Data acquisition and man-machine collaborative labeling method based on edge calculation

Abstract

The invention discloses a data acquisition and man-machine collaborative labeling method based on edge computing, and the method comprises the following steps: S1, selecting an edge device close to a data source, carding basic information of the device, and performing data acquisition; S2, constructing a labeling model by using a computer according to the type of the device; S3, preprocessing the data of the edge device, and estimating the proportions of different data; S4, sorting the labeling models according to the types of the data. During data acquisition, data which is not changed for a long time is monitored and is acquired until the data is changed, and the time interval of two changes is recorded, so acquisition of intermediate same data is reduced, tedious work of data collection and subsequent data annotation processing is simplified, regular change data is predicted, comparison monitoring and regular collection are implemented, collection of a large amount of useless data is reduced, and data storage space is saved.

Description

technical field

[0001] The invention relates to the technical field of edge computing, in particular to a method for data collection and man-machine collaborative labeling based on edge computing. Background technique

[0002] Edge computing refers to an open platform that integrates network, computing, storage, and application core capabilities on the side close to the source of objects or data to provide the nearest end services, and its applications are initiated on the edge side to generate faster network services. Response to meet the basic needs of the industry in terms of real-time business, application intelligence, security and privacy protection, etc. Edge computing is between physical entities and industrial connections, or at the top of physical entities, while cloud computing can still access the history of edge computing Data, labeling the data can make the data more convenient to analyze and use;

[0003] However, the current data collection and labeling of e...

Examples

Embodiment

[0042] Example: such as figure 1 As shown, the present invention provides a technical solution, a data collection and human-machine collaborative labeling method based on edge computing, including the following steps:

[0043] S1. Select an edge device close to the data source, sort out the basic information of the device, and collect data;

[0044] S2. Using a computer to construct a labeling model according to the type of equipment;

[0045] S3. Preprocess the data of the edge device and estimate the proportion of different data;

[0046] S4, and then sort the labeling models according to the type of data;

[0047] S5. Input data into the labeling model for labeling;

[0048] S6. Extract the data that took a long time to label and failed to label, and manually label, check and modify;

[0049] S7. Re-input the manually labeled data, and update the labeling model according to the cause of labeling failure;

[0050] S8. Transmitting the marked data to the edge computing d...

technical field

[0001] The invention relates to the technical field of edge computing, in particular to a method for data collection and man-machine collaborative labeling based on edge computing. Background technique

[0002] Edge computing refers to an open platform that integrates network, computing, storage, and application core capabilities on the side close to the source of objects or data to provide the nearest end services, and its applications are initiated on the edge side to generate faster network services. Response to meet the basic needs of the industry in terms of real-time business, application intelligence, security and privacy protection, etc. Edge computing is between physical entities and industrial connections, or at the top of physical entities, while cloud computing can still access the history of edge computing Data, labeling the data can make the data more convenient to analyze and use;

[0003] However, the current data collection and labeling of e...

Examples

Embodiment

[0042] Example: such as figure 1 As shown, the present invention provides a technical solution, a data collection and human-machine collaborative labeling method based on edge computing, including the following steps:

[0043] S1. Select an edge device close to the data source, sort out the basic information of the device, and collect data;

[0044] S2. Using a computer to construct a labeling model according to the type of equipment;

[0045] S3. Preprocess the data of the edge device and estimate the proportion of different data;

[0046] S4, and then sort the labeling models according to the type of data;

[0047] S5. Input data into the labeling model for labeling;

[0048] S6. Extract the data that took a long time to label and failed to label, and manually label, check and modify;

[0049] S7. Re-input the manually labeled data, and update the labeling model according to the cause of labeling failure;

[0050] S8. Transmitting the marked data to the edge computing d...

Images