<![CDATA[Urban waste management in smart city development requires efficient and stable visual monitoring systems. Utilization of edge devices such as Raspberry Pi is often constrained by limited computational power for complex computer vision models, making edge server architecture a relevant solution. This study evaluates the performance of image transmission from a Raspberry Pi to a centralized server for YOLOv8 object detection by comparing MJPEG streaming and HTTP POST-based periodic snapshot methods. Evaluation metrics included median latency (p50), jitter, and tail latency (p95 and p99). The results indicate that MJPEG streaming provides more stable latency compared to snapshots, particularly at tight transmission intervals. The transmission interval proved to have a significant effect on inference pipeline stability, while image resolution showed no observable impact on latency distribution under the evaluated conditions. This research recommends selecting appropriate transmission strategies to maintain the reliability of visual monitoring systems. These findings provide practical guidance for designing reliable centralized visual monitoring systems in resource-constrained edge environments.]]>
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