Basis-IoT

Le résumé fourni par la source

Smart farming is revolutionizing agriculture by incorporating state-of-the-art technologies to enhance decision-making, production, and resource efficiency. In countries such as India, where agriculture plays a pivotal role in the national economy, traditional irrigation practices are often inefficient and labor-intensive, particularly under conditions of water scarcity and unpredictable rainfall. New technologies such as software-defined networking (SDN) and the Internet of Things (IoT) have shown promise in automating irrigation systems through sensor-driven, real-time decision-making. To further enhance the reliability, security, and intelligence of such systems, this chapter explores the integration of blockchain and artificial intelligence (AI) into SDN-enabled IoT irrigation networks. Blockchain ensures data immutability, transparency, and decentralized trust, which is critical for managing shared agricultural resources and recording sensor data and control decisions. AI enables predictive analytics, adaptive irrigation scheduling, and intelligent fault detection based on historical and real-time data streams. The proposed model leverages AI for optimizing irrigation decisions and blockchain for secure and auditable data exchange among stakeholders, including farmers, government agencies, and IoT infrastructure providers. This chapter discusses the architecture, design requirements, and operational benefits of the AI–blockchain–IoT-integrated approach. It also addresses scalability, data privacy, and decision autonomy as critical enablers for sustainable, data-driven agriculture at scale. This chapter discusses the need for SDN-based IoT technology integrating the blockchain framework for smart irrigation systems on large-scale agricultural land. The work proposes the architecture for an SDN-based IoT model for a smart irrigation system. The different SDN components and their importance with usability in the smart irrigation system are portrayed along with the different issues and possible solution approaches in SDN-based IoT smart irrigation systems. Finally, the network performance is presented through the simulation.

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