# The scope for AI-augmented interpretation of building blueprints in commercial and industrial property insurance

arXiv: https://arxiv.org/abs/2205.01671 · HTML: https://mlsanity.com/paper/2205.01671/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 5 of its 25 references that are in the map.
- First posted on arXiv 29 Apr 2022.

## Builds on (most cited first, 5 of 5)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Human pose estimation via Convolutional Part Heatmap Regression](https://mlsanity.com/paper/1609.01743/) (2016)
- [CubiCasa5K: A Dataset and an Improved Multi-Task Model for Floorplan Image Analysis](https://mlsanity.com/paper/1904.01920/) (2019)
- [Deep Floor Plan Recognition Using a Multi-Task Network with Room-Boundary-Guided Attention](https://mlsanity.com/paper/1908.11025/) (2019)
- [Room Classification on Floor Plan Graphs using Graph Neural Networks](https://mlsanity.com/paper/2108.05947/) (2021)

## Abstract (arXiv)

This report, commissioned by the WTW research network, investigates the use of AI in property risk assessment. It (i) reviews existing work on risk assessment in commercial and industrial properties and automated information extraction from building blueprints; and (ii) presents an exploratory 'proof-of concept-solution' exploring the feasibility of using machine learning for the automated extraction of information from building blueprints to support insurance risk assessment.