AI-powered solutions for quality inspection, knowledge management, and safety monitoring improve defect detection, accelerate information access, and enhance operational safety.
Apply image recognition and multimodal models to detect defects in appearance, sound, and vibration data, enhancing quality control.
Use large models to process and summarize technical documents, enabling quick Q&A, knowledge retrieval, and training.
Monitor video, sensors, and logs in real time to identify hazards, issue early warnings, and protect people and equipment.
This dataset contains video samples for detecting foreign object suspension on transmission lines, aiding in power inspection automation.
This dataset focuses on the detection and analysis of abnormal events involving the uncontrolled movement of large machinery.
This dataset is used to identify and analyze shockwave events caused by explosions within factory premises.
This dataset is used to identify irregular vibrations, abnormal sounds, jumps, and other precursor behaviors of faults during the operation of fans.
This dataset is used for identifying the leak and diffusion processes of flammable liquids, providing support for safety monitoring.
This dataset is used to detect high-pressure gas leak events, aiding in industrial safety monitoring and management.
This dataset focuses on the detection and analysis of short-circuit events in electrical equipment, assisting in safety monitoring and equipment maintenance.
This dataset is used to monitor and analyze the dynamic spread behavior of open flames in industrial environments.
This dataset provides video data of conveyor belt operation anomalies to help identify fault issues.
This dataset is used to detect illegal standing behavior under lifting operations to enhance site safety monitoring effectiveness.
This dataset is used to detect violation behavior when workers contact high-temperature equipment without wearing gloves.
This dataset is designed to identify workers not wearing protective goggles and masks during welding operations, enhancing the efficiency of safety monitoring.
This dataset focuses on the recognition and analysis of industrial packaging sealing actions.
This dataset monitors the consistency of actions in standard assembly steps, aiming to enhance industrial automation levels.
This dataset focuses on action recognition and path analysis in welding operations, providing diverse video data to support research and applications.
This dataset is used to identify if an operator or robot has correctly completed a tightening action.
This dataset is used to recognize the grasping path, posture, and gripping actions of a robotic arm on objects.
The Air Fryer Heating Coil Damage Detection Dataset focuses on identifying damage to heating coils to prevent fire risks.
This dataset is used to detect whether the dust cup of a vacuum cleaner is closed, improving the detection efficiency of industrial equipment.
This dataset is used to determine whether the closure of an electric kettle lid is abnormal to prevent steam leakage and scalding.
Lightning-Fast Response, 1:1 Technical Validation