IoT-driven smart agricultural technology for real-time soil and crop optimization
Hammad Shahab, Muhammad Naeem, Muhammad Iqbal, Muhammad Aqeel, Syed Sajid Ullah
Abstract
• Introduces an innovative IoT-based system that optimizes water and fertilizer usage through real-time soil condition monitoring. • Integrates AI for data-driven decision-making, ensuring precision in farming practices. • Provides real-time insights for effective soil nutrient management. • Demonstrates scalability for diverse agricultural environments, enhancing sustainability and efficiency across various farming settings. To address world food and agricultural sustainability, the UN's Sustainable Development Goals (SDGs) place strong emphasis on a transformative agricultural sector. By 2050, there will be about 10 billion people on the planet, making it imperative to increase about 60 percent in food production efficiency and security in order to meet the growing population's demands. In this critical situation, IoT-based smart farming offers a promising solution that can achieve 12 SDGs out of 17. This study unveils a groundbreaking Internet of Things (IoT) system designed to revolutionize agricultural practices by providing real-time monitoring of soil parameters, including temperature, moisture, salinity, EC, pH, nitrogen, potassium, and phosphorus levels. Field testing conducted with rice crops in Rahim Yar Khan, Pakistan, demonstrated the system's remarkable ability to accurately measure all eight critical parameters. The soil analysis showed a temperature between 30.5 °C and 33.2 °C, a moisture content between 60.6 % and 94.1 % and a pH value between 7.13 and 8.33. Nutrient content varied with nitrogen (71–103 mg/kg), phosphorus (15–19 mg/kg), and potassium (101–141 mg/kg). Leveraging this data, an AI-driven mobile application was used to deliver best recommendations for optimizing crop management, particularly in fertilization, irrigation and disease diagnoses practices. By integrating advanced IoT technologies, cloud computing, predictive algorithms, and a smart soil sensor, this system revolutionizes agriculture by enabling real-time monitoring of critical factors influencing rice crops metabolism. It empowers farmers with data-driven insights to enhance productivity, optimize resource use, and improve sustainability. This scalable solution addresses modern agricultural challenges by reducing environmental impact and strengthening crop resilience. Focused on unlocking the potential of data-driven decision-making, this research paves the way for sustainable, smart farming practices to meet the growing demands of a rapidly increasing global population.