System for monitoring road bridge through AI
Through AI monitoring of road bridge systems, sensors and AI analysis technology are used to solve the problems of untimely update of existing system information and inaccurate early warnings, real-time monitoring and accurate early warning are achieved, and traffic safety and management efficiency are improved.
Patent Information
- Application Number
- CN202411271232.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-11
- Publication Date
- 2024-12-27
AI Technical Summary
The existing road and bridge monitoring systems have problems such as untimely update of information and insufficient early warnings, resulting in serious road traffic accidents and congestion problems.
A system for monitoring road bridges through AI is designed, including data acquisition unit, data transmission unit, AI analysis unit, professional audit unit, broadcast push unit and alarm notification unit. The sensor module is used to monitor data in real time, and the data encoding and transmission module is used to monitor data in real time. Ensure accurate data transmission, the AI analysis module conducts in-depth analysis, the professional audit module conducts audit, and the broadcast push module promptly notify users.
Real-time and accurate road and bridge status monitoring and early warning are achieved, traffic safety and management efficiency are improved, and timely information transmission and accurate user reception are ensured.
Smart Images
Figure CN119211287A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the technical field of intelligent transportation systems, and in particular relates to a system for monitoring roads and bridges through AI. Background Art
[0002] At present, road traffic accidents and congestion are becoming increasingly serious, partly because the real-time status information of roads and bridges cannot be quickly and accurately conveyed to drivers and traffic management departments. Existing monitoring and early warning systems mostly use manual inspections or simple sensors, which have problems such as untimely information updates and inaccurate early warnings. With the development of artificial intelligence and Internet of Things technologies, it is possible to achieve a more efficient and intelligent road early warning system. Summary of the invention
[0003] The purpose of the present invention is to provide a system for monitoring roads and bridges through AI, which includes a sensor module, a data acquisition module, a communication module, a data storage module, a data preprocessing module and a control module through a data acquisition unit, so that the operator uses the sensor module to monitor and detect the physical or chemical quantities of the target environment or object in real time. It collects data through various sensors. These sensors convert analog signals into electrical signals for further processing, solving existing problems.
[0004] In order to solve the above technical problems, the present invention is achieved through the following technical solutions:
[0005] The present invention is a system for monitoring roads and bridges through AI, comprising a data acquisition unit, wherein the output end of the data acquisition unit is provided with a data transmission unit, the output end of the data transmission unit is provided with an AI analysis unit, the output end of the AI analysis unit is provided with a professional review unit, the output end of the professional review unit is provided with a broadcast push unit, and the output end of the broadcast push unit is provided with an alarm notification unit.
[0006] Furthermore, the data acquisition unit includes a sensor module, a data acquisition module, a communication module, a data storage module, a data preprocessing module and a control module.
[0007] Furthermore, the data transmission unit includes a data encoding module, a data decoding module, a data transmission control module, a data buffer module and a data stream module.
[0008] Furthermore, the AI analysis unit includes a feature engineering module, a pattern recognition module, a pattern classification module, a data fusion module and a data integration module.
[0009] Furthermore, the professional audit unit includes an audit standard module, a rule definition module, an audit process management module, an audit execution module and an exception handling module.
[0010] Furthermore, the broadcast push unit includes a content management module, a user management module, a message delivery module, a push plan module and a scheduling module.
[0011] Furthermore, the alarm notification unit includes a data receiver module, an alarm determiner module, an alarm generator module, a communication interface module and a configuration interface module.
[0012] The present invention has the following beneficial effects:
[0013] 1. The present invention includes a sensor module, a data acquisition module, a communication module, a data storage module, a data preprocessing module and a control module through a data acquisition unit, so that the operator uses the sensor module to monitor and detect the physical or chemical quantity of the target environment or object in real time. It collects data through various sensors. These sensors convert analog signals into electrical signals for further processing.
[0014] 2. The present invention includes a data encoding module, a data decoding module, a data transmission control module, a data buffer module and a data stream module through a data transmission unit, so that the operator uses the data encoding module to convert the original data into a format suitable for transmission. It converts the data into a compressed form or a specific data format through an encoding algorithm to reduce possible errors in the transmission process or improve transmission efficiency. The encoding process may also include data encryption to ensure the security of the data.
[0015] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS
[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.
[0017] Figure 1 It is a flowchart of the present invention.
[0018] In the accompanying drawings, the components represented by the reference numerals are listed as follows:
[0019] 1. Data collection unit; 2. Data transmission unit; 3. AI analysis unit; 4. Professional review unit; 5. Broadcast push unit; 6. Alarm notification unit. DETAILED DESCRIPTION
[0020] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0021] See also Figure 1 The present invention is a system for monitoring roads and bridges through AI, including a data acquisition unit 1, a data transmission unit 2 is provided at the output end of the data acquisition unit 1, an AI analysis unit 3 is provided at the output end of the data transmission unit 2, a professional review unit 4 is provided at the output end of the AI analysis unit 3, a broadcast push unit 5 is provided at the output end of the professional review unit 4, and an alarm notification unit 6 is provided at the output end of the broadcast push unit 5.
