Authors :
R.K.A. Risina Rasmith; C.P. Abeywickrama; H.L.D.P. De Silva; K.G. Chamindu Hansana; S. Siriwardana; S. Jayaweera
Volume/Issue :
Volume 8 - 2023, Issue 10 - October
Google Scholar :
https://tinyurl.com/a6bck5pr
Scribd :
https://tinyurl.com/23ybnmzz
DOI :
https://doi.org/10.5281/zenodo.10066306
Abstract :
Facial skincare is crucial for overall health,
beauty, and wellbeing, as the face serves as a foremost
reflection of one's life. Face skin is delicate and more
sensitive to damage. Neglecting proper facial skincare
can lead to some diseases like acne, dark spots, and
other signs of aging. Facial skin diseases are a common
health problem that can be found worldwide. Since
ancient times, ayurvedic treatments can be found as
natural and optimum solutions to cure those diseases
and keep the facial skin healthy and glowing. This
research introduces an integrated framework to
automate face skin disease detection, identify ayurvedic
plants, patient data management and telemedicine
system, and user interaction within the context of facial
skin health. The proposed system utilizes machine
learning techniques to identify four facial skin
conditions: acne, dark circles, dark spots, and wrinkles
into 3 levels. Additionally, it can recognize 20 different
ayurvedic plants using leaves, flowers, fruits, and barks
and offers ayurvedic remedies through natural
language processing (NLP) based emotional awareness
chatbot using text and audio messages and enhances
patient engagement through a web application using
telemedicine system, connecting medical professionals
and patients for efficient care delivery. This research
aims to reform skincare by combining advanced
technology with traditional knowledge, offering holistic
solutions to facial skin health. It addresses the need for
early face skin disease detection, natural remedies, and
seamless patient-professional interaction, eventually
promoting a healthy and fair appearance.
Keywords :
Facial Skincare, Disease Detection, Ayurvedic Plants, Telemedicine, Natural Remedies.
Facial skincare is crucial for overall health,
beauty, and wellbeing, as the face serves as a foremost
reflection of one's life. Face skin is delicate and more
sensitive to damage. Neglecting proper facial skincare
can lead to some diseases like acne, dark spots, and
other signs of aging. Facial skin diseases are a common
health problem that can be found worldwide. Since
ancient times, ayurvedic treatments can be found as
natural and optimum solutions to cure those diseases
and keep the facial skin healthy and glowing. This
research introduces an integrated framework to
automate face skin disease detection, identify ayurvedic
plants, patient data management and telemedicine
system, and user interaction within the context of facial
skin health. The proposed system utilizes machine
learning techniques to identify four facial skin
conditions: acne, dark circles, dark spots, and wrinkles
into 3 levels. Additionally, it can recognize 20 different
ayurvedic plants using leaves, flowers, fruits, and barks
and offers ayurvedic remedies through natural
language processing (NLP) based emotional awareness
chatbot using text and audio messages and enhances
patient engagement through a web application using
telemedicine system, connecting medical professionals
and patients for efficient care delivery. This research
aims to reform skincare by combining advanced
technology with traditional knowledge, offering holistic
solutions to facial skin health. It addresses the need for
early face skin disease detection, natural remedies, and
seamless patient-professional interaction, eventually
promoting a healthy and fair appearance.
Keywords :
Facial Skincare, Disease Detection, Ayurvedic Plants, Telemedicine, Natural Remedies.
