Innovative IoT-driven solutions for real-time crop health surveillance and precision agriculture
Priya Chugh, Suman Kumar Swarnkar, Purushottam Kumar
Abstract
The combination of Internet of Things, or IoT, devices for crop health surveillance is investigated in this study, with an emphasis on environmental factors and soil analysis. By using cutting-edge algorithms, the project seeks to improve precision agriculture methods by offering up-to-date information on disease detection, nutritional status, and soil water content. A wireless sensor system equipped with many sensors, including soil water content; humidity, including humidity gauges; and levels of nutrients sensors, including observation cameras, is deployed as part of the setup for the experiment. Amazon Web Services (AWS) IoT Analytics is used for handling and analyzing the data, showcasing the effectiveness and scalability concerning cloud-based technologies. The suggested methods address automated sprinkler control, recognizing illnesses by picture classification, nutrient level calculation, and calibration of soil moisture. Algorithms for calibration guarantee precise observations, and nutrient assessment offers useful information about soil fertility. Machine learning-based disease diagnosis systems demonstrate a 92% reliability rate. Water efficiency is enhanced by the computerized irrigation regulation algorithm, which maintains ideal soil moisture conditions. The study’s uniqueness is emphasized by comparison with already-available software products, as well as the accuracy and dependability of the system are evaluated through performance indicators. The study offers a thorough comprehension of the ways in which IoT sensors, computer programs, and cloud-based tools work together, adding to the precision agricultural landscape’s ongoing evolution.