STEM与日常科技·英语30篇（1）
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Edge Computing and the Need for Low Latency
边缘计算与低延迟场景
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When self-driving cars detect a pedestrian, they must react in under 100 milliseconds — too slow if data travels to a distant cloud server.
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Edge computing places processing power close to where data is generated, such as inside traffic cameras or factory machines.
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This reduces delay, or latency, by cutting transmission distance and avoiding network congestion during peak hours.
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In smart factories, edge devices instantly adjust robotic arms when sensors spot misaligned parts on a conveyor belt.
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Video analytics for crowd monitoring also relies on edge AI to flag anomalies without sending raw footage online.
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Unlike traditional cloud models, edge systems prioritize speed and local decision-making over centralized storage.
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They often work alongside the cloud: edges handle urgent actions, while the cloud analyzes long-term trends.
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5G networks further boost edge computing by providing ultra-fast, reliable connections between devices and local servers.