Challenges and Limitation Analysis of an IoT-Dependent System for Deployment in Smart Healthcare Using Communication Standards Features

Abstract

The use of IoT technology is rapidly increasing in healthcare development and smart healthcare system for fitness programs, monitoring, data analysis, etc. To improve the efficiency of monitoring, various studies have been conducted in this field to achieve improved precision. The architecture proposed herein is based on IoT integrated with a cloud system in which power absorption and accuracy are major concerns. We discuss and analyze development in this domain to improve the performance of IoT systems related to health care. Standards of communication for IoT data transmission and reception can help to understand the exact power absorption in different devices to achieve improved performance for healthcare development. We also systematically analyze the use of IoT in healthcare systems using cloud features, as well as the performance and limitations of IoT in this field. Furthermore, we discuss the design of an IoT system for efficient monitoring of various healthcare issues in elderly people and limitations of an existing system in terms of resources, power absorption and security when implemented in different devices as per requirements. Blood pressure and heartbeat monitoring in pregnant women are examples of high-intensity applications of NB-IoT (narrowband IoT), technology that supports widespread communication with a very low data cost and minimum processing complexity and battery lifespan. This article also focuses on analysis of the performance of narrowband IoT in terms of delay and throughput using single- and multinode approaches. We performed analysis using the message queuing telemetry transport protocol (MQTTP), which was found to be efficient compared to the limited application protocol (LAP) in sending information from sensors.

Advancements in Bio-inspired Self-Powered Wireless Sensors: Materials, Mechanisms, and Biomedical Applications

“…The integration of cloud and big data may solve problems related to medical data management. 377 Despite all these advances and the efforts made to overcome the existing challenges, there are still unresolved issues in the commercialization of self-powered sensors. The authors of this review hope to have provided a clear understanding of the background, current status, and future opportunities of batteryfree sensors based on biofuel cells or nanogenerators.…”

“…A number of researchers have suggested that the data received by IoT-based sensors should be effectively stored in cloud servers and that IoT devices should be used to transfer data to different cloud subsystems for disease detection. The integration of cloud and big data may solve problems related to medical data management …”

IoT-enabled solutions for Alzheimer's disease management: innovations and opportunities

“…Radio-frequency recognition is based on an encryption strategy used to secure medical data. In a network setting, the flow of data for health information is highly complex, and data security in wearable health tracking systems depends on biometric security with resource constraints (Upadhyay et al, 2023).…”

Real-Time Remote Patient Monitoring: A Review of Biosensors Integrated with Multi-Hop IoT Systems via Cloud Connectivity

“…The optimization of data transmission is another facet, demanding protocols and algorithms to minimize energy consumption during transmission. This optimization ensures biosensors can operate for extended periods without frequent battery replacements [122].…”