Utility-Aware Progressive Inference over UDP Packet Blocks for Emergency Communications
Jiayue Wang, Zhiyuan Ren, Tao Zhang, Wenchi Cheng

TL;DR
This paper introduces a utility-aware progressive inference framework for emergency UDP communications that enables early hazard detection by analyzing partial packet blocks, reducing delay and bandwidth use.
Contribution
It proposes a novel method that operates directly on UDP packet blocks, estimating utility for early decision-making, which improves efficiency and timeliness in hazard recognition.
Findings
Reduces average packet usage by 34.2%.
Decreases decision delay by over 1200 ms.
Maintains high detection accuracy with 91.5% match rate.
Abstract
Emergency communications increasingly rely on remote visual inference for timely hazard detection under stringent bandwidth and latency constraints. However, conventional UDP-based visual delivery typically performs inference only after the full payload has been received, even though partially received packet blocks may already contain sufficient task-relevant evidence for reliable decision making. This paper proposes a utility-aware progressive inference framework for emergency communications, which operates directly on UDP packet blocks and determines when sufficient task value has been accumulated for early hazard recognition. Specifically, the sender estimates packet-level decision utility as lightweight control metadata, while the receiver progressively updates partial observations, accumulates the utility of received packets, and triggers an early stop once the normalized utility…
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