Abstract
For the successful operation of smart home environments, it is important to know the state or activity of an occupant. A large number of sensors can be deployed and embedded in places or things. All sensor nodes measure the physical world and send data to the base station for processing. However, the processing of all collected data from every sensor node can consume significant energy and time. In order to enhance the sensor network in smart home applications, we propose the irrelevant data elimination based on k-means clustering algorithm to enhance data aggregation. This approach embeds the cluster head–based algorithm into cluster heads to omit irrelevant data from the base station. The pattern of measured data in each room can be clustered as an active pattern when human activity happens in that room and a stable pattern when human activity does not happen in the room. The irrelevant data elimination based on k-means clustering algorithm approach can reduce 55.94% of the original data with similar results in human activity classification. This study proves that the proposed approach can eliminate meaningless data and intelligently aggregate data by delivering only data from rooms in which human activity likely occurs.
Highlights
The smart home has been of interest to many studies and for many applications, such as automatic controlling appliances and elderly assistance
We compared the quality of data aggregation and the size of the dataset being transmitted between the full data transmission approach, the EK-means approach,[18] and our cluster-based data transmission approach
The performance results of the data reduction with the existing aggregation approach, called the EK-means aggregation algorithm at the sensor level, show results with different values for the required parameters, which include the period size of the data represented by point T and a similarity threshold d between the two readings of data
Summary
The smart home has been of interest to many studies and for many applications, such as automatic controlling appliances and elderly assistance. Smart homes can improve the lives of occupants and the elderly by utilizing ambient sensors to capture the presence and behavior of occupants for active and assisted living (AAL) purposes. A smart home communication system can be divided into an external network, a base station network, and an internal network.[1] This network can be wired or wireless, and the Internet is used to interconnect devices in the home; the smart home is one of the applications of the Internet of things (IoT). Sensors or devices can be placed everywhere, measure the physical world, and transmit data to the base station by communicating through a network based on the IoT.[2] Gathering huge data in sensor networks can be found in a wide area, such as a smart
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