Weather Monitoring and Prediction System based on Machine Learning and IoT

Abstract

The weather may have a considerable influence on people’s lives. Changes in the weather have the potential to have an impact on a diverse variety of human activities, including agriculture and transportation. The traditional weather and soil monitoring technologies are erroneous and costly, thus accurate and low-cost technologies are still required. The objective of this study is to monitor and review the current weather conditions to keep people up to date with the latest information and allow for the timely implementation of preventative measures if a disaster is anticipated. Arduino is an open-source electronic device creation platform that is based on the amalgamation of hardware and software components that can be freely and flexibly modified to fulfill the needs of the project. The weather forecasting device is used for monitoring weather conditions, more precisely the temperature, humidity, and moisture content of the soil, from which the user gets real-time weather conditions of the place to take necessary actions accordingly, like watering plants, acting against increased LPG or certain gas content in the atmosphere, and many more. After training and testing of results, it follows that the accuracy of weather monitoring does increase and is a better option for increasing datasets. Furthermore, the low cost of the device makes it easily available to farmers.