A Machine Learning Perspective to foster Accuracy and Prediction of Urbanization using Automatic Weather Station

Abstract

Farmingis largely dependent on the climate. Additionally, poor climatic information seriously impairs both the amount and quality of crop production. However, IoT technologies let you know the current weather conditions. The agricultural fields have sensors installed both inside and outside of them. They gather environmental information that is utilized to choose the best crops for specific climatic circumstances. The entire Internet of Things (IoT) ecosystem is made up of sensors that are highly accurate at detecting real-time meteorological conditions like humidity, rainfall, temperature, and more. Numerous sensors are available to detect each of these factors and can be set up to meet your needs for smart farming. These sensors keep an eye on the state of the crops and the surrounding weather. Organizations and communities may create smart surroundings thanks to weather stations powered by LoRa. This weather station is being developed in India for smart agriculture for helping farmers to increase crop productivity. The following modules include the LoRa WAN Outdoor Gateway along with the following sensors CO2/PM2.5/PM10, Wind Direction & Speed, Rain Gauge, Rain and snow Detect sensor, Temperature, Humidity, Illuminance, Pressure, Total Solar Radiation, PAR (Photosynthetically Available Radiation).