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

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