Leveraging IoT and Machine Learning for Efficient Rice Stock Monitoring and Prediction

Recent technological advancements have made agricultural industry easier through the use of the Internet of Things (IoT). Many studies have been done to increase the adaptability of IoT in agricultural industries. IoT is mainly used as a tool to monitor and report data to a cloud server remotely. Those efforts are important to solve global challenges to produce 70% more foods, as the United Nation stated. To further solve those challenges, this paper tries to propose a comprehensive system to monitor the rice stock and forecast it for future use. This paper also shows that multivariable linear regression is an appropriate machine learning algorithm to forecast the rice stock. Furthermore, the forecast result is displayed in a web-based application built with Vue.js that exhibits a wonderful score when tested with Lighthouse.