Abstract: Precision farming is essential for optimizing resource use and improving crop yields to attain sustainable agriculture. However, challenges like data insecurity, fertilizer costs, and inadequate consideration of soil health pose a hindrance to achieving these goals. To overcome these issues, the proposed work presents a novel approach for optimizing fertilizer dispensing by developing a framework connecting IoT and blockchain with a community of greenhouses. The system consists of IoT sensors installed inside the greenhouses to measure soil pH and nutrient values. This collected sensor data is compressed and stored securely and in an off-chain manner by the IPFS (Inter-Planetary File System) hash using the Keccak-256. MetaMask transfers the data for blockchain registration and authentication. The data is then preprocessed using Z-score normalization, Label Encoding, and One-Hot Encoding to obtain a precise analysis. A Deep Learning-based Convolutional Neural Network (DL-CNN) is used to classify soil conditions and determine the appropriate fertilizer requirements. The results of the DL-CNN model are viewed in a dashboard through a Decentralized Application (D-App) that we developed to provide real-time information to consumers, field analysts, and agricultural organizations. Field analysts use the information to establish a control center for precisely applying fertilizers. The proposed method achieves a classification accuracy rate of 98.86%, thus increasing soil health and providing a solution for effectively managing fertilizers.

B. C. Preethi, G. Sugitha and T. B. Sivakumar, “Optimized Fertilizer Dispensing for Sustainable Agriculture Through Secured IoT-Blockchain Framework” International Journal of Advanced Computer Science and Applications(IJACSA), 15(9), 2024. http://dx.doi.org/10.14569/IJACSA.2024.0150927

@article{Preethi2024,
title = {Optimized Fertilizer Dispensing for Sustainable Agriculture Through Secured IoT-Blockchain Framework},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0150927},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0150927},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {9},
author = {B. C. Preethi and G. Sugitha and T. B. Sivakumar}
}