DEVELOPING IOT-BASED ADAPTIVE NETWORK MECHANISMS FOR ENHANCING RELIABILITY IN SMART FARM SYSTEMS

Abstract

The integration of the Internet of Things (IoT) in smart farming has revolutionized agricultural practices by enhancing efficiency, productivity, and sustainability. IoT technologies enable real-time monitoring and management of farming operations through a network of interconnected sensors and devices. However, the reliability of these networks is critical to the success of smart farming systems. Challenges such as node failures, environmental interferences, and high data traffic can significantly impact network performance, leading to data loss and increased latency. This research addresses these challenges by developing IoT-based adaptive network mechanisms designed to enhance network reliability in smart farm systems. These mechanisms include dynamic routing algorithms and fault detection and recovery protocols that adjust to real-time network conditions, ensuring continuous and efficient data flow. The key findings from both simulated environments and real-world field tests demonstrate that the proposed adaptive network mechanisms significantly improve data transmission success rates, reduce latency, and increase network throughput compared to traditional static routing protocols. These improvements ensure robust and reliable connectivity, essential for the continuous monitoring and automation of smart farming operations. The contributions of this research lie in the development and validation of adaptive network mechanisms that enhance the reliability of IoT-based smart farming systems, supporting the advancement of precision agriculture and contributing to more sustainable and productive farming practices.