SkyVision Platform Enables Efficient Comparison of Two - Handed Operation Specifications

In industrial production, the implementation of two-handed operation specifications directly affects production safety and efficiency. DaoAI's SkyVision zero-code video surveillance AI platform provides an efficient and accurate solution for the comparison of two-handed operation specifications in industrial SOP.

User scenario: A leading industrial manufacturer's product production involves complex assembly processes. In a specific assembly production line, workers are required to strictly follow the two-handed operation specifications. The detection object is whether the workers' two-hand movements during operation comply with the standard SOP process. This process is crucial for ensuring product quality and production safety.

Pain points: In terms of quantitative dilemmas, the traditional manual detection method has many problems. On the one hand, the labor cost is high, and long-time detection can easily lead to fatigue of inspectors, with a missed detection rate as high as 12%, making it difficult to ensure the accuracy and consistency of detection. On the other hand, as the industry's attention to the application of edge-side AI in the field of intelligent security increases, the traditional detection method is far from sufficient in terms of real-time performance and intelligence. At the same time, when the production line is reconfigured, it is necessary to retrain the inspectors, and the reconfiguration time is up to 3 hours, seriously affecting production efficiency. In addition, due to the lack of effective monitoring means, it is difficult to ensure workers' compliance with operations, and there are certain safety hazards.

Technical principle

The SkyVision zero-code video surveillance AI platform uses advanced computer vision algorithms and deep learning technologies. In terms of imaging, high-precision industrial cameras are used to capture real-time images of workers' two-hand movements. The convolutional neural network (CNN) is used to extract and analyze features of the images, which can accurately identify the position, posture, and movement trajectory of the two hands. The core algorithm continuously learns and optimizes to model the standard two-handed operation specifications. During the model training process, combined with the semantic understanding ability of the DaoAI World model, the platform can understand the meaning and correlation of different actions, thus accurately judging whether the current two-hand movements comply with the specifications. Due to the use of edge-side AI technology, data is processed and analyzed in real-time on the local edge box without transmitting a large amount of data to the cloud, greatly improving the processing speed and data security.

• High - precision imaging: Industrial cameras provide clear and accurate image data, laying the foundation for subsequent analysis.
• Deep learning algorithm: CNN can automatically learn and identify complex action features, improving the recognition accuracy.
• Semantic understanding: The DaoAI World model endows the platform with the ability to understand the semantics of actions, enhancing the accuracy of judgment.
• Edge - side processing: The edge box processes data in real-time, reducing data transmission delay and ensuring real-time alarms.

DaoAI Solution and Product

Centered around the SkyVision zero-code video surveillance AI platform, this platform has the ability to train its own models on - site within hours and can quickly adapt to different operation specifications and scenarios. During deployment, simply install the industrial camera in a suitable position and connect it to the edge box to start real-time monitoring. Through the zero-code operation interface, users can easily define the standard actions of two-handed operations, and the platform will automatically perform model training without professional programming knowledge. At the same time, the platform supports the semantic understanding of the DaoAI World model, enabling more accurate recognition and judgment of actions. When non-compliant actions are detected, the edge box will immediately issue a real-time alarm to notify relevant personnel for processing. In addition, DaoAI's AI AOI software system can be used as a supporting tool to provide feature recognition of the visual basic model and assist the SkyVision platform in more accurate analysis.

The SkyVision platform makes the detection of industrial two-handed operation specifications more intelligent and efficient.

Quantitative results: By using the SkyVision platform, the detection rate of the manufacturer's two-handed operation specifications has increased to 98.2%, and the missed detection rate has decreased to <1.8%, greatly improving the detection accuracy. At the same time, the false alarm rate has been reduced by -75%, reducing unnecessary interference. In terms of production line reconfiguration, the reconfiguration time has been shortened from the original 3 hours to 5min, significantly improving production efficiency.