Automating Document Intelligence in Statutory City Planning
Lars Malmqvist, Robin Barber

TL;DR
This paper introduces an AI system that automates document processing tasks in UK city planning, reducing administrative workload and legal risks while involving human oversight for accuracy.
Contribution
It presents an integrated AI-in-the-Loop system for automating document analysis, redaction, and feature extraction in city planning, with active learning to improve over time.
Findings
System piloted at four UK authorities
Demonstrated reduction in manual processing workload
Preliminary ROI model indicates potential cost savings
Abstract
UK planning authorities face a legislative conflict between the Planning Act, which mandates public access to application documents, and the Data Protection Act, which requires protection of personal information. This situation creates a manually intensive workload for processing large document volumes, diverting planning officers to administrative tasks and creating legal compliance risks. This paper presents an integrated AI system designed to address these challenges. The system automates the identification and redaction of personal information, extracts key metadata from planning documents, and analyzes architectural drawings for specified features. It operates with an AI-in-the-Loop (AI2L) design, presenting all suggestions for review and confirmation by planning officers directly within their existing software; no action is committed without explicit human approval. The system is…
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Taxonomy
TopicsArtificial Intelligence Applications · Smart Cities and Technologies · Geographic Information Systems Studies
