Remote monitoring method and system for super-deep underground space based on multi-source data fusion

By combining interface specifications, conversion modules, clustering algorithms, and prediction models, the problem of integrating multi-source heterogeneous data was solved, enabling real-time and accurate monitoring of ultra-deep underground spaces and improving risk warning capabilities.

CN121524916BActive Publication Date: 2026-07-21SINOHYDRO BUREAU 8 CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
SINOHYDRO BUREAU 8 CO LTD
Filing Date
2025-11-06
Publication Date
2026-07-21

AI Technical Summary

Technical Problem

Existing monitoring technologies struggle to effectively integrate multi-source heterogeneous data and geospatial information, resulting in low efficiency in data collection and analysis for ultra-deep underground space monitoring, and an inability to accurately reflect the actual state of underground space.

Method used

Initial data is obtained through a pre-defined interface specification. A conversion module is used to handle format differences. A clustering algorithm is used to group similar devices, embed location information, and generate an integrated dataset with annotations. Combined with the correlation information of environmental variable changes, the dataset is fused into a dynamic matrix. A classification model is used to identify abnormal patterns, generate a mapping layer, and a prediction model is used to estimate trend information to generate a risk distribution map.

Benefits of technology

It has achieved efficient collection and transmission of multi-source data, accurately mapped the actual state of underground space, constructed a real-time and accurate risk early warning system, and significantly improved the efficiency of environmental monitoring response.

✦ Generated by Eureka AI based on patent content.

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Abstract

The application discloses a kind of based on multi-source data fusion's super deep underground space remote monitoring method and system, initial data is obtained from multi-source equipment through preset interface, it is uniformly converted module for the sequence containing time and value;Then clustering algorithm grouping similar equipment embedding position, generate labeled integrated dataset;Again, if coefficient is over threshold, then it is fused into dynamic monitoring matrix;From which extract trend and identify abnormality by classification model, output labeled mapping layer;Accordingly generate transmission protocol data, and it is optimized to integrated variable relationship signal sequence by computing node;Finally, prediction model estimates trend key point, and generates the risk distribution graph of corresponding monitoring state.The fusion mechanism of dynamic monitoring matrix and signal sequence, realize the closed-loop circulation of data from heterogeneous to optimization, to accurately predict high-risk distribution, improve environmental monitoring response efficiency;Real-time, accurate risk early warning system is built, significantly reduce the loss of emergency.
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