Mining Correlation Patterns among Appliances in Smart Home Environment

Methods for Abnormal Usage Detection in Developing Intelligent Systems for Smart Homes

“…This performance study has been conducted on a real world dataset which is taken from [1] including six appliances as presented in Table 2. The database used in training and testing consist a collection of usage logs for 45 days and 15 days, respectively.…”

“…Abnormal usage detection can help residents not only reducing electricity consumption, but also having benefit for the environment. However, previous researches [1,2] have been focused on analysis of the usage behavior on single device and neglect of the appliance correlations. Actually, the correlation among the usage of some appliances can provide valuable information to assist residents better detect abnormal usage of their appliances.…”

Discussions on the Pattern Development of Smart Home Design

“…It has become a bottleneck restricting the development of the industry. To solve this problem in the design of the system, they should consider the installation and maintenance convenience, through the network, not only the household can realize the control function of family intelligent system, also allows the engineering staff in the work of the remote inspection system, carry on the fault diagnosis system [7]. In this way, system settings and version update can be carried out in different places, which greatly facilitates the application and maintenance of the system, improves the response speed and reduces the maintenance cost.…”

Incremental Temporal Mining using Incremental TPMiner and Incremental P-TPMiner Algorithms

“…Chen, C. Chen, W. Peng and W. Lee, [2] In this paper, a novel algorithm, namely, Correlation Pattern Miner(CoPMiner), is developed to capture the usage patterns and correlations among appliances probabilistically effectively and efficiently. Search space is reduced by using CoPMiner.…”