Smart health monitoring system for physical disable person
In this project, we monitor the physically disabled person and based on that provide the data to the doctor for better treatment. We have used the Arduino controller for connection.
In this Project, there are two parameters Drowsiness and safe distance. For that we generate the alert by buzzer when People will Drowsy and we cross the safe distance that may lead to collision on the road which is based on the general formula of safe distance using MYOSA kit. Driver drowsiness detection is done using Raspberry PI and OpenCV library in which the eye blink is calculated on the video that is fed in the system.
In this project, we monitor the physically disabled person and based on that provide the data to the doctor for better treatment. We have used the Arduino controller for connection.
The aim of this project is used to establish more transparency between students and faculties. So It provides a feature to students like leave, discussion, forums, etc. Using this project, faculty guide and monitor the progress of the student.
This project was targeted to predict the Image label of cifar 10 dataset using convolutional neural network