Abstract
Datastreams are potentially infinite sources of data that flow continuously while monitoring a physical phenomenon, like temperature levels or other kind of human activities, such as clickstreams, telephone call records, and so on. Radio Frequency Identification (RFID) technology has lead in recent years the generation of huge streams of data. Moreover, RFID based systems allow the effective management of items tagged by RFID tags, especially for supply chain management or objects tracking. In this paper we introduce SMART (Simple Monitoring enterprise Activities by RFID Tags) a system based on outlier template definition for detecting anomalies in RFID streams. We describe SMART features and its application on a real life scenario that shows the effectiveness of the proposed method for effective enterprise management.
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References
Avnur, R., Hellerstein, J.M.: Eddies: Continuously adaptive query processing. In: Proceedings of the ACM SIGMOD International Conference on Management of Data, Dallas, Texas, USA, pp. 261–272 (2000)
Datar, M., Motwani, R., Babcock, B., Babu, S., Widom, J.: Models and Issues in Data Stream Systems. In: Twenty-first ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, Madison, Wisconsin, USA, pp. 1–16 (2002)
Li, X., Gonzalez, H., Han, J., Klabjan, D.: Warehousing and Analyzing Massive RFID Data Sets. In: Proc. of the ICDE Conference (2006) (to appear)
Madden, S., Hellerstein, J.M.: Distributing queries over low-power wireless sensor networks. In: ACM SIGMOD Int. Conf. on Management of Data, Madison (WI), USA (2002)
Raghavan, P., Henzinger, M.R., Rajagopalan, S.: Computing on data streams. Technical Report 1998-011, Digital Systems Research Center (1998), http://www.research.digital.com/SRC/
Gehrke, J., Bonnet, P., Seshadri, P.: Querying the Physical World. IEEE Personal Communication 7 (2000)
Alert System, http://www.alertsystems.org
Li Lee, M., Ganti, V., Ramakrishnan, R.: ICICLES: Self-tuning Samples for Approximate Query Answering. In: Proceedings of 26th International Conference on Very Large Data Bases, Cairo, Egypt, pp. 176–187 (2000)
Thakkar, H., Wang, H., Bai, Y., Luo, R.C., Zaniolo, C.: An introduction to the Expressive Stream Language (ESL). Tech. Report
Pei, J., Chen, Q., Liu, Y., Chen, L., Zhao, Y.: Mining frequent trajectory patterns for activity monitoring using radio frequency tag arrays. In: PerCom, pp. 37–46 (2007)
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Angiulli, F., Masciari, E. (2010). Effectively Monitoring RFID Based Systems. In: Catania, B., Ivanović, M., Thalheim, B. (eds) Advances in Databases and Information Systems. ADBIS 2010. Lecture Notes in Computer Science, vol 6295. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15576-5_5
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DOI: https://doi.org/10.1007/978-3-642-15576-5_5
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