Factory three-dimensional positioning monitoring method based on big data and grouping task presetting

Abstract

The invention discloses a factory three-dimensional positioning monitoring method based on big data and grouping task presetting. The method mainly comprises the steps of1 defining effective ranges bytaking positioning devices as base points, combining the effective ranges of a plurality of positioning devices into a construction area so as to divide a factory into a plurality of construction areas, and setting an electronic map of the factory; 2 setting a plurality of personnel who cooperatively execute the same task as a task group, and presetting and recording a predetermined task route ofeach task group in a factory; 3 identifying the identity of the personnel entering the factory, and determining a task group and a predetermined task route; and 4 comparing the actual task route of each person with a predetermined task route, sending alarm information as long as the actual task route of one person deviates from the predetermined task route in one task group, and highlighting thealarm information on an electronic map.

Description

technical field [0001] The invention relates to the technical field of construction safety, in particular to a factory stereo positioning monitoring method based on big data and group task preset. Background technique [0002] A large factory has a large area, a large number of personnel, a complex environment, and many confidential areas. Many employees work in different positions, and even a specific task requires multiple people to cooperate. In order to facilitate management, communication and unified scheduling, it is necessary to quickly understand the real-time location and work progress of each person at any time, as well as the progress of each task group, otherwise it may cause one person to affect the entire task group, and one task group to affect the entire project The phenomenon of progress occurs, seriously reducing work efficiency. In addition, the workshops of large factories are often multi-storey buildings. Compared with flat construction factories, it i...

AI Technical Summary

Problems solved by technology

In order to facilitate management, communication and unified scheduling, it is necessary to quickly understand the real-time location and work progress of each person at any time, as well as the progress of each task group, otherwise it may cause one person to affect the entire task group, and one task group to affect the entire project Progress phenomenon occurs, seriously reducing work efficiency

In addition, the workshops of large factories are often multi-storey buildings. Compared with flat construction factories, personnel positioning and supervision are more difficult

[0003] Although there are methods for automatic positioning of factory personnel in the prior art, it is generally only to determine the position of each member, and it is impossible to intuitively understand the progress of their task execution, and it is also impossible to intuitively understand the overall situation of each task group. It cannot be ruled out that normal staff members enter abnormally

[0004] In addition, factories often have multiple confidential places, and irrelevant personnel are not allowed to enter. At present, security measures such as card swiping, face recognition, and smart locks are generally adopted to allow certain people to have permission to open due to work needs.

However, at present, these methods cannot avoid the entry of people with opening authority during non-working hours, or the entry of unrelated personnel using work cards, resulting in loopholes in security measures

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