DESIGN AND IMPLEMENTATION OF IOT-BASED INTELLIGENCE SYSTEMS FOR AGRICULTURE: AN IRRIGATION AND SOLAR DRYING APPROACH

Abstract

The application of Internet of Things (IoT) technology to agriculture has transformed conventional farming methods in recent years, increasing sustainability, productivity, and efficiency. With an emphasis on irrigation control and solar drying procedures, this article offers a thorough design and implementation methodology for Internet of Things-based intelligence systems created especially for agricultural applications.

Throughout the agricultural fields, a network of connected sensors, actuators, and communication devices makes up the proposed system. These Internet of Things gadgets gather data in real time on a range of environmental factors, including solar radiation strength, temperature, humidity, and soil moisture content. The technology analyzes the gathered data and uses machine learning and advanced data analytics to give farmers automated decision-making tools and actionable insights.

For irrigation management, the IoT-based system optimizes water usage by dynamically adjusting irrigation schedules based on the current soil moisture conditions and weather forecasts. By precisely delivering water to the crops when and where it is needed most, the system helps prevent over-irrigation, minimize water waste, and improve crop yield.

Furthermore, the system incorporates solar drying technology to facilitate post-harvest processing of agricultural products. Solar drying units equipped with IoT sensors monitor and control the drying environment, ensuring optimal conditions for preserving the quality and nutritional value of the harvested crops. Through remote monitoring and control capabilities, farmers can efficiently manage the drying process, reducing dependency on conventional energy sources and enhancing the economic viability of agricultural operations.

The implementation of IoT-based intelligence systems for agriculture holds immense potential to address the challenges of food security, water scarcity, and climate change resilience. By empowering farmers with data-driven insights and automated control mechanisms, these systems contribute to sustainable agricultural practices and the advancement of smart farming technologies.