Fine Tuning and Tools Development for Plantain Grove Protection Using Iot and Machine Learning

Abstract

Agriculture plays a vital role in a country’s economy. In agriculture banana groves are as important as paddy fields. It is difficult for the farmers to protect their banana groves from natural disasters like wind, heat and flood. In order to protect the banana groves from natural disasters we provide a modern solution using Machine learning and IoT. In this project we will be calculating the temperature , sunlight intensity , pH level of the soil, moisture content in the soil and air, level of the water, amount of water should be delivered in hour basis with the help of sensors and speed and direction of wind using wind and pressure level sensors and all the calculated values are displayed in LCD display . These data are collected and processed by using machine learning algorithms for future predictions . It will give alert message and Buzzer if the temperature level goes above 95’F and below 22’F(the plant growth will be slow) so that we can reduce the temperature by using pump irrigation method . For instance 4000 plantain can be planted in a acre of land(square planting) which needs around 950 litres for 1 hr, if water level increases or decreases for a certain amount of time it will leaves a alert message and buzzer so that we can protect our trees from rotting. Plantain tress also gets damaged by the speed of wind i.e if 30 mph will break stalks attaching the leaves, wind of 40mph can break the main stem and winds of 60mph can topple the whole stands of banana plants, if the speed of the wind goes above the respective speed given above it will gives an alarm so that we can do some measures to protect the plantain trees. The pH sensor is used to display the pH value in LCD display and also suggest Fertilizers and Pesticides according to the pH value. By the using Arduino we are installing pump which retrieve and release water in the field . In the existing project they have SMT32 controller which works only in 0° and in 180° but we use Arduino which is more efficient than SMT32 controller and we also gives notification when the value of wind and temperature goes high, and predict it using Machine Learning.