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A RAG-enhanced multi-agent LLM/VLM framework for auditable and region-aware structural health monitoring of a historic masonry structure - Nature

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IntroductionHistoric masonry minarets are slender, tall structures that embody cultural identity while remaining vulnerable to progressive deterioration and sudden hazards1,2. Aging mortar, material heterogeneity, environmental exposure, nearby construction, and seismic activity can introduce cracks, detachments, and out-of-plane deformations that are difficult to detect early, especially when access is limited and interventions must be minimally invasive. Structural health monitoring (SHM) for such heritage assets therefore benefits from non-contact sensing and data-driven inference that can operate continuously, localize damage, and provide interpretable evidence to support conservation decisions. For tall, slender masonry forms, monitoring is additionally complicated by geometric discontinuities (e.g., balconies, openings, and transitions), spatially varying material properties, and complex soil–structure interaction, all of which can concentrate damage and alter dynamic response over time3,4,5.

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