Authors :
Johani D. Basaula; David Austin L. Aguilar; Charletsone Maru; Jireh Joshua Pablo; Katsuya Shiong Suzuki; Arnel Balasta
Volume/Issue :
Volume 9 - 2024, Issue 5 - May
Google Scholar :
https://tinyurl.com/m7h2cx39
Scribd :
https://tinyurl.com/2p9se4f9
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24MAY2456
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
This study aims to develop and implement an
herbal medicine scanner. HerbID, with its approach, has
sparked a growing interest in remedies for their healing
properties in today's world. This state of the art technology
introduces an identification system that is reshaping how
we engage with medicine. By combining a repository of
solutions, with advanced scanning capabilities HerbID
ensures a seamless user experience. Through a scan users
can precisely recognize herbs empowering them to make
informed choices regarding their health and overall
wellness. HerbID offers more than identifying herbs – it
offers in depth insights into the benefits, potential
advantages and usage tips for each herb. With HerbID you
can gain the knowledge and confidence to make the most
of medicine whether you're a beginner or well versed in
natural healing practices. Explore a range of remedies,
with HerbID your go to herbal medicine companion.
References :
- Raclariu-Manolică, A. C., Mauvisseau, Q., & de Boer, H. J. (2023). Horizon scan of DNA-based methods for quality control and monitoring of herbal preparations. Frontiers in Pharmacology, 14, 1179099
- Klein-Junior, L. C., de Souza, M. R., Viaene, J., Bresolin, T. M., de Gasper, A. L., Henriques, A. T., & Vander Heyden, Y. (2021). Quality control of herbal medicines: From traditional techniques to state-of-the-art approaches. Planta medica, 87(12/13), 964-988.
- Cui, X., Song, L., Sun, J., & Zhou, H. (2024, March). Research on the application of intelligent Chinese herbal medicine identification technology. In International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023) (Vol. 13105, pp. 571-577). SPIE.
- Kaur, P. P., Singh, S., & Pathak, M. (2021, April). Review of machine learning herbal plant recognition system. In Proceedings of the International Conference on Innovative Computing & Communications (ICICC) 2020, Proceedings of the International Conference on Innovative Computing & Communication (ICICC).
- Sharma, S., Naman, S., Dwivedi, J., & Baldi, A. (2023). Artificial Intelligence-Based Smart Identification System Using Herbal Images. Applications of Optimization and Machine Learning in Image Processing and IoT.
- https://medium.com/@yafonia/agile-in-a-nutshell-7725674ee31e
This study aims to develop and implement an
herbal medicine scanner. HerbID, with its approach, has
sparked a growing interest in remedies for their healing
properties in today's world. This state of the art technology
introduces an identification system that is reshaping how
we engage with medicine. By combining a repository of
solutions, with advanced scanning capabilities HerbID
ensures a seamless user experience. Through a scan users
can precisely recognize herbs empowering them to make
informed choices regarding their health and overall
wellness. HerbID offers more than identifying herbs – it
offers in depth insights into the benefits, potential
advantages and usage tips for each herb. With HerbID you
can gain the knowledge and confidence to make the most
of medicine whether you're a beginner or well versed in
natural healing practices. Explore a range of remedies,
with HerbID your go to herbal medicine companion.