Mobile Based Ayurvedic Leaf Detection and Retrieving Its Medicinal Properties Using Deep Learning and NLP

Authors

  • Rajasekaran Subramanian, Devika Rubi Rajasekaran, Saranya Seethamraju, Gunji Sai Charan, Bala Omkar Surampalli

Keywords:

Ayurveda, Medicinal Plants, Deep Learning, Image Processing, Inception V3, Flutter, ChatGPT, Translator Module

Abstract

The Indian ancient medical system AYURVEDA provides treatment to multiple diseases traditionally by using the parts of various medicinal plants which reduces the cost and side effects of Allopathy medicines. The Botanical Survey of India declared that India has around 8000 species of medicinal plants. Identifying the parts of the medicinal plants help the pharmaceutical industries and healthcare professionals for producing good medicines. This paper proposes a mobile based application to detect ayurvedic leaves and retrieving its medicinal properties using deep learning and NLP. The proposed application uses IneptionV3 for training and testing the images of 75 Indian medicinal species leaves in which each medicinal species consists of 1000 images makes a dataset of 75000 images. The model got an F1 accuracy of 95% and deployed in cloud so that it can be accessed anywhere. The application is integrated with ChatGPT to retrieve the medicinal properties of the detected leaves and has the facility to translate and listen the retrieved medicinal properties in English, Telugu, and Sanskrit.

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References

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Published

24.03.2024

How to Cite

Rajasekaran Subramanian. (2024). Mobile Based Ayurvedic Leaf Detection and Retrieving Its Medicinal Properties Using Deep Learning and NLP. International Journal of Intelligent Systems and Applications in Engineering, 12(3), 3561–3565. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/5992

Issue

Vol. 12 No. 3 (2024)

Section

Research Article

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