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.
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Manogaran, G., Thota, C., Lopez, D., Sundarasekar, R. (2017). Big Data Security Intelligence for Healthcare Industry 4.0. In: Thames, L., Schaefer, D. (eds) Cybersecurity for Industry 4.0. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-319-50660-9_5
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DOI: https://doi.org/10.1007/978-3-319-50660-9_5
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