Integrated safety management system based on intelligent analysis of thousand eyes video

In response to the weak personnel safety management and relatively low integration with intelligent control systems in the current intelligent development process of the coal mining industry, a comprehensive safety management system based on “thousand eyes” video surveillance analysis has been constructed. The system architecture and advantages were introduced, with a focus on the functional modules of “thousand eyes” big data safety analysis and decision-making, “thousand eyes” AR+AI augmented reality intelligent scene analysis, big data intelligent risk control analysis, “thousand eyes” intelligent video platform, AR+AI augmented reality intelligent scene analysis, device intelligent control linkage protection decision-making, and comprehensive safety management. The comprehensive safety management system based on the “thousand eyes” video surveillance analysis is based on a distributed microservice architecture application system. With the help of AI intelligent recognition technology and AR augmented reality technology, it has formed a standardized gradient management mode process of “image capture, information recognition, platform warning+background recording, remote warning+linkage control”, which unifies and efficiently manages equipment operation and production, effectively avoids potential dangers and safety hazards, and maximizes the efficient operation of underground equipment and personnel safety.

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-12-01
DOI
https://doi.org/10.13347/j.cnki.mkaq.20240378
Primary Topic
Mycorrhizal Fungi and Plant Interactions
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Integrated safety management system based on intelligent analysis of thousand eyes video

SHILAP Revista de lepidopterología
Mycorrhizal Fungi and Plant Interactions
article

Integrated safety management system based on intelligent analysis of thousand eyes video

article en

Abstract

In response to the weak personnel safety management and relatively low integration with intelligent control systems in the current intelligent development process of the coal mining industry, a comprehensive safety management system based on “thousand eyes” video surveillance analysis has been constructed. The system architecture and advantages were introduced, with a focus on the functional modules of “thousand eyes” big data safety analysis and decision-making, “thousand eyes” AR+AI augmented reality intelligent scene analysis, big data intelligent risk control analysis, “thousand eyes” intelligent video platform, AR+AI augmented reality intelligent scene analysis, device intelligent control linkage protection decision-making, and comprehensive safety management. The comprehensive safety management system based on the “thousand eyes” video surveillance analysis is based on a distributed microservice architecture application system. With the help of AI intelligent recognition technology and AR augmented reality technology, it has formed a standardized gradient management mode process of “image capture, information recognition, platform warning+background recording, remote warning+linkage control”, which unifies and efficiently manages equipment operation and production, effectively avoids potential dangers and safety hazards, and maximizes the efficient operation of underground equipment and personnel safety.

SHILAP Revista de lepidopterología
Openalex Percentile: Top 51%
Mycorrhizal Fungi and Plant Interactions
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.