Plant Growth Analysis using IoT and Reinforcement Learning Techniques for Controlled Environment

Abstract

The Internet of Thing (IoT) plays a major role for improving the green house plant productivity and generates essential information to yields. Various existing systems introduces a smart approach that utilizes the IoT concept to remotely deliver users with data regarding temperature, humidity, and soil moisture severity. The purpose of this system is to track and evaluate plant circumstances. This paper descries a plant growth analysis using IoT and statical machine learning techniques for broccoli plants. Initially data has collected using IoT modules including various potential parameters such as soil temperature, soil moisture, humidity and plant height on daily interval basis. The experimental analysis has done in controlled environment for 30 days daily records. Finally, system recommends possible decides need to take for improve the yield or productivity.