Eye Health Monitoring System

Abstract

The current research focuses on examining the negative impacts of blue light on human eyes. With the increasing usage of digital devices such as laptops, smartphones, and televisions, individuals are spending most of their time in front of screens. This prolonged screen time puts immense strain on the eyes, and blue light with wavelengths between 415 nm and 455 nm is a significant contributor to eye strain and damage. To understand the extent of damage, we considered various parameters such as the size of the screen, light intensity, and luminous intensity. We used a TCS34725 RGB sensor to measure the blue light emissions reaching the human eye and established a relationship between sensor outputs and light intensity. To classify the data, we utilized both KNN and Naïve Bayes algorithms for efficient analysis and quicker results.