Healthcare Disaster Prediction with IoT, Data Analytics, and Machine Learning

ABSTRACT

Disaster may be natural or man-made, for example, terrorist attack, earthquakes, landslides, cyclones and storms/wave surges, floods or disease epidemics, and insect/animal plagues like COVID-19. Due to disaster, normal patterns of life get disturbed affecting the physical and psychological health. It is challenging to predict the likelihood of occurrence of disaster but people should have the aim to handle this acute and long term. Any type of disaster affecting the health stresses for healthcare. Due to this pandemic situation, the health of the person is affected. In the current scenario, so much has been impacted due to COVID-19. People are affected because they didn’t get proper help, timely and admissible solutions for the same. When no one is prepared for this type of situation like disasters, people face issues like availability of hospitals and medicine, loss of their family, etc. To handle this problem, the Internet of things (IoT) is playing an important role in healthcare. There are so many android apps and IoT devices for health monitoring. To minimize the impact of this disaster or to predict it early, technical and medical innovations are necessary. One such example is Aarogya Setu app that is making use of GPS and Bluetooth to track coronavirus-infected people. IoT devices generate a huge amount of data that needs to be analyzed. This chapter will discuss different IoT devices, data analytics, and machine learning (ML) algorithms that are used to predict disasters, thus, affecting the health. © 2023 by Apple Academic Press, Inc.