Meta-Analytical Approach of ML, IoT and Nanotechnology for Plant Disease Detection towards a Sustainable Agriculture

Abstract

This review article examines various technologies, such as Machine Learning, the Internet of Things (IoT), and Nanotechnology, that have the potential to address plant disease detection issues and provide sustainable long- term solutions. In addition, how these strategies can be integrated into precision agricultural practices to enhance crop health and productivity has also been discussed and analyzed. This meta-analysis aims to contribute to the advancement of agriculture and facilitate informed decision-making by stakeholders         in             the          industry. A thorough understanding of the present landscape of plant disease detection and the challenges that persist can lead to innovative solutions that guarantee the long-term viability of agriculture. This presentation will provide an in-depth overview of current research, highlighting the latest technological advancements and strategic approaches that have the potential to revolutionize the identification and control of plant diseases in agricultural systems.