Telemedical and remote healthcare monitoring using IoT and machine learning

Abstract

Health has become one of the most promising challenges. Remote healthcare gives the provision of real-time monitoring of patients from different areas. The development of IoT has transformed face-to-face medical consultation to remote telemedicine. The main objective of IoT-based healthcare is to provide benefits to patients through medical services using IoT sensors or wearable devices. This will avoid frequent visits of patients to the hospitals for their regular check-up. Wearable devices are used to collect patients’ data, like heartbeat rate, body temperature and BP level, with the help of sensors like ECG sensors or pulse sensors and many more, per the requirement of the patient. Sensors are used to convert the data from the physical world to the digital world by storing it in the IoT server. Further, this data is used for making decisions. This monitoring of data by medical professionals can be on a regular basis or in emergency situations. The main aim of this chapter is to provide a systematic view of using machine learning and IoT devices for remote healthcare which will help patients, especially those who are suffering from chronic diseases.