IoT and Machine Learning Based Affordable Smart Farming

An breakthrough technology called the Internet of Things (IoT) provides workable and dependable solutions for the modernization of a few locations. Systems based on the Internet of Things are being created to monitor and maintain horticulture farms with the least amount of human intervention. The proposed model is a framework for a smart water system that predicts how much water will be needed for a harvest using machine learning analysis. The three most crucial factors to consider when estimating how much water will be present in a given farming area are wetness, temperature, and moistness. Agriculture is one of the most important factors in the economic development of any country. In many non-industrialized nations, horticulture plays a significant and critical role in the development of their economies. India, one of the world's top producers of vast quantities of various harvests, genuinely employs conventional agricultural methods. Ranchers must increasingly produce more food of the highest quality while simultaneously coping with challenges associated to climate change adaptation. IoT-based and machine learning-based smart horticulture would help ranchers by continuously monitoring their crops and providing advice on harvesting and composting. This study's major objective is to provide a Smart Agribusiness framework based on the Internet of Things (IoT) that would help ranchers by providing recommendations based on a variety of variables, such as temperature, pH, wetness, and precipitation.