Abstract: In many tropical and subtropical areas, banana farming is an essential part of the agricultural economy. However, crop yield and quality are impacted by a number of diseases and environmental factors. In order to maintain plant health and increase productivity, early disease detection is essential. An AI and ML-based system for early disease detection and banana tree health monitoring is presented in this paper. To identify diseases and give farmers real-time feedback, the system makes use of deep learning and image processing techniques. To extract features and classify various banana leaf diseases, a convolutional neural network (CNN) model is used. The effectiveness of the suggested system in precisely identifying diseases and supporting decision-making for improved crop management is demonstrated by experimental results.

Keywords: Convolutional Neural Networks, AI, Machine Learning, Disease Detection, Banana Tree.


Downloads: PDF | DOI: 10.17148/IJIREEICE.2025.13411

Cite This:

[1] GOKULPRIYAN V, Dr. A. NIRMALA, "EARLY DISEASE DETECTION AND BANANA TREE HEALTH MONITERING SYSTEM USING MACHINE LEARNING," International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering (IJIREEICE), DOI 10.17148/IJIREEICE.2025.13411

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