Next-Gen Precision Agriculture: Integrating AI, IoT, and D2D Communications
Abstract
This chapter explores the synergistic integration of Artificial Intelligence (AI), the Internet of Things (IoT), and Device-to-Device (D2D) communications within the context of precision agriculture, a pivotal innovation aimed at enhancing farming efficiency and real-time decision-making. As global demands for food increase and the need for sustainable agricultural practices becomes more urgent, the convergence of these technologies offers a transformative solution. AI's capability for sophisticated analytics allows for predictive insights and enhanced decision-making. Concurrently, IoT devices facilitate comprehensive real-time data collection across various agricultural environments, and D2D communications ensure robust, immediate data exchange, which is crucial for operational efficiency and prompt responses in agricultural settings. The chapter outlines the applications, benefits, and challenges associated with implementing these technologies in agriculture. It discusses how AIdriven systems enhance crop monitoring and soil management, how IoT networks facilitate extensive data acquisition, and how D2D communications improve connectivity and system reliability. Furthermore, it addresses the integration challenges such as interoperability, security, and privacy, and proposes a framework for overcoming these barriers through standardization and best practices. Future directions, such as the implications of 5G technology and advanced AI models on agriculture, are also explored to highlight ongoing research and emerging opportunities. This comprehensive analysis not only underscores the significant enhancements that AI, IoT, and D2D technologies bring to precision agriculture but also emphasizes the necessity for continued innovation and interdisciplinary collaboration to realize their potential in modern farming practices.
Fields of Study & Subjects
Smart Agriculture and AI
Internet of Things and AI
Advanced Data and IoT Technologies
Publication details
- Journal / source
- BENTHAM SCIENCE PUBLISHERS eBooks
- Pages
- 174–196
- Publication date
- 14 January 2026
- Document type
- Book chapter