Edge-Based Agentic Retrieval-Augmented Generation for Autonomous FHWA Bridge Inspection Compliance
4.00T1 sourcearXiv cs.MA
Source record
Published by arXiv cs.MA (T1 source). The original is at https://arxiv.org/abs/2608.20372.
Pipeline notes
The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.
SummaryBridgeGuard is an air-gapped, edge-deployed agentic RAG system for FHWA bridge inspection compliance. It combines vector search over regulatory guides with SQL queries on NBI data, orchestrated by a multi-step ReAct agent. A section-aware chunking method preserves regulatory item boundaries, yielding 94.2% chunk integrity versus 28.4% for naive splitting, and 99.77% accuracy on Delaware's 874-bridge inventory.
Why it mattersDemonstrates a fully offline, multi-step agentic RAG pipeline that meets regulatory compliance at edge scale. The chunking comparison and ablations are directly applicable to other field-based compliance workflows.
Cited by
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