IOT IN SMART AGRICULTURE: A SYSTEMATIC REVIEW AND CLASSIFICATION OF TECHNIQUES AND GAPS
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Abstract
IoT technologies are reshaping agricultural practices by supporting real-time data analysis and intelligent automation. This paper presents a systematic review and classification of recent IoT-based techniques in smart agriculture, focusing on applications such as smart irrigation, disease detection, and environmental monitoring.
Ten research papers published between 2019 and 2025 are analysed to identify common architectures, core technologies, and implementation strategies. The review highlights the role of sensors, microcontrollers, wireless protocols, and mobile/cloud platforms in building intelligent farming systems. It also explores emerging trends like edge AI and predictive analytics.
The paper concludes by discussing key challenges including energy inefficiency, interoperability issues, and low adoption rates, and outlines future directions for building robust, secure, and scalable IoT ecosystems tailored to agricultural needs.
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