The Efficient Data Classification using SVMcW for IoT Data Monitoring and Sensing

摘要

The developing of the wireless network supports the high transmission data rate and low latency for UEs. Hence, extensive data and application are the main reason for enhancing the usage of IoT. With the IoT device increasing; it means that more data need to be processed and analyzed. In order to reduce the process time and power consumption, we proposed the method of the smart monitor to the director the IoT data, and the Support Vector Machine (SVM) to classify data. By this way, the data process can achieve real-time processing. Besides, to solve the disadvantage of SVM and reduce the training time, we involved the concept of weight in the feature of SVM. Finally, the simulation results show that our method can reduce the training time and guarantee the classifier accuracy.