A Novel Approach Towards Using Big Data and IoT for Improving the Efficiency of m-Health Systems

The application of big data in healthcare is growing at tremendous speed and many new discoveries and methodologies are published in the last decade in this field. Big data technologies are effectively being used in biomedical informatics and healthcare research. The mobile phones, sensors, patients, hospitals, researchers, and other organizations are generating a huge amount of healthcare data in these days. The large amounts of clinical data are being continuously generated by medical organizations and are used for detecting and curing new diseases. The actual test in m-health systems is the way to discover, gather, examine and administer the information to build a person’s life better and easier, by predicting the life dangers at early stages. A number of technologies have been developed by researchers which can decrease on which overheads for the evasion of overall management of chronic illnesses. The medical devices that continually monitor health system indicators or tracking of online health data in real-time environment as and when patient self-administers physiotherapy are now in huge demand. Many intelligent patients have now started using mobile applications (apps) to manage different daily life-related health needs on regular basis because of easy availability of high-speed Internet connections on smartphone and cybercafes. These devices and mobile applications are now progressively more used and integrated with telemedicine and telehealth via the Internet of Things (IoT). In this chapter, the authors have discussed the applications and challenges of biomedical big data. Further, this chapter presents novel approaches to advancements in healthcare systems using big data technologies and distributed computing systems.