Sensor Networks in Healthcare

Ambrose, Arny; Cardei, Mihaela

doi:10.1201/b17124-10

Cited by 1 publication

(1 citation statement)

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“…Sensor networks are used in healthcare as emergency response applications, smart home applications, and continuous monitoring applications in telemedicine [21]. Although SE is essential for the development of software systems and software components of complex systems, the literature on SE applications for sensor networks applications in health and their applications is sparse [20].…”

Section: G Capabilitiesmentioning

confidence: 99%

Sensor Networks and Personal Health Data Management: Software Engineering Challenges

Zhang

Pike

et al. 2020

Advances in Intelligent Systems and Computing

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The advances of 5G, sensors, and information technologies enabled 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 can measure vital signs, advances in the management of medical knowledge, and improvement of algorithms for decision support, are fueling a technological disruption to health monitoring. The increase in size and complexity of wireless sensor networks and expansion into multiple areas of health monitoring creates challenges for system design and software engineering practices. In this paper, we highlight some of the key software engineering and data-processing issues, along with addressing emerging ethical issues of data management. The challenges associated with ensuring high dependability of sensor network systems can be addressed by metamorphic testing. The proposed conceptual solution combines data streaming, filtering, cross-calibration, use of medical knowledge for system operation and data interpretation, and IoT-based calibration using certified linked diagnostic devices. Integration of blockchain technologies and artificial intelligence offers a solution to the increasing needs for higher accuracy of measurements of vital signs, high-quality decision-making, and dependability, including key medical and ethical requirements of safety and security of the data.

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Section: G Capabilitiesmentioning

confidence: 99%