Book ChapterDOI
Big Data Security Intelligence for Healthcare Industry 4.0
Gunasekaran Manogaran,Chandu Thota,Daphne Lopez,Revathi Sundarasekar +3 more
- pp 103-126
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TLDR
This chapter proposes a secure Industrial Internet of Things (IoT) architecture to store and process scalable sensor data (big data) for health care applications using proposed Meta Cloud-Redirection (MC-R) architecture with big data knowledge system.Abstract:
Nowadays, sensors are playing a vital role in almost all applications such as environmental monitoring, transport, smart city applications and healthcare applications and so on. Especially, wearable medical devices with sensors are essential for gathering of rich information indicative of our physical and mental health. These sensors are continuously generating enormous data often called as Big Data. It is difficult to process and analyze the Big Data for finding valuable information. Thus effective and secure architecture is needed for organizations to process the big data in integrated industry 4.0. These sensors are continuously generating enormous data. Hence, it is difficult to process and analyze the valuable information. This chapter proposes a secure Industrial Internet of Things (IoT) architecture to store and process scalable sensor data (big data) for health care applications. Proposed Meta Cloud-Redirection (MC-R) architecture with big data knowledge system is used to collect and store the sensor data (big data) generated from different sensor devices. In the proposed system, sensor medical devices are fixed with the human body to collect clinical measures of the patient. Whenever the respiratory rate, heart rate, blood pressure, body temperature and blood sugar exceed its normal value then the devices send an alert message with clinical value to the doctor using a wireless network. The proposed system uses key management security mechanism to protect big data in industry 4.0.read more
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References
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Journal ArticleDOI
A Survey on Wearable Sensor-Based Systems for Health Monitoring and Prognosis
TL;DR: A variety of system implementations are compared in an approach to identify the technological shortcomings of the current state-of-the-art in wearable biosensor solutions and evaluate the maturity level of the top current achievements in wearable health-monitoring systems.
Journal ArticleDOI
Body Area Networks: A Survey
TL;DR: This paper provides a detailed investigation of sensor devices, physical layer, data link layer, and radio technology aspects of BAN research, and presents a taxonomy of B Ban projects that have been introduced/proposed to date.
Journal ArticleDOI
Sensor networks for emergency response: challenges and opportunities
Konrad Lorincz,David J. Malan,T.R.F. Fulford-Jones,A. Nawoj,A. Clavel,Victor Shnayder,Geoffrey Mainland,Matt Welsh,Steve Moulton +8 more
TL;DR: The proposed CodeBlue integrates sensor nodes and other wireless devices into a disaster response setting and provides facilities for ad hoc network formation, resource naming and discovery, security, and in-network aggregation of sensor-produced data.
Proceedings Article
CodeBlue: An Ad Hoc Sensor Network Infrastructure for Emergency Medical Care
TL;DR: The architecture of CodeBlue, a wireless infrastructure intended for deployment in emergency medical care, integrating low-power, wireless vital sign sensors, PDAs, and PC-class systems, is introduced and research challenges being addressed are highlighted.
Journal ArticleDOI
Big Data In Health Care: Using Analytics To Identify And Manage High-Risk And High-Cost Patients
TL;DR: Six use cases are presented where some of the clearest opportunities exist to reduce costs through the use of big data: high-cost patients, readmissions, triage, decompensation, adverse events, and treatment optimization for diseases affecting multiple organ systems.