Heterogeneous Wireless Access Networks for IoT and E-Health-A Survey

In a heterogeneous wireless environment, there are many different radio access technologies (RATs), such as Wi-Fi and 2G, 3G, 4G, and 5G, which each have a different degree of coverage and processing power to meet various service requirements. A mobile user may have access to various access networks in such a situation. On the PC of each user, numerous programs with varied Quality of Service (QoS) requirements can operate simultaneously. It would be advantageous for a multi-interface terminal to use two or more interfaces simultaneously in order to improve performance. However, using multiple networks at once could use up more energy than just using one interface. Therefore, energy use must to be taken into account when analyzing the Flow/Interface Relationship (FIA). This paper presents a novel method for choosing the ideal FIA that achieves the best trade-off between all the characteristics taken into account, dubbed Smart Tabu Search (STS). STS considers user preferences, network circumstances, network expenses, application QoS specifications, and battery life of mobile devices. We use simulations and testbed experiments to validate our concept. Professionals are now able to diagnose and monitor patients remotely because to the growing use of healthcare monitoring devices. One of the most frequent occurrences that affects the reliability of information transmission in any network is congestion, which is defined as the unchecked increase in traffic relative to network capacity. With the use of a mesh network, wireless sensors, and some of the most significant models for vital signs, the article aims to provide a realistic simulation environment for a healthcare system. The simulator environment is a helpful tool for assessing the dependability and effectiveness of the healthcare system in a realistic setting. However, the system is not appropriate for real-time applications due to the sluggish network adaption caused by the end-to-end based traffic regulation decision. In more recent scheduling techniques, additional scheduling factors were taken into account, including the priority order of inserting packets using a fixed priority algorithm based on Priority Queuing (PQ), user-defined. Context priorities, user-defined profile priorities, the applications and devices that are currently active, the number of their direct neighboring nodes, the average link quality, and user preferences. A cutting-edge paradigm for communication called the Internet of Things (IoT) permits online connections between parts from various domains. The traditional healthcare system has a growing need for social resources like doctors, nurses, hospital beds, and health monitoring gadgets, making modern healthcare one of the most alluring IoT applications. In this paper, a design for a small wearable sensor patch that can gauge body temperature, photo plethysmography, and the electrocardiogram (ECG) is given. The suggested sensor patch can be used to constantly estimate blood pressure (BP) based on the pulse arrival time (PAT) without the need for additional cables or equipment because ECG and PPG sensors are combined in one device. Three sensors are used to monitor vital signs, a central board is used to analyze and collect signals, and a power board is used to provide power and charge batteries. The entire set of parts is made with a rigid-flexible construction that permits rapid attachment to the body for applications like remote health monitoring. For specialized measurements of a particular physiological signal (such an ECG), the sensors can be taken out of the main board in order to save power. By comparing the suggested sensor patch to a commercial reference device, experiments are done to verify its performance. A tiny Bluetooth Low Energy (BLE) module that enables wireless transfer of physiological parameters to a 1/4 SeThe suggested sensor system includes a tiny Bluetooth Low Energy (BLE) module that enables wireless communication of physiological values to a gateway. In order to safeguard data while it is being transmitted for security and privacy reasons, both the sensor and the data are encrypted. The wearable sensor system is linked to the Internet cloud, where health data can be kept and later reviewed, by means of a stationary gateway based on laptops and a mobile gateway based on smartphones. The results of the testing show that the platform is viable for use in IoT-connected healthcare applications.