This chapter covers various technical features available for building a smart healthcare system. Its different components are included as separate sections along with introduction and conclusion parts. There are many other sections incorporated here, namely infrastructure development, streaming data management, cloud computing and machine learning techniques for data analysis. The advancements in sensor technology and internet of things could enable real-time monitoring of several body parameters. The values from these sensors connected to the body can be Integrated for analysis. Which can enhance our health monitoring system. The way of harvesting information from these fast-moving data is also explored here in this chapter. Further, the role of machine learning techniques to build intelligence to the system is discussed in detail. This chapter is organized as a systematic study to form a smart healthcare system which are accepted by the people because of its analytical accuracy.
TopIntroduction
Traditional industries transform to smart industries with advancements in information and communication technologies. The growth of artificial intelligence together with the advancement of Rapid increase in computation power, availability of health data from various devices and health applications and the support of transforms the healthcare industry into a smart healthcare industry (Chui et al., 2017). Today’s healthcare system recognizes the impact of ICT to improve the quality of healthcare and turns into a smart healthcare system. Prevention of diseases, impact diseases on the body and their treat are together means “healthcare”. The smartness of healthcare system is achieved through the introduction of advanced diagnostic tools, better treatment and usage of devices that improve the quality of life of anyone to everyone. Health improvement through internet resources, mobile resources, record management by electronic means, health management with smart device etc. are treated as smart health services. All these services will reduce efforts of patients to get service of experts, quicker and accurate responses for monitored conditions and reduce cost of treatment.
A Smart healthcare system follows a three-layered architecture. First layer is called collection layer which constitutes sensors which are part of wireless body area network. This layer is responsible for collecting sensed data and sends either to the edge devices or clouds for storage or processing. Edge systems can be any device which is capable to do basic processing with sensed data. The point where data reaches first from sensors are sometimes called Base Station (BS) The transmission layer, second layer, consists of a gateway and base stations along with internet support. Third layer, Analysis Layer, is formed by incorporating cloud facilities with data mining algorithms and machine learning technologies (Chen et al., 2018). Health status of a user and corresponding medical treatment measures can be obtained from such systems with Artificial intelligence.
The core component of smart healthcare systems are sensors. Sensors are devices which used to detect changes or variation in its environment. Based on the environment from which changes are detected, method and purpose of these devices, they are classified into different categories. Deployment of sensors in an environment are the means to collect various data related to the environment (Aggarwal et al., 2013). Group of such sensor nodes together with other networking devices forms a Wireless Sensor Network (WSN). These small devices are communicating with short range signals. These networks face challenges in terms of battery life, short communication range, modest processing power, little storage capacity etc. Here we are considering one such network call Wireless Body Area Network and is considered as part of a smart healthcare system.
Sensors connected in proximity to the human body, combined with wireless communication technologies form a Wireless Body Area Network (WBAN). Wearing smart gadgets or devices, implanting communicating devices to the human body brings connection and a hence a network among themselves around patients’ body (Sethi & Anand, 2019). We can connect all the sensors within two meters range and form a body centered system by using the Personal Area Network (PAN). This body centered system supports computer assisted rehabilitation or early detection of medical conditions with the help of a number of physiological sensor values participating in Wireless Body Area Network. A real time update of medical records is possible with the data from sensors of WBAN and remote monitoring of these updates plays a big role in smart health systems.