Realtime Object Detection and Disease Prediction of Visually Impaired People

Abstract

In order to detect objects, this research combines real-time object identification with appropriate deep learning techniques. In our study, we describe the creation of a real-time system for item recognition, classification, and position estimation in the open environment. Blind and visually impaired people daily deal with a variety of difficulties. The proposed plan's goal. Computer vision is used to precisely identify indoor items. Those who are blind or visually challenged can use navigational aids, The Technology for navigation of the blind is not sufficiently accessible, without vision it can be challenging for visually impaired persons to navigate through rooms or different road paths .The main aim to develop the project is to help the visually impaired people and to detect the obstacles .The blind persons life become easier and without anyone helps they can walk alone through street they does not need anyone to assist them they can handle their self correctly. The preventing users from dangerous location our aim is to collected from environment (cameras, sensors, scanners, etc.) and transmitted to the users to the audio format. Data in the healthcare industry consists of all the information related to patients. Herea general architecture has been proposed for predicting the disease in the healthcare industry