Abstract
To process continuous sensor data in Internet of Things (IoT) environments, this study optimizes queries using multiple MJoin operators. To achieve efficient storage management, it classifies and reduces data using a support vector machine (SVM) classification algorithm. A global shared query execution technique was used to optimize multiple MJoin queries. By comparing each kernel function of the SVM classification algorithm, the system's performance was evaluated through experiments according to the selected optimal kernel function and changes in sliding window size. Furthermore, to implement a smart home system that can actively respond to users, classified and reduced sensor data were utilized to enable the intelligent control of devices inside the home. The sensor data (e.g., temperature, humidity, gas) used to recognize the current conditions of an IoT-based smart home system and corresponding date data were classified into decision trees, and the system was designed using five sensors to intelligently control priorities such as ventilation, temperature, and fire and intrusion detection. The experiments demonstrated that the multiple MJoin technique yields high improvements in performance with relatively few searches. In this study, the sigmoid was selected as the optimal kernel function for the SVM classification algorithm. According to the SVM classification algorithm results, based on changes in the sliding window size, the average error rate was 2.42%, the reduction result was 17.58%, and the classification accuracy was 85.94%. According to the comparison of the classification performance of SVM and other algorithms, the SVM classification algorithm exhibited a minimum 9% better classification performance. Thus, compared to existing home systems, this algorithm is expected to increase system efficiency and convenience by enabling the configuration of a more intelligent environment according to the user's characteristics or requirements.
Highlights
The purpose of the modern Internet of Things (IoT) is to provide services based on intelligent systems considering user convenience and accuracy
The sigmoid kernel function was selected as the optimal kernel function for the support vector machine (SVM) classification algorithm
Current systems in IoT environments use a large amount of various sensor data
Summary
The purpose of the modern Internet of Things (IoT) is to provide services based on intelligent systems considering user convenience and accuracy. The IoT-based smart home system transmits data that have been measured by the sensors to the server and uses the multiple MJoin operator to optimize queries. If the PrevID of a tuple is included in the PostID possessed by a purging tuple or dead tuple, the tuple is removed or a new dead vector value is added If this search is executed without a separate data structure, all tuples in the join operator are evaluated based on the index. IoT-BASED SMART HOME SYSTEM The IoT-based smart home system distinguishes the sensor data that have been classified and reduced by the SVM classification algorithm and sets the priorities among tasks This was designed to operate tasks and devices according to the environmental changes within the home. The user can intervene at the desired moment and control the device’s operation, and user-customized services can be provided [36], [37]
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