sing orthogonal frequency division multiplexing (OFDM) tech- nology and data compression. TABLE 2.1 H-loT Layered Architecture Data Collection Layer Collection of data from the various sensors on the patient's body Data Storage Layer Storage of large amount of data Data Processing Layer Various computing algorithms are implemented on the cloud 5G Wireless Communication System in Healthcare Informatics (Identification) Bluetooth (Communication) (Location) H-loT Technologies Sensors FIGURE 2.2 Technologies used in different layers of H-IoT. Threshold Sampling Quantization based Signal Decomposition Transmitter Compressed EEG Signal M-Health Cloud Threshold Signal based Reconstruction Receiver FIGURE 2.3 System model. Figure 2.3 shows the translation of an EEG signal to an M-health cloud end-to-end system. The EEG signal is obtained through an EEG headset attached to a patient's head. The signal is sampled, quantized, and decomposed for the application of the compression scheme. The compressed signal is transmitted and received by the proposed threshold- based transmitter and receiver, respectively. With this efficient design of transceiver, the communication system achieves excellent performance with reference to data reduction gain, reduced system complexity, and signal distortion. The data is compressed by up to 50%, with 0% distortion and sample error rate [22]. Researchers have proposed various technological tools for healthcare diagnostic tools and sensors [23]. The advances in materials and processes have also been explained which led to precision in diagnostic data, and reduction in the price and size of healthcare products. 5G Wireless in Healthcare Informatics Healthcare 1.0 Healthcare 2.0 Healthcare 3.0 Healthcare 4.0 Healthcare 5.0 (c. 1780) (c. 1870) (c. 1970) (c. 2010) ( 2020) Vaccination Specialists Computers Artificial Personalization Sanitation Antibiotics Imaging Intelligence Digital Wellness Germ Theory Big Hospitals Evidence-based Telemedicine medicine Automatic Health Monitors FIGURE 2.4 Healthc