Bridge IoT Emergency Supervision for Real-Time Reliability Control
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Solution Overview
Problem
Bridge emergency supervision faces challenges such as insufficient inspection coverage, untimely maintenance, lack of data-sharing mechanisms, and insufficient reliability supervision, leading to risks like vortex-induced vibrations and collapses, which may result in secondary disasters.
Innovation Solution
A large model-based Internet of Things (IoT) system for bridge emergency supervision, including an emergency supervision system with an integrated platform structure that determines bridge health, safety coefficients, and reliability levels, and generates appropriate responses such as traffic signal regulation, maintenance, and traffic regulation instructions, using sensors, robots, and smart barricades to control traffic signal lights, maintenance robots, and smart barricades to reinforce the bridge and ensure the safety of the bridge.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional bridge inspection methods are used, then inspection costs are low, but inspection coverage is insufficient and maintenance is untimely
Solution Approach 1:
The bridge supervision system is divided into multiple independent sensor nodes distributed at different locations on the bridge structure. Each sensor monitors specific parameters (vibration, displacement, temperature), and the data is aggregated by a gateway to the central platform. This segmentation enables comprehensive coverage without requiring a single complex centralized system.
Solution Approach 2:
The supervision system integrates multiple functions into a unified platform: real-time monitoring, data analysis, safety assessment, maintenance scheduling, and emergency response. The same sensor network serves both routine inspection and emergency supervision purposes, improving reliability while managing system complexity through multi-functionality.
2Productivity
If manual inspection methods are used, then labor requirements are low, but inspection coverage and timeliness are insufficient
Solution Approach 1:
The bridge monitoring system performs self-inspection through an automated sensor network that continuously monitors structural health without human intervention. Sensors automatically detect anomalies, the system self-diagnoses potential issues, and triggers maintenance alerts proactively, significantly improving inspection efficiency while the modular component design keeps the quantity of system components manageable.
Solution Approach 2:
Manual mechanical inspection methods are replaced with an automated sensor-based monitoring system that uses electronic and computational methods. Sensors replace manual surveyors, and automated data analysis replaces manual assessment, dramatically increasing productivity. The system uses standard sensor components and software tools, keeping the quantity of required components reasonable.
3Reliability
If real-time monitoring is implemented, then bridge safety is improved, but data processing complexity increases
Solution Approach 1:
The system extracts and processes only the critical information from the vast amount of sensor data. Rather than analyzing all raw data, the gateway filters and extracts key parameters (vibration amplitude, displacement thresholds, temperature anomalies) and transmits only these processed insights to the central platform, reducing data processing burden while maintaining safety supervision reliability.
Solution Approach 2:
The system performs preliminary data processing and analysis at the sensor gateway level before data reaches the central platform. Local preprocessing includes filtering noise, detecting anomalies, and generating alerts, which reduces the volume of data requiring central processing. This preliminary action maintains real-time safety monitoring while significantly reducing overall data processing complexity.
4Measurement precision
If comprehensive monitoring is implemented, then inspection coverage is improved, but system complexity increases
Solution Approach 1:
The monitoring system is segmented into standardized sensor modules that can be independently installed at various bridge locations. Each module performs specific measurements (vibration, displacement, temperature) and communicates through a uniform protocol to the gateway. This modular segmentation enables comprehensive monitoring coverage while keeping individual components simple and the overall system structure manageable.
Solution Approach 2:
The system transitions from single-point monitoring to multi-dimensional spatial monitoring by deploying sensors throughout the bridge structure. This dimensional expansion enables comprehensive coverage of different bridge components (deck, girders, piers) without requiring complex integrated systems, as each dimension is monitored by identical standardized sensors that aggregate data through the gateway architecture.
Data Source
AI summary
Provided are a method, a large model-based system of Internet of Things (IoT), and a storage medium for emergency supervision of a bridge in a smart city. The method is executed by an emergency supervision management platform of the large model-based system of IoT for emergency supervision of the bridge in the smart city. The method includes: determining a bridge health value of the bridge based on sensing data of a plurality of target locations on the bridge; determining a bridge safety coefficient based on first traffic flow data of the bridge; determining a bridge reliability level based on the bridge health value and the bridge safety coefficient; in response to the bridge reliability level satisfying a first predetermined condition, generating at least one of a signal light regulation instruction, a maintenance regulation instruction, or a traffic regulation instruction.