Paper Contents
Abstract
The rapid growth in the Internet of Things and Artificial Intelligence has transformed smart griculture in terms of providing for precise, data-driven management of resources in areas such as water, agrochemicals, and pest control. IoT-based wireless sensors and AI technologies provided farmers with real-time insight into field conditions to allow outcome predictions and autonomous deployments for machinery to garner better efficiency and crop yield. This paper mainly focus on new emerging technologies that are related to IoT-based smart agriculture and also describes challenges and future trends in the integration of IoT with traditional farming practices. A new variant of soft computing algorithm such as Differential Evolution is used to optimize Quality of Service (QoS) management in IoT applications, specifically focusing on energy harvesting and sensor coverage in smart agriculture. This proposed approach outperforms existing methods in terms of delay, service cost, and network coverage. Its contribution is significant as it addresses current technological limitations and provides insights for future research in IoT-based smart agriculture.
Copyright
Copyright © 2024 TUMMALA SUJITH CHOWDARY. This is an open access article distributed under the Creative Commons Attribution License.
