Computer Vision on IOT Based Patient Preference Management System

Abstract

Patient preference management is an essential work for any healthcare scheme to give priority to the needy patient. The work is generally carryout by a caretaker in the healthcare block to enroll their details of the patient on computer to find out and suggest an available consultant and time slot for the patient. These kind of usual works can be helpful up to certain normal conditions only. During uncertain times like viral explosion or war or nature disaster, the usual system will make the patient to wait in a queue for enrollment process. Most of the time it is intolerable to make a severe injured person to wait in the queue for the treatment. At the same time, during viral explosion the people were asked to stay at their home and for treatment they have to make a phone call to the care taking team for expressing their situation and health status. Attending a huge number of phone calls manually and providing a good suggestion to the caller is a challenging work for any healthcare team. The proposed IoT based computer vision system suggests the patient to send their status through a mobile phone message or email to the healthcare server to segregate the status of patient as emergency, severe and follow-up categories. This makes the healthcare team to identify the needy patient at right time to serve them. The proposed system is simulated with different computer vision algorithm and analyses its accuracy, time delay and drop rate to make a reliable patient preference management system.