Smart Agriculture: A Comprehensive Survey on IoT-Enabled Plant Disease Detection and Agricultural Automation

T. Thilagavathi, L. Arockiam, I. Priya Stella Mary
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Abstract

This research paper is dedicated to the comprehensive review and discussion of diverse techniques employed in plant disease detection within the realm of agriculture. Emphasizing notable contributions and showcasing innovative methodologies, the research work takes a critical turn to address the myriad issues and challenges intricately woven into the integration of IoT data analytics in agriculture. The paper meticulously unravels the complexities associated with plant disease detection in the era dominated by IoT and data analytics. Serving as more than just a repository of current methodologies and technologies, this work actively illuminates the challenges that await further exploration. The insights derived from this exploration will provide a substantial foundation for emerging researchers. By shedding light on the evolving landscape of plant disease detection and the nuances of IoT integration in agriculture, this paper empowers researchers to actively contribute to the resilience and sustainability of agricultural practices in the face of ongoing challenges.
智能农业:物联网植物病害检测与农业自动化综合调查
本研究论文致力于全面回顾和讨论农业领域中植物病害检测所采用的各种技术。研究工作强调了显著的贡献并展示了创新的方法,在农业物联网数据分析的整合中解决了无数错综复杂的问题和挑战。论文细致地揭示了在物联网和数据分析占主导地位的时代,植物病害检测的复杂性。这项工作不仅是当前方法和技术的宝库,还积极揭示了有待进一步探索的挑战。从这一探索中得出的见解将为新兴研究人员奠定坚实的基础。通过揭示植物病害检测不断演变的格局以及物联网在农业中整合的细微差别,本文使研究人员能够在面对持续不断的挑战时,为农业实践的适应力和可持续性做出积极贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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