Internet of Things based Weather and Water Quality Monitoring System

Abstract

Weather forecasting is a statistical analysis of an environment. It is widely used to predict the upcoming weather monitoring report. Weather is a climate in terms of temperature, air swing, rainfall, and cloud covering. Simultaneously, water quality was monitored by the turbidity level, and acid and base nature of water. This combination of weather forecasting and water quality management system is most useful for the applications such as Agrology, logistics transportation, and construction. Both the weather forecast and water quality management system were designed using machine learning algorithms. These hasty machine learning techniques are biased toward the modern Internet of Things, which is used to segregate and separate both the real-time and stored datasets. This proposed methodology is more beneficial for the field of agrology. This weather forecast helps to identify the soil's nature and environmental conditions. Water quality management helps to improve the yield and high protection for the crops. This proposed system is most eminent at the time of natural disasters. Using renowned sensors supports increases in the efficacy of the proposed system.