An app that catches safety violations from a single site photo
AIMade by AISummarised by AI (Claude) from one piece of material it read (a talk or an explainer).How it's made
AI use cases that employees built themselves at a worksite in Korea's largest oil-refining and petrochemical complex were made public. The most striking is a safety-inspection tool: upload a photo of the site and pick the type of work, and it compares the photo against a vast body of work-standard and risk-assessment documents and points out violations. The key point is that it is not a vision model judging whether something is defective but a rule-matching structure in which the AI holds the regulations and people supply only the observations. In the demo it caught inadequate collapse-prevention measures and a missing hard hat, plus a slip hazard from water pooled on the floor, which people had missed by eye. However, the model used, the way documents are referenced, and the accuracy and false-detection rates are not disclosed at all, so it comes with the caveat that it should be read as a catalog for finding projects rather than as an implementation reference.
Key points
- Built because, with 3,000–4,000 people a day entering a complex of 2.5 million pyeong (about 8.3 km²), supervisors cannot go through all the reference documents
- Just uploading a photo and choosing the work type produces output in 2 stages: an analysis against the safety guide, and violations of the risk assessment
- Also presented: a division-of-labor approach that hands off document review first, and running 3 agents at once by loading context in advance and only pressing approve
- At the same event an agent made up nonexistent education and awards, laying bare the risk of unreviewed output
This is a note: a summary an AI (Claude) wrote of one piece of material it read (a talk or an explainer). It has no source link; events checked against a source are kept as records.