Abstract
Smarthealth care system is required to handle the large volume of data produced by the Massive Internet of Medical things. Smart healthcare system uses information and communication technology of IoT, data analytic, machine learning, deep learning, augmented reality, and cloud technologies to realize efficient, personalized, convenient health care systems. This chapter intended to give an overview, and the case of the above said ICT technologies for smart health applications. Smart healthcare systems are more patient-centric and enable them to get anywhere any health care service at an affordable cost. Machine learning and deep learning allow auto diagnosis of disease and predict the disease in an earlier stage in a systematic way from the acquired data set from the patient. Prediction of the disease increases the chance of curing the disease and reduces the Mortality rate. IoT enables smart continuous remote patient monitoring and medical data acquisition via an intelligent sensor system. Augmented Reality (AR) helps the surgeons to diagnose the disease accurately, performs surgery precisely with the help of real-time data of the patient quickly. AR also make surgeons precisely study patients’ anatomy through overlaying AR set augmentation of their scanned image on top of their body. Doctors able to visualize the internal part of the human body and organs without cutting the body. Cloud platform enables the patient data storage and retrieval of them anywhere at any time. Cloud computing facilitates run diagnosis and decision support software on ad hoc fashion and enables remote healthcare services. mHealth system utilizes mobile applications to easily reach the community of patients to provide health care services.
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Ponnusamy, V., Christopher Clement, J., Sriharipriya, K.C., Natarajan, S. (2021). Smart Healthcare Technologies for Massive Internet of Medical Things. In: Chakraborty, C., Ghosh, U., Ravi, V., Shelke, Y. (eds) Efficient Data Handling for Massive Internet of Medical Things. Internet of Things. Springer, Cham. https://doi.org/10.1007/978-3-030-66633-0_4
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