A Novel Rel-DASA Model for Reliable Data Analysis in IoT Based Smart Agriculture

Abstract

Agriculture today depends largely on these technologies to supply food for human consumption because to their widespread usage. The Internet of Things bridges the gap by providing farmers with critical tools to predict crop growth, availability of moisture in the soil, soil status, and so on. We describe a comprehensive agricultural monitoring system for accurate crop growth management. This proposed research investigates how supplying farmers with real-time data such as weather forecasts through sensor integration might enhance decision-making. Internet of Things, Agricultural Sensors, Wi-Fi Module, Android App, and Raspberry Pi are all integrated.