Perceptual information integrated access system based on urban important infrastructure

Abstract

The invention provides a perceptual information integrated access system based on urban important infrastructure. The perceptual information integrated access system comprises a supporting layer, a core business layer and a data application layer;the supporting layer comprises a basic library and a knowledge library; the core business layer comprises a diagnosis center, an emergency dispatching center, a safety center, a data center, a monitoring center, an operation center, a user center and an operation and maintenance center; and the data application layer comprises a statistical analysis center and a data sharing center. The system obtains various real-time monitoring information based on the Internet of Things technology, is in butt joint with existing monitoring system data based on the MQTT technology, establishes and maintains a holographic digital mapping model through a big data and deep learning multi-dimensional perception data association analysis algorithm, and realizes intelligent evaluation, analogue simulation, real-time early warning and quick response of urban important infrastructure disasters and emergencies.

Description

technical field [0001] The invention relates to the technical field of monitoring system information processing, in particular to an integrated access system for sensing information based on important urban infrastructure. Background technique [0002] Looking at the current situation of urban construction, it has become an inevitable trend in the development of modern cities to seek space, land, and resources underground. The current stage is the era of rapid and in-depth development of underground space development and utilization. At present, the number of underground facilities, including underground rail transit, underground complexes, and underground utility corridors, is growing rapidly, and the development and utilization are characterized by diversification, depth, and complexity. The pressure to ensure the safe and efficient operation of urban underground infrastructure is enormous. How to use advanced means such as the Internet of Things to realize the comprehens...

AI Technical Summary

Problems solved by technology

[0003] (1) There are many monitoring systems for various types of urban underground infrastructure, each planned separately, and the coherence is not strong. Data intercommunication between systems is impossible, data reversal process is blocked, and information sharing cannot be carried out. The phenomenon of "data islands" is becoming more and more serious

[0004] (2) The state monitoring of urban underground infrastructure mainly adopts wired methods, which requires large manpower investment and high monitoring costs. It is urgent to build a wireless heterogeneous fusion network system for complex underground environments

The existing wireless heterogeneous fusion strategies have problems such as complex network protocol conversion, low network transmission efficiency, poor network collaboration efficiency, and low network resource utilization. They lack the ability to provide ubiquitous access to the Internet of Things for massive monitoring terminals, and also Unable to provide continuous and reliable network service quality assurance for various monitoring applications

[0005] (3) The types and dimensions of existing monitoring data such as fire, equipment failure, and civil structure failure are single, forming information islands, and the time domain, space domain, object domain, and event domain of data are separated, and there is a lack of multi-dimensional spatio-temporal big data processing models

The safety status analysis, disaster early warning and trend prediction technology of various facilities are weak, and the efficient cluster processing and intelligent decision-making of large-scale spatiotemporal and disaster event data have not yet been realized

[0006] (4) Urban underground infrastructure faces a series of emergency problems such as complex emergency environment, few exits, limited space, few evacuation paths, and relatively weak information management. At the same time, multi-disaster emergency response involves multi-department coordinated command and multi-type emergency resource allocation. Basically rely on human command and decision-making, which is very difficult, and has not yet realized the transformation from passive acceptance to active response, and there is a shortcoming of emergency intelligent comprehensive decision-making command

[0007] (5) There is still a large gap between the existing monitoring system platform and the goal of holographic perception group construction, mainly reflected in the incomplete collection of perception, imprecise state capture, inconsistent networking methods, unrelated perception systems, and non-sharing of perception data, etc. question

At the same time, there is a lack of an integrated comprehensive management platform for real-time monitoring, trend deduction, and status evaluation and analysis of the operating status of underground infrastructure

[0008] (6) my country's urban underground infrastructure safety risk prevention and control is facing many problems, such as weak joint monitoring capabilities for various faults and disasters, fragmented monitoring systems, and lack of unified management; integrated solutions for design, construction, and operation and maintenance are stuck. At the stage of scientific research, no practical application demonstration has been formed; at present, it has not been possible to formulate a complete set of comprehensive solutions from the perspective of integration of design, construction, operation and maintenance, and move towards industrialization

[0009] To sum up, at present, the basic theories of underground infrastructure disaster mechanism analysis, disaster risk prediction, and multi-hazard coupling are not perfect, especially the lack of quantitative method support for risk decision-making, and the lack of vulnerability analysis of key nodes; in the state of underground infrastructure In terms of online monitoring technology, most of them are experimental studies, which are not scientific and systematic enough to realize long-term, long-distance, multi-dimensional and multi-parameter comprehensive monitoring

In terms of mobile inspections of underground infrastructure, regular manual inspections are mostly used, and the scope of inspections is not comprehensive, the efficiency is low, and it is easy to misjudge

However, the existing machine dynamic inspection equipment equipped with sensors has large detection errors due to multi-source data time out of sync.

To sum up, in terms of intelligent diagnosis and decision-making, there is a lack of a disaster classification and early warning system supported by effective data.

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