SafeStep：面向行人安全监测的语义通信交互式演示系统
SafeStep: An Interactive Demonstration of Semantic Communication for Pedestrian Safety Monitoring
- Auburn University（奥本大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文开发了SafeStep这一实时语义通信平台，对比Meta-VIB等收发器，证实Meta-VIB损失降低92.1%，且SafeStep可观测AoI诱导的性能下降，是同类平台首例。
AI中文摘要：
本文开发了SafeStep，这是一款基于浏览器的交互式语义通信平台，用于实时行人安全监测。SafeStep从四路实时交通摄像头馈送中提取行人信息，通过加性高斯白噪声（AWGN）信道上的语义通信收发器传输该信息，并渲染用户特定的位置、轨迹和风险标签。该平台允许独立选择收发器、信噪比（SNR）、码长和信息年龄（AoI），并通过向每个浏览器的实时行人安全监测展示所选配置的收发器性能。SafeStep将最新提出的名为Meta-VIB的语义通信设计与五个基线收发器进行比较。Meta-VIB使用仅含416万参数的紧凑神经模型，可在不同SNR、码长和AoI值间泛化，无需在线重新训练。实验结果显示，Meta-VIB实现了高达92.1%的平均任务损失降低。在一台高端GPU服务器上，集成并发访问工作负载通过20个用户维持目标5帧/秒的速率；在100个用户各请求不同配置时，SafeStep无请求失败，平均应用响应时间低于1秒，但平均每浏览器帧率降至约1帧/秒。据所知，SafeStep是首个能在实时监测应用中直接观测到AoI诱导的下游性能下降的实时语义通信平台。
英文摘要：
In this paper, we develop SafeStep, an interactive browser-based semantic communication platform for live pedestrian safety monitoring. SafeStep extracts pedestrian information from four live traffic-camera feeds, transmits it through a semantic communication transceiver over a software-emulated Additive White Gaussian Noise (AWGN) channel, and renders user-specific positions, trajectories, and risk labels. The platform allows each user to select the transceiver, Signal-to-Noise Ratio (SNR), codelength, and Age of Information (AoI) and view the resulting pedestrian reconstruction. SafeStep compares a recently proposed semantic communication design called Meta-VIB with five baseline transceivers. Meta-VIB uses a compact neural model with only $4.16$ million parameters to generalize across varying SNR, codelength, and AoI values without online retraining. Meta-VIB achieves mean task-loss reductions of up to $92.1\%$. On one high-end GPU server, the integrated concurrent-access workload maintains the target $5$ frames/s through $20$ users. At $100$ users, each requesting a distinct configuration, SafeStep records no request failures and a mean application response time below $1$ s, but its mean per-browser frame rate falls to approximately $1$ frame/s. To our knowledge, SafeStep is the first real-time semantic communication platform to make AoI-induced downstream degradation directly observable in live monitoring applications.
