Abstract
RFID has been widely used in monitoring applications. In healthcare applications, events have to be detected in real time to make decisions. In this paper, we study optimization algorithms of event processing in RFID-enabled healthcare monitoring applications. We utilize non-deterministic automata (NFA) to model event processing. To reduce partial matches in event processing, we take advantage of a special data structure to maintain the events in memory. Event detection is accelerated by introducing context information as context can be used to delete many running instances which would not generate output complex event. Experiment results show that our methods are efficient and sound.
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Acknowledgments
This work has been supported by funds from Chengdu University of Information Technology, China (J201410), the Applied Basic Research Key Project of Sichuan Province (2017JY0011), and the China Scholarship Council.
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Peng, S., He, J. (2019). Optimization of Event Processing in RFID-Enabled Healthcare. In: Jiang, M., Ida, N., Louis, A., Quinto, E. (eds) The Proceedings of the International Conference on Sensing and Imaging. ICSI 2017. Lecture Notes in Electrical Engineering, vol 506. Springer, Cham. https://doi.org/10.1007/978-3-319-91659-0_29
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DOI: https://doi.org/10.1007/978-3-319-91659-0_29
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