Skin disease prediction using Arduino UNO and UV sensor

The human bodies are covered with skin at the outermost side and tissues in the innermost side. The skin in the human bodies is acting as the barriers that prevent the entering of virus, bacteria and other harmful organism inside the body.
The skin disease is the most common and challenging diagnosis in the daily life. Most of the occurrence in the skin disease was not reported. Since there is the lack of infrastructure and medical services.
In this study, the neural network based on the image analysis is used to predict the skin disease. Skin disease prediction is the time saving process that involves in identifying the type of disease and the report the patient about the type of the disease.
The existing of this system was the device like wristbands and patches measure UV exposure. They often connect to smartphones to track data and provide alerts when UV levels are high. Some apps analyze exposure data to assess potential skin risks.
The proposed system combine the sensors to gather comprehensive environmental data. This would allow for a more accurate assessment of skin health risks.
This technique is the web based application that makes easy for the patient to check themselves about the type of the disease. The results are accurate and are available to the patient by the web page.