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A Smart and Interactive Edge-Cloud Big Data SystemStauffer, Jake 08 1900 (has links)
Indiana University-Purdue University Indianapolis (IUPUI) / Data and information have increased exponentially in recent years. The promising era of big data is advancing many new practices. One of the emerging big data applications is healthcare. Large quantities of data with varying complexities have been leading to a great need in smart and secure big data systems.
Mobile edge, more specifically the smart phone, is a natural source of big data and is ubiquitous in our daily lives. Smartphones offer a variety of sensors, which make them a very valuable source of data that can be used for analysis. Since this data is coming directly from personal phones, that means the generated data is sensitive and must be handled in a smart and secure way. In addition to generating data, it is also important to interact with the big data. Therefore, it is critical to create edge systems that enable users to access their data and ensure that these applications are smart and secure. As the first major contribution of this thesis, we have implemented a mobile edge system, called s2Edge. This edge system leverages Amazon Web Service (AWS) security features and is backed by an AWS cloud system. The implemented mobile application securely logs in, signs up, and signs out users, as well as connects users to the vast amounts of data they generate. With a high interactive capability, the system allows users (like patients) to retrieve and view their data and records, as well as communicate with the cloud users (like physicians). The resulting mobile edge system is promising and is expected to demonstrate the potential of smart and secure big data interaction.
The smart and secure transmission and management of the big data on the cloud is essential for healthcare big data, including both patient information and patient measurements. The second major contribution of this thesis is to demonstrate a novel big data cloud system, s2Cloud, which can help enhance healthcare systems to better monitor patients and give doctors critical insights into their patients' health. s2Cloud achieves big data security through secure sign up and log in for the doctors, as well as data transmission protection. The system allows the doctors to manage both patients and their records effectively. The doctors can add and edit the patient and record information through the interactive website. Furthermore, the system supports both real-time and historical modes for big data management. Therefore, the patient measurement information can, not only be visualized and demonstrated in real-time, but also be retrieved for further analysis. The smart website also allows doctors and patients to interact with each other effectively through instantaneous chat. Overall, the proposed s2Cloud system, empowered by smart secure design innovations, has demonstrated the feasibility and potential for healthcare big data applications. This study will further broadly benefit and advance other smart home and world big data applications. / 2023-06-01
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A Smart and Interactive Edge-Cloud Big Data SystemJake M Stauffer (10987104) 22 June 2021 (has links)
<p>Data and information have increased
exponentially in recent years. The promising era of big data is advancing many
new practices. One of the emerging big data applications is healthcare. Large
quantities of data with varying complexities have been leading to a great need
in smart and secure big data systems. </p>
<p>Mobile edge, more specifically the
smart phone, is a natural source of big data and is ubiquitous in our daily
lives. Smartphones offer a variety of sensors, which make them a very valuable
source of data that can be used for analysis. Since this data is coming
directly from personal phones, that means the generated data is sensitive and
must be handled in a smart and secure way. In addition to generating data, it
is also important to interact with the big data. Therefore, it is critical to
create edge systems that enable users to access their data and ensure that
these applications are smart and secure. As the first major contribution of
this thesis, we have implemented a mobile edge system, called s<sup>2</sup>Edge.
This edge system leverages Amazon Web Service (AWS) security features and is
backed by an AWS cloud system. The implemented mobile application securely logs
in, signs up, and signs out users, as well as connects users to the vast
amounts of data they generate. With a high interactive capability, the system
allows users (like patients) to retrieve and view their data and records, as
well as communicate with the cloud users (like physicians). The resulting
mobile edge system is promising and is expected to demonstrate the potential of
smart and secure big data interaction.</p>
<p>The smart and secure transmission
and management of the big data on the cloud is essential for healthcare big
data, including both patient information and patient measurements. The second
major contribution of this thesis is to demonstrate a novel big data cloud
system, s<sup>2</sup>Cloud, which can help enhance healthcare systems to better
monitor patients and give doctors critical insights into their patients'
health. s<sup>2</sup>Cloud achieves big data security through secure sign up
and log in for the doctors, as well as data transmission protection. The system
allows the doctors to manage both patients and their records effectively. The
doctors can add and edit the patient and record information through the
interactive website. Furthermore, the system supports both real-time and
historical modes for big data management. Therefore, the patient measurement
information can, not only be visualized and demonstrated in real-time, but also
be retrieved for further analysis. The smart website also allows doctors and
patients to interact with each other effectively through instantaneous chat.
Overall, the proposed s<sup>2</sup>Cloud system, empowered by smart secure
design innovations, has demonstrated the feasibility and potential for
healthcare big data applications. This study will further broadly benefit and
advance other smart home and world big data applications. </p>
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