Abstract
With the rapid proliferation of IOT sensors, the traditional cloud computing paradigm confronts several challenges such as bandwidth limitation and high latency. Therefore, edge computing paradigm has been paid more attention. In order to guarantee the real-time monitoring of electric heaters, this paper proposes a monitoring architecture combining cloud and edge nodes, and an anomaly detection method and a heating prediction method based on the architecture. Experiments show that the presented monitoring mechanism can reduce response time, improve data transmission efficiency and realize real-time monitoring and management.
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References
Kusriyanto, M., Putra, B.D.: Smart home using local area network (LAN) based arduino mega 2560. In: 2nd International Conference on Wireless and Telematics (ICWT 2016), pp. 127–131. IEEE (2016)
Khattak, A.M., Ho, T., Hung, D., et al.: Towards smart homes using low level sensory data. Sensors 11(03), 11581–11604 (2011)
Zhang, Q., Hu, Y., Ji, C., et al.: Edge computing application: real-time anomaly detection algorithm for sensing data. J. Comput. Res. Dev. 55(03), 524–536 (2018)
Tabatabaei, S.A., Ham, W.V.D., Klein, M.C.A., et al.: A data analysis technique to estimate the thermal characteristics of a house. Energies 10(9), 1358 (2017)
Gers, F.A., Schmidhuber, J., Cummins, F.: Learning to forget: continual prediction with LSTM. Neural Comput. 12(10), 2451–2471 (2000)
Zheng, H., Shi, D.: Using a LSTM-RNN based deep learning framework for ICU mortality prediction. In: Meng, X., Li, R., Wang, K., Niu, B., Wang, X., Zhao, G. (eds.) WISA 2018. LNCS, vol. 11242, pp. 60–67. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-02934-0_6
Acknowledgement
This work is supported by the Key projects of the National Natural Science Foundation of China (No. 61832004).
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Wang, J., Wang, Z., Zhao, L. (2019). A Monitoring Mechanism for Electric Heaters Based on Edge Computing. In: Ni, W., Wang, X., Song, W., Li, Y. (eds) Web Information Systems and Applications. WISA 2019. Lecture Notes in Computer Science(), vol 11817. Springer, Cham. https://doi.org/10.1007/978-3-030-30952-7_65
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DOI: https://doi.org/10.1007/978-3-030-30952-7_65
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