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Enhancing Agricultural Practices Through IoT: A Dual-Modality Approach for Network Resilience and User Engagement

Abstract

In the realm of smart agriculture, integrating Internet of Things (IoT) technologies promises to revolutionize traditional farming practices. However, challenges such as network unreliability in remote agricultural settings and the need for user-friendly, real-time monitoring and control systems persist. This paper presents an innovative IoT-based system that addresses these issues through a dual-modality approach: integrating edge-level decision-making for continuous operation during network disruptions and cloud-based monitoring and control via user-friendly desktop and mobile applications. Employing LoRa and LoRaWAN for efficient long-range communication, the system showcases resilience in challenging network environments, ensuring uninterrupted agricultural management. The implementation includes sophisticated sensors for accurate data collection and integrates with the Loriot platform for seamless data management. Results from controlled testing environments confirm the system's reliability in sensor accuracy, communication efficiency, and seamless transition between cloud and edge computing. The development of intuitive applications further enhances the system's practicality, offering farmers enhanced control and real-time insights into soil conditions. This research contributes significantly to the advancement of smart agriculture, demonstrating a comprehensive, adaptable, and user-friendly solution for modern farming challenges.

Research topics

  • Smart Agriculture and AI

Sustainable Development Goals

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DOI: 10.1109/mi-sta61267.2024.10599760

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