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

Authors

  • T. Thilagavathi Research Scholar, St. Joseph’s College (Autonomous), Affiliated to Bharathidasan University, Tiruchirappalli, 620002.
  • L. Arockiam Associate Professor, St. Joseph’s College (Autonomous), Affiliated to Bharathidasan University, Tiruchirappalli, 620002.
  • I. Priya Stella Mary Assistant Professor, St. Joseph’s College (Autonomous), Affiliated to Bharathidasan University, Tiruchirappalli, 620002.

DOI:

https://doi.org/10.59461/ijitra.v3i2.107

Keywords:

Internet of Things , Image processing , Machine Learning Classification , Artificial Intelligence , Agriculture , Plant disease

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.

Downloads

Published

2024-06-15

How to Cite

T. Thilagavathi, L. Arockiam, & I. Priya Stella Mary. (2024). A Smart Agriculture: A Comprehensive Survey on IoT-Enabled Plant Disease Detection and Agricultural Automation. International Journal of Information Technology, Research and Applications, 3(2), 39–47. https://doi.org/10.59461/ijitra.v3i2.107

Issue

Section

Regular Issue