Toward QoS Monitoring in IoT Edge Devices Driven Healthcare—A Systematic Literature Review

• Published in: Sensors (Basel, Switzerland) Vol. 23; no. 21; p. 8885
• Main Authors: Younas, Muhammad Irfan, Iqbal, Muhammad Jawed, Aziz, Abdul, Sodhro, Ali Hassan
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01.11.2023
• Subjects: Artificial Intelligence; artificial intelligence (AI); Caregivers; Cloud Computing; Delivery of Health Care; Disasters; Health care industry; Health care reform; Health facilities; Humans; Industry; Internet of Things; Internet of Things (IoT); Interoperability; Literature reviews; Machine learning; Medical records; Middleware; Optimization; Patients; Quality of service; Response time; smart healthcare; Systematic review; smart healthcare; Internet of Things (IoT); quality of service; cloud computing; machine learning; artificial intelligence (AI)
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s23218885

Smart healthcare is altering the delivery of healthcare by combining the benefits of IoT, mobile, and cloud computing. Cloud computing has tremendously helped the health industry connect healthcare facilities, caregivers, and patients for information sharing. The main drivers for implementing effective healthcare systems are low latency and faster response times. Thus, quick responses among healthcare organizations are important in general, but in an emergency, significant latency at different stakeholders might result in disastrous situations. Thus, cutting-edge approaches like edge computing and artificial intelligence (AI) can deal with such problems. A packet cannot be sent from one location to another unless the “quality of service” (QoS) specifications are met. The term QoS refers to how well a service works for users. QoS parameters like throughput, bandwidth, transmission delay, availability, jitter, latency, and packet loss are crucial in this regard. Our focus is on the individual devices present at different levels of the smart healthcare infrastructure and the QoS requirements of the healthcare system as a whole. The contribution of this paper is five-fold: first, a novel pre-SLR method for comprehensive keyword research on subject-related themes for mining pertinent research papers for quality SLR; second, SLR on QoS improvement in smart healthcare apps; third a review of several QoS techniques used in current smart healthcare apps; fourth, the examination of the most important QoS measures in contemporary smart healthcare apps; fifth, offering solutions to the problems encountered in delivering QoS in smart healthcare IoT applications to improve healthcare services.