Smart Irrigation Systems using (IoT) – A Survey

Abstract

In India a very vast population is dependent on farming activities and most of them still uses traditional methods of irrigation. Water availability plays main role in this sector. As the world is advancing and population of India is on the rise scarcity of water is becoming a common problem in most part of the country. This survey paper provides a comprehensive overview of smart irrigation systems, focusing on their integration with IoT, deep learning, sensors, and AI to optimize agricultural practices. The paper conducts an extensive literature review, exploring challenges and opportunities in the domain, including IoT applications in agriculture, deep learning techniques, sensor technologies, and AI-driven decision-making. The methodology involves developing and integrating key components like sensor deployment, data collection, deep learning model training, and AI-based decision-making algorithms. Performance evaluation compares the system's effectiveness with traditional methods, analyzing irrigation decisions, water consumption, crop yield, and water conservation. The results demonstrate how the smart irrigation system optimizes water usage, maintains optimal soil moisture levels, and improves crop health, leading to increased agricultural productivity and reduced water waste. Overall, this survey paper contributes valuable insights for researchers, practitioners, and policymakers, emphasizing the potential of IoT, deep learning, sensors, and AI in revolutionizing agriculture and promoting sustainable and efficient irrigation practices to address water scarcity challenges. Keyword:- IoT(internet of things), ML (Machine Learning), LDR(light dependent register), DHT (Dihydrotestosterone)