Internet of Things (IoT) in telemedicine delivers immediate treatments to patients, continuously monitors critically ill patients, and keeps tracks of records of each patient. The main target groups have become senior citizens for service providers in telemedicine technology. Getting older may lead to the loss of individuals’ physical and mental stability when compared to the young population. Therefore, it is necessary to have a system to monitor their daily activities continuously. This study aims to investigate the telemedicine systems based on the IoT used in the healthcare sector while identified the cost-effective and comprehensible telemedicine system. The data from 26 peer-reviewed publications were reviewed and assembled according to different parameters: telecare system platform, algorithm, encryption method, IoT hub system, operating system, communication system, sensors, storage, network system, and hardware. According to the results, electrocardiogram (ECG) is the conventional sensors type, used in healthcare systems, and it was 22%. Also, the use of motion and temperature sensors was recorded as 18% and 20%, respectively. It was reported 8% of the Ubuntu/Linux users and 4% of infrared (IR) users. Similarly, 25% of the healthcare systems use Wi-Fi as the communication system, while 21% use the Bluetooth as the communication system. In total, 4% of the healthcare system intended to use a GPRS communication system. Furthermore, 38% of the healthcare systems use the Android operating system, and 23% of the user implemented the iOS operating system. JAVA operating system has popular among 4% of the users in the healthcare system. The analysis showed that the highest percentage of the sensors used in healthcare systems is ECG sensors, and most of the healthcare systems use Wi-Fi as the communication system and Android as the operating system.
|Title of host publication||Studies in Computational Intelligence|
|Editors||Gonçalo Marques, Akash Kumar Bhoi, Victor Hugo C. de Albuquerque, Hareesha K.S.|
|Number of pages||20|
|Publication status||Published - 2021|
|Name||Studies in Computational Intelligence|