Lightweight CNN and blockchain integrated secured model for crop disease information system
by Neenu Johnson; M.B. Santosh Kumar; T. Dhannia
International Journal of Sustainable Agricultural Management and Informatics (IJSAMI), Vol. 10, No. 2, 2024

Abstract: Crop diseases are a major threat to the farming community that reduce yield and affect the income of farmers. Higher profitability, attaining sustainability, minimising workload, and economic development of the nation are the main driving forces for the adoption of smart farming technologies. Deep learning has emerged as an accurate tool for prediction and decision-making in smart farming. The integration of blockchain with deep learning is efficient in developing a secured data sharing framework. A crop disease data management framework that leverages the benefits of deep learning, blockchain, and interplanetary file system is proposed to assist farmers in crop disease detection and secure sharing of crop disease data. In the framework, a lightweight convolutional neural network architecture-based banana crop disease detection module is included that achieves an accuracy of 99.91%. A system architecture based on blockchain for the crop disease communication module is included to ensure secured crop data sharing.

Online publication date: Tue, 02-Apr-2024

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