends the sensors’ data to an Internet of Things-based cloud framework known as Adafruit IO. Adafruit IO stores all the sensors’ data. A soil moisture sensor acquires the moisture data of the farm field. The acquired moisture data is in a percentage value. 0% means no moisture content, and 100% indicates high moisture content. Depending on the moisture content, a message is sent automatically to the user to turn On/Off irrigation. Through Adafruit IO, a user can control the irrigation process remotely. A waterproof temperature sensor is employed to measure soil temperature, and a temperature and humidity sensor measures the temperature and humidity of the surrounding environment of the farming field. The temperature-related sensors measure temperature in the Celsius unit, and the humidity sensor measures the humidity content in percentage. An air quality sensor reads the air quality of the farming field, and the output data of the air quality sensor is in a percentage value. A barometric pressure sensor measures the sudden change of atmospheric pressure in this system, which can help predict rainfall. The output result of the barometric pressure sensor is in the millibar unit. In this proposed system, a light-dependent resistor measures the amount of light. Consequently, the analyzed data can predict suitable actions for the farming field.