The excavation site robotic arm action control dataset enhances the efficiency of intelligent control in the construction and real estate industry.

This dataset provides high-quality image data for road damage detection in the construction industry.

This dataset focuses on detecting personnel working at heights in scaffold areas.

Train models to check underground mine procedures step by step for sequencing errors, unsuitable support measures, and omitted controls.

Train models to verify construction conclusions more reliably by linking submittal content to project requirements and supporting evidence.

A high-quality image dataset for face geological recognition in tunnel construction environments.

Evaluate how well models interpret numerical conditions, applicable configurations, and restrictions in scaffolding design and load specification texts.

Train models to assess commercial and industrial rooftop solar feasibility by reasoning across roof, load, structural, shading, and grid constraints.

The tunnel construction site safety helmet wearing detection image dataset is used to detect the wearing conditions of safety helmets by personnel at the construction site.

This dataset is used to detect the encroachment of roads by material stacking at construction sites.

This dataset is used to predict the icing thickness of transmission lines, enhancing the monitoring and maintenance efficiency of the energy sector.

Cross-check payment application claims against contract terms and site records to help models identify insufficient evidence, missing measurement grounds, and conflicting records.

This dataset is used to identify the material stacking situation at construction sites to improve site management and safety.

The Transmission Line Vegetation Hazard Prediction Image Dataset is used to enhance the efficiency of vegetation management around transmission lines in the energy sector.

Check safety constraints step by step to pinpoint omitted controls, incorrect ordering, and conflicts in mine-work responses.

The Post-Disaster Ruins Drone Aerial Damage Assessment Dataset provides high-precision aerial imagery for building damage assessment.

The Construction Machinery Noise Pollution Audio Dataset aims to support environmental noise monitoring and control.

Extract hazards, exposed entities, and control measures from work-at-height observations to streamline the structuring of safety records.

Explore planning steps and risk-control evidence for demolition preparation, and evaluate the accuracy and traceability of RAG retrieval.

This dataset is used for detecting the wearing status of safety equipment for personnel within construction areas.