Role of the Internet of Things and deep learning for the growth of healthcare technology

Abstract The healthcare industry is in a state of great despair with rising healthcare costs, an aging global population, and an increase in new and chronic diseases. This could lead to a state of healthcare services being out of reach of ordinary people making them unproductive and prone to chronic diseases. The Internet of Things (IoT) has tremendously transformed and revolutionized the way present healthcare services are being provided to patients. The technology allows remote monitoring in the healthcare sector, helping in the continuous and safe monitoring of a patient's health condition, and empowering physicians to deliver quality healthcare at reasonable costs. The level of patient/doctor interaction has increased tremendously leading to widespread satisfaction with improved healthcare efficiency among patients due to the ease of interaction with healthcare providers. It has also helped to reduce the duration and length of hospital stay for patients, having a major impact on reducing the healthcare costs and improving treatment outcomes. Several applications in the healthcare sector employing IoT are presently available to benefit healthcare providers, hospitals, insurance companies, and patients at large. IoT has largely benefited critically ill patients and the elderly population living alone who require continuous monitoring due to their diseased condition by tracking their health conditions on a regular basis and allowing any disturbances or changes in routine daily living activities to trigger an alarm to a family member or concerned healthcare providers for an immediate check on their condition and provide instant care and treatment to avoid any fatalities or long-term damage. However, several potential challenges exist while designing any IoT-based healthcare system such as security and privacy, user identification and authentication, and regular communication and exchange of healthcare data, which need to be addressed before the technology can be adopted on a wider scale.