An IoT architecture for preventive maintenance of medical devices in healthcare organizations
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In recent years, hospitals have spent a significant amount on technologically advanced medical equipment to ensure not only the accuracy and reliability of medical devices, but also the required level of performance. Although medical devices have been revolutionized thanks to technology advancements, outdated maintenance strategies are still used in healthcare systems and services. Also, maintenance plans must often be developed for a mixture of advanced and obsolete technologies being used in medical devices. Therefore, most healthcare organizations have been facing the challenge of detecting equipment-related risks that would have been alleviated if effective integrity monitoring mechanisms were in place. Additionally, continuously growing volumes of large data streams, collected from sensors and actuators embedded into network-enabled sensors and microprocessors of medical equipment, require a scalable platform architecture to support the necessary storage and real-time processing of the data for device monitoring and maintenance. This paper investigates the issue of maintaining medical devices through an Internet-of-Things (IoT)-enabled autonomous integrity monitoring mechanism for those devices generating large-scale real-time data in healthcare organizations. The proposed architecture that includes an integrity monitoring framework and a data analytics module ensures the complete visibility into medical devices and provides a facility to predict possible failures before happening.
KeywordsReal-time monitoring information system Big data Medical devices Internet-of-Things (IoT) Network-enabled preventive maintenance
Compliance with ethical standards
Conflict of interest
Author Jamal Maktoubian certify that he has NO affiliations with or involvement in any organization or entity with any financial interest and declares that he has no conflict of interest. Author Keyvan Ansari declares that he has no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
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