Grouping and time-series notifying of periodic data in a real-time streaming system for smart toy claw machine

Abstract

Abstract Traditional online claw machine has defects such as video delay, which affects the accuracy of the operation when the operator operates the claw machine. When there are too many viewers on-line that watch the operation of the smart toy claw machine by the operator, the video will be a delay. The traditional online claw machine is lack of interactive features. It also cannot increase the number of viewers and create discussion topics to attract more consumers. This paper proposes a real-time streaming system for a smart toy game machine. It can improve the above shortcomings and reduce costs and improve network management efficiency. The player can operate and control the device without delay based on the proposed framework. This system will allow the large number of viewer ends that do not need to control the online smart toy claw machine to view the real-time video smoothly. This system allows an increase in the number of the viewers end and let the viewers end creates discussion topics that attract more consumers. In this study, we propose a grouping and time-series (GT) notifying of periodic data of customer-premise equipment (CPE) WAN management protocol (called GT_CWMP). The network traffic and server processing time can be reduced 98% and 89% compared to the normal and random methods, respectively.