AI DIAGNOSIS AT EDGE USING ENSEMBLE MODELS FOR RAPID RADIOLOGY

Abstract

The monitoring of health for a person, particularly those with paralysis, has seen massive improvement with the advent of IoT technologies. With the improvement of healthcare systems the integration of IoT devices proves to be an efficient solution for enhancing patients' quality of life and providing them with ongoing care. In this essay, I focus on new practices of health monitoring systems for paralysed persons (under the condition of remote, real-time monitoring). Existing systems such as GSM based health monitoring only enables basic functionalities such as monitoring heart rate and body temperature, caregivers are alerted if threshold levels are crossed. Nevertheless, such systems do not usually have the smooth integration of real time data transfer and remote surveillance. On the contrary, the proposed system utilizes IoT for the development of a more efficient and automatic tracking system for health. By integrating sensors for monitoring such pivotal parameters as body temperature and heart rate, this system allows for data transfer over the Wi-Fi network to care givers and family members. In case of any abnormalities alerts are generated automatically to make sure that timely interventions are implemented. The system also includes live online tracking of the patient's condition in order to maintain a continuous update. The purpose of this Internet of Things health monitoring system is to reduce accessibility and reliability of health care for paralysed persons, providing piece of mind to the family members and care providers. The paper presents an overview of the proposed solution, and outlines its possible effect on the healthcare sector, particularly the advantages that real-time, transmissible health data will provide and which will improve the condition of the patients.