Fractal-Based Outlier Detection Algorithm over RFID Data Streams

Li Lian Sheng

Abstract


Nowadays, Radio frequency identification (RFID) has been extensively deployed to retailing, supply chain management, object recognition, object monitoring and tracking and many other fields. Detecting outliers in RFID data streams can help us find abnormal activities and thus avoid disasters. In order to detect outliers in RFID data streams efficiently and effectively, we proposed a fractal based outlier detection algorithm. Firstly, we built a monotone searching space based on the self-similarity of fractal. Then, we proposed two piecewise fractal models for RFID data streams, and presented an outlier detection algorithm based on the piecewise fractal model. Finally, we validated the efficiency and effectiveness of the proposed algorithm by massive experiments.

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International Journal of Online and Biomedical Engineering (iJOE) – eISSN: 2626-8493
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