Research on Edge Computing Terminal for Low-Power Online Video Streaming Analysis

The edge computing terminal research is critical in low-power online video stream analysis, however it has an issue with erroneous performance positioning. The typical Particle swarm arithmetic is unable to address the computational research issue in low-power online video stream analysis, and the result is insufficient. As a result, a Particle swarm arithmetic-based research on low-power online video stream analysis edge computing terminal is provided, and research on low-power online video stream analysis edge computing terminal is assessed. To begin, the genetic analysis theory is used to discover the influencing elements, and the indicators are split based on the edge computing terminal research's needs to decrease interference factors in the edge computing terminal research. The genetic analysis theory is then used to create a Particle swarm arithmetic edge computing terminal research scheme, and the outcomes of the edge computing terminal research are thoroughly examined. The MATLAB simulation results reveal that, under particular evaluation conditions, the Particle swarm arithmetic outperforms the standard Particle swarm arithmetic in terms of edge computing terminal research accuracy and time of influencing variables.