Intelligent identification system and method for worker edge falling facing dangerous omen reasoning

A technology for intelligent recognition and workers, applied in neural learning methods, character and pattern recognition, instruments, etc., can solve problems such as high false positive rate of perception results, achieve hardware development, improve detection accuracy, and wide detection range

Pending Publication Date: 2022-04-15
JIANGSU UNIV
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Problems solved by technology

However, if we only rely on the superpower of computer vision in the field of image perception and ignore the semantic relationship between perceived objects, t

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  • Intelligent identification system and method for worker edge falling facing dangerous omen reasoning
  • Intelligent identification system and method for worker edge falling facing dangerous omen reasoning
  • Intelligent identification system and method for worker edge falling facing dangerous omen reasoning

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Embodiment Construction

[0046] The present invention will be further described below in conjunction with accompanying drawing and specific embodiment, so that those skilled in the art can understand the present invention better and can implement, but the embodiment given is only for explaining the present invention, does not serve as to the present invention limited.

[0047] figure 1 The embodiment of the present invention provides an intelligent recognition system for workers falling on the edge of danger-oriented reasoning. The recognition system is composed of a construction edge operation image acquisition unit, a semantic database model, an edge dangerous area extraction model, and a worker behavior state extraction model. It is cascaded with the semantic reasoning model.

[0048] The construction edge operation image acquisition unit is used to collect the construction edge operation image; and input the edge dangerous area extraction model and worker behavior state extraction model respectiv...

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Abstract

The invention discloses a worker limb falling intelligent identification system and method oriented to risk omen reasoning, and the method comprises the steps: extracting features of key objects of limb falling scenes, and determining the spatial range of each limb dangerous scene; knowledge structured combination is carried out according to the subject class, the attribute class, the object class, the position class and the behavior state class, and a limb area insurance mega knowledge graph is constructed through a graph database; performing visual identification on the edge falling dangerous area and the characteristics of the behavior state of the worker; and evaluating the safety state of the worker limb operation by utilizing graph database reasoning according to a visual identification result. According to the method, in combination with the behavior state of a worker, the constructed edge region risk omen knowledge rule is utilized, and the edge risk omen event is identified on the basis of intelligent visual detection. The system is high in intelligent level, and has high expansibility and practical value.

Description

technical field [0001] The invention relates to the technical field of semantic understanding of computer vision, including deep learning technology and semantic reasoning technology, and in particular to an intelligent recognition system and method for a worker's edge fall oriented to dangerous reasoning. Background technique [0002] The construction industry is an important industry supporting social and economic development, and it is also a typical high-risk industry. Among the many types of safety accidents, falling from heights is the most important type of accidents, accounting for more than half of the accidents. In various high-altitude operation scenarios, climbing, suspension, platform, and cross operations are difficult, and experienced workers are usually selected and equipped with reliable safety equipment, and the probability of falling accidents from heights is very small. However, falling from the edge operation, which is not very difficult, has become the...

Claims

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Application Information

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IPC IPC(8): G06V20/52G06K9/62G06N3/04G06N3/08G06V10/25G06V10/44G06V10/774G06V10/82
Inventor 刘泽锋韩豫吴晗
Owner JIANGSU UNIV
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