# Internet of Things and Its Applications: A Comprehensive Survey
## 5 IoT Applications
### Healthcare Applications
It explains that the Body Sensor Networks (BSN) or Wireless Body Area Networks (WBAN) are usually placed in contact with the patient's body, in order to sense and gather physiological information to be stored and saved in the database. Since the information is collected from various sources, a procedure for combining the collected data is required, which is known as data fusion. The authors presented a new approach for displaying the gathered information in a manner that supports making a precise and specific decision at the proper time. The results addressed a few challenges, including the limited coverage, sensor deficiency, ambiguity, and irregularity. However, this work does not present any algorithm for an evaluation of the presented approach. Another study is presented in [97], which focuses on proposing a negligible inaccuracy altered IEEE 802.15.4 transceiver for IoT healthcare applications. The study aimed to improve the frequency offset evaluator to ensure a better and higher performance in modifying errors compared to the current evaluators of IEEE 802.15.4. It helps to enhance the total bit error and the frequency of packet error in comparison to the standard architecture. Moreover, this study contributes to diminishing the power consumption as less retransmission is involved, in order to ensure a successful packet broadcast. An investigation conducted by [PERSON] et al. [98] established a new concept of sensor detections in Cognitive Radio Sensor Networks (CRNs). A theoretical approach of the recommended paradigm, in contrast with the Primary User Emulation Attack (PUEA), is presented in this work, where an elaborated method highly enhances the effectiveness of strike exposure. However, this study does not consider the reliability, trustworthiness, and operability of the system in terms of the node movement influence regarding detection implementation. In [99], [PERSON] et al. present a theoretical and experimental analysis of three epidermal loop antennas to measure the biological parameters for IoT healthcare applications. This work examines the error-vector magnitude (EVM) and evaluates the Bit Error Rate (BER) parameters to endorse the accuracy of the global system for mobile communication (GSM) and Bluetooth Low Energy (BLE) communications in Quadruple Loop (QL) antennas. The results show the appropriate reliability and constancy between the factor of refection and the forms of radiation. The evaluation of data communication shows that the achieved BER is appropriate for the studied antenna expertise and can work in 4 Quadrature Amplitude Modulation (QAM) wireless connectivity. A further study on healthcare applications was conducted by [PERSON] et al. [100], where a routing approach for WSN was focused on improving the interference and energy effectiveness, following blockage and interface perception of the energy efficiency. Since many IoT devices share the same focus point, the network poses extreme traffic and delays in the link between the devices. The elaborated algorithm uses a function to determine the following party node, which operates the following three parameters: (1) The signal to interference plus noise ratio (SINR); (2) the route sustainability; and (3) node blockage. It can be seen that the data the proposed approach is able to deliver enhanced the data rate and lowered the energy consumption and packet loss. Moreover, [PERSON] and [PERSON] [101] suggested a new design for IoT applications in healthcare, enabling the processing of retinal images that are taken by a smartphone funduscopy. To enhance the quality of the images, an algorithm that has a super-resolution using the Kernel support vector regression process was recommended. The obtained results show that the proposed algorithm has a more effective performance compared to various current super-resolution algorithms.