Sensor Networks and Personal Health Data Management: Software Engineering Challenges
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Sensor Networks and Personal Health Data Management: Software Engineering Challenges
Xiang Zhang,
Jialu Zhang,
Matthew Pike,
Nasser M. Mustafa,
Dave Towey,
Vladimir Brusic
Proceedings of the Future Technologies Conference (FTC) 2020, Volume 3 | 2020
| View on Publisher's Website
Abstract
The advances of 5G, sensors, and information technologies have enabled the proliferation of smart pervasive sensor networks. 5G mobile networks provide low-power, high-availability, high-density, and high-throughput data capturing by sensor networks and continuous streaming of multiple measured variables. Rapid progress in sensors that measure vital signs, advances in the management of medical knowledge, and improvements in decision-support algorithms are fueling a technological disruption in health monitoring. However, the increasing size and complexity of wireless sensor networks and their expansion into multiple areas of health monitoring present significant challenges for system design and software engineering. This paper highlights key software engineering and data-processing issues, along with emerging ethical concerns regarding data management. It explores the role of metamorphic testing in ensuring high dependability of sensor network systems, proposes solutions integrating blockchain technologies and artificial intelligence, and examines how these approaches can improve the accuracy, security, and reliability of health data management.