Smart Irrigation System for Urban Gardening using Logistic Regression algorithm and Raspberry Pi

Abstract

Abstract People have shown an increasing interest in urban gardening. Irrigation is one of the common methods used to take care of the plant growth. However, the proper irrigation timing of plant is much unclear for most people. Moreover, the manual irrigation is impossible when people do not have physical access to the plant in a long period of time. Hence, a smart irrigation system using Raspberry Pi has been proposed to ease the irrigation. In this system, three different sensors, including moisture, humidity and temperature sensors are installed in the soil of the plant. The collected data from the sensors will be used to predict whether the plant need to be watered or not. This system implements a machine-learning algorithm called Binary Logistic Regression using Python library to test the accuracy of the system. The accuracy of the algorithm to predict the irrigation is 82%. The finding from this study is believed to be helpful as it may contribute to the development of better irrigation system.