Convergence model of AI and IoT for virus disease control system

Abstract

Recently, virus diseases, such as SARS-CoV, MERS-CoV, and COVID-19, continue to emerge and pose a severe public health problem. These diseases threaten the lives of many people and cause serious social and economic losses. Recent developments in information technology (IT) and connectivity have led to the emergence of Internet of Things (IoT) and Artificial Intelligence (AI) applications in many industries. These industries, where IoT and AI together are making significant impacts, are the healthcare and the diagnosis department. In addition, by actively communicating with smart devices and various biometric sensors, it is expanding its application fields to telemedicine, healthcare, and disease prevention. Even though existing IoT and AI technologies can enhance disease detection, monitoring, and quarantine, their impact is very limited because they are not integrated or applied rapidly to the emergence of a sudden epidemic. Especially in the situation where infectious diseases are rapidly spreading, the conventional methods fail to prevent large-scale infections and block global spreads through prediction, resulting in great loss of lives. Therefore, in this paper, various sources of infection information with local limitations are collected through virus disease information collector, and AI analysis and severity matching are performed through AI broker. Finally, through the Integrated Disease Control Center, risk alerts are issued, proliferation block letters are sent, and post-response services are provided quickly. Suppose we further develop the proposed integrated virus disease control model. In that case, it will be possible to proactively detect and warn of risk factors in response to infectious diseases that are rapidly spreading worldwide and strengthen measures to prevent spreading of infection in no time.

Emerging Point-of-Care Optical Biosensing Technologies for Diagnostics of Microbial Infections

“…The IoMT-integrated biometric sensors can be used to send health data to relevant medical experts and track timely medication; IoMT apps allow us to monitor the patient from faraway locations. The healthcare application has explored the true potential of IoMT technologies via effective data collection, analysis, and transmission of data from the POC biosensor . The field of biosensors is undergoing a revolution in terms of decision-making, real-time monitoring, and intelligent functioning with the addition of artificial intelligence (AI) and IoT.…”

“…In addition, the data can be viewed and monitored instantaneously on a smart phone device. For instance, adding IoT devices to COVID-19 diagnostics makes it possible to create a “hospital-on-a-chip” system that can be used to find SARS-CoV-2 even in the most remote locations …”

“…The healthcare application has explored the true potential of IoMT technologies via effective data collection, analysis, and transmission of data from the POC biosensor. 91 The field of biosensors is undergoing a revolution in terms of decision-making, real-time monitoring, and intelligent functioning with the addition of artificial intelligence (AI) and IoT. Disease diagnosis has become more efficient with the integration of nanomaterials and IoT, which offers affordable, energyefficient, portable, flexible, versatile, and quick sensing devices.…”

“…For instance, adding IoT devices to COVID-19 diagnostics makes it possible to create a "hospital-on-a-chip" system that can be used to find SARS-CoV-2 even in the most remote locations. 93 More recently, the AI-based IoMT therapy assistance system for COVID-19 patients was intended to help those who have COVID-19 whether symptomatic or asymptomatic. More information will be gathered from the initial screening patient's data via intelligent graphical user interference (GUI).…”

Advances in the Rapid Diagnostic of Viral Respiratory Tract Infections

“…Internet-connected POC testing devices, coupled with predictive models and artificial intelligence (AI), would be a great asset in disease evolution monitoring and provide a valuable tool to stop their spreading (Sim and Cho, 2021). AI programs developed to diagnose a disease would be trained on data-like symptoms, lab results, and scans and images of confirmed and susceptible cases.…”