Abstract
Agriculture growth is the key component in socioeconomic growth of our country due to liberalization and globalization. Gradually with significant increase in technology, advanced telecommunication services assist plant disease treatment at remote locations. Earlier systems were designed for either monocot or dicot plant family disease detection. The paper proposes an integrated approach for monocot and dicot plant disease detection and treatment along with precautionary measurement through smartphone and image processing techniques. The paper mainly focuses on plant disease detection technique based on integrated approach of K-means segmentation algorithm and SVM Classifier. The proposed and developed approach gives 83 % accuracy for plant diseases recognition.
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Acknowledgments
The authors are grateful to Mr. Shrihari Hasabnis for data collection. The authors would like to thank the referees for their helpful comments.
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Anjali Chandavale, Suraj Patil, Ashok Sapkal (2017). Agri-Guide: An Integrated Approach for Plant Disease Precaution, Detection, and Treatment. In: Satapathy, S., Bhateja, V., Joshi, A. (eds) Proceedings of the International Conference on Data Engineering and Communication Technology. Advances in Intelligent Systems and Computing, vol 469. Springer, Singapore. https://doi.org/10.1007/978-981-10-1678-3_78
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DOI: https://doi.org/10.1007/978-981-10-1678-3_78
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