Recently, due to the great advent of sensor
technology, residents can collect the usage data of appliances in a house easily. However, with data progressively generating, it is still a challenge to visualize how these appliances are used. Thus, a mining and maintaining system is needed to incrementally discover appliance usage
patterns. Most previous studies on usage
pattern discovery are mainly focused on analyzing the patterns of single appliance and do not consider the incremental maintenance of mining results. In this paper, a novel system, namely, Dynamic Correlation Mining System (DCMS) is
developed to capture and maintain the correlation patterns among appliances incrementally. The experimental results indicate that proposed system is efficient in execution time and possesses scalability. Furthermore, we apply DCMS on a real-world dataset to show the practicability.
The 10-th Workshop on Wireless, Ad Hoc and Sensor Networks (WASN 2014)