Intelligent Interactive Health Display

The Intelligent Interactive Health Display introduces various methods for assessing an individual's health status using diverse sensors. It enables individuals to gather information about their height, weight, BMI, and body temperature using sensors like the Ultrasonic sensor, weight scales, and IR temperature sensors. BMI serves as a dependable indicator of body fat levels for most individuals, aiding in the identification of weight categories that may pose health risks. The ideal BMI range falls between 18.5 and 24.9. The values below 18 represent underweight and over 24.9 indicate overweight. Leveraging this intelligent display to ascertain one's BMI enables more precise health monitoring, reducing the need for extensive visits to healthcare facilities. This empowers individuals to adapt their dietary habits according to their body type, promoting overall well-being. Additionally, the envisioned display system also seeks to discern and visually display a person's emotional state using a camera. The aim is to design a system capable of realtime prediction and classification of facial emotions. Feature extraction is done by using the Convolution Neural Network (CNN) algorithm, implemented with the OpenCV, Keras, and NumPy libraries. This feature holds significant promise, as it can be employed to detect irregularities in various bodily regions, contributing to early analysis of potential health issues. The display then shows the emotions expressed by individuals in realtime.