International Journal of Agriculture Extension and Social Development

author(s)
Shoba H, Nagaraja G, Krishnamma PN and Sreedevi MS

abstract
Due to the expanding global population, agricultural techniques have had to evolve to meet food demand. Traditional approaches may be useful, but they lack efficiency, sustainability, and scalability. This has led the agriculture industry to investigate sophisticated technologies like IoT and AI, resulting in smart farming. IoT and AI in agricultural engineering are transforming the business by helping farmers maximize resources, boost production, and reduce environmental impact. IoT collects real-time data from agricultural sources including soil, weather, crop health, and equipment. Sensors around the farm continually monitor these factors, providing massive volumes of data that reveal agricultural ecosystem dynamics. IoT devices provide data to cloud platforms for analysis and interpretation. This integrated data collecting and transmission method underpins smart farming, enabling accurate agricultural monitoring and control. AI is crucial to turning data into intelligence. AI uses machine learning algorithms to identify data patterns and trends for predictive analytics and decision-making. Weather predictions and soil moisture levels may help AI models determine planting and harvesting periods. AI-powered systems may also identify plant illnesses, insect infestations, and offer focused remedies, minimizing broad-spectrum pesticide use. AI helps farmers make data-driven decision that boost crop yields, lower input costs, and improve farm management. Precision agriculture is a major benefit of combining IoT and AI in agricultural engineering. Precision agriculture involves micro-managing farms depending on local variables. Variable rate technology (VRT) applies fertilizers and water to specific field rather than the whole farm. Runoff and chemical usage are reduced, optimizing resource utilization and minimizing environmental effect. IoT and AI help agriculture maintain itself. Farmers may save water, minimize greenhouse gas emissions, and preserve soil health by monitoring and predicting environmental conditions. IoT sensors in smart irrigation systems assess soil moisture and weather conditions to modify water delivery in real time, ensuring crops to get enough water without waste. AI-driven analytics may also discover sustainable crop rotation patterns to reduce soil nutrient depletion and promote biodiversity.