[0022] The data acquisition unit 1 includes a sensor module, a data acquisition module, a communication module, a data storage module, a data preprocessing module and a control module.
[0023] Function of sensor module: The sensor module is responsible for real-time monitoring and detection of physical or chemical quantities of the target environment or object. It collects data through various sensors. These sensors convert analog signals into electrical signals for further processing. Function of data acquisition module: The data acquisition module is responsible for collecting and converting the signals provided by the sensor module. It usually includes an analog-to-digital converter (ADC) and other signal processing circuits. This module converts the analog signals from the sensor into digital signals for subsequent processing and analysis. Function of communication module: The communication module is responsible for transmitting the data processed by the data acquisition module to other systems or devices. It can realize remote transmission of data through various communication interfaces (such as serial communication, wireless communication, Ethernet, Bluetooth, etc.). The communication module ensures that the data can be effectively and safely transmitted to the predetermined target location. Function of data storage module: The data storage module is responsible for saving the collected data to the storage medium for subsequent access and analysis. It can use various storage media (such as flash memory, hard disk, SD card, etc.) and ensure the persistence and integrity of the data. This is particularly important for applications that need to store data for a long time. Function of data preprocessing module: The data preprocessing module performs preliminary processing on the data before data storage. This includes operations such as denoising, filtering, data correction, and standardization to improve data quality and accuracy. Preprocessed data is more suitable for subsequent analysis and decision-making. The role of the control module: The control module is responsible for coordinating and managing the operations of other modules. It can execute control instructions, monitor system status, handle abnormal situations, and control the data acquisition and processing process according to preset logic and algorithms. The control module ensures the normal operation of the system and optimizes the coordination between the modules. Overall, the data acquisition unit 1 can efficiently and accurately complete the data collection, processing, storage and transmission tasks through the collaborative work of these six modules. This system is often used in various fields, such as industrial monitoring, environmental monitoring, smart homes, medical equipment, etc., to achieve automated data acquisition and intelligent decision support.
[0024] The data transmission unit 2 includes a data encoding module, a data decoding module, a data transmission control module, a data buffer module and a data stream module.
[0025] The various modules of the data transmission unit 2 are mainly responsible for the processing and management of data during the transmission process, ensuring that the data can be correctly and efficiently transmitted from the source to the target. The following are the functions of each module: Data encoding module function: The data encoding module is responsible for converting the original data into a format suitable for transmission. It converts the data into a compressed form or a specific data format through an encoding algorithm to reduce possible errors during the transmission process or improve the transmission efficiency. The encoding process may also include data encryption to ensure the security of the data. Data decoding module function: The data decoding module is responsible for converting the encoded data generated by the encoding module back to the original format at the receiving end. It decodes the received data to restore its original content so that the recipient can correctly understand and use the data. Data transmission control module function: The data transmission control module is responsible for managing various aspects of data transmission, including the implementation of the transmission protocol, error detection and correction, data flow control, etc. It ensures that the data is transmitted smoothly in the network and handles possible transmission problems such as data loss or duplication. Data buffer module function: The data buffer module is used to temporarily store data during the data transmission process. It can balance the speed difference between the sender and the receiver to prevent data loss or transmission bottlenecks. The buffer ensures the smooth and efficient flow of data. The role of the data flow module: The data flow module is responsible for controlling the flow direction and speed of data. It coordinates the sending and receiving of data, ensuring that data flows in a predetermined order and rate to avoid data congestion or conflict, and ensures the smoothness of the entire data transmission process. Comprehensive role In summary, the data transmission unit 2 ensures that data is effectively encoded, decoded and managed during the transmission process through the collaboration of these modules, thereby achieving efficient, secure and reliable data transmission.
[0026] The AI analysis unit 3 includes a feature engineering module, a pattern recognition module, a pattern classification module, a data fusion module and a data integration module.
[0027] The various modules in the AI analysis unit 3 work together to extract valuable information from the data and conduct in-depth analysis. The following is a detailed description of the role of each module: Feature Engineering Module Role: The feature engineering module is responsible for extracting and generating features from raw data. These features are key variables used for training and analysis. Feature engineering involves selecting, extracting, transforming, and creating features to better represent the intrinsic properties of the data. These features can be directly calculated from the raw data or constructed through certain algorithms or domain knowledge. Pattern Recognition Module Role: The pattern recognition module is used to identify potential patterns and structures in the data. It applies various algorithms (such as clustering, dimensionality reduction, association rule mining, etc.) to discover commonalities or anomalies in the data. Pattern recognition helps the system understand the complex relationships and patterns in the data and provides a basis for subsequent analysis. Pattern Classification Module Role: The pattern classification module is responsible for classifying the identified patterns into different categories. It uses classification algorithms (such as decision trees, support vector machines, neural networks, etc.) to classify data so that it can be labeled and organized. The classification results can be used for prediction, decision support, and subsequent analysis. Data Fusion Module Role: The data fusion module is responsible for integrating data from different resources or different types. It combines information from multiple data sources to provide a more comprehensive and consistent view. Data fusion improves the overall quality and accuracy of data by integrating the advantages of different data sources, reducing redundancy and contradictions. The role of the data integration module: The data integration module is used to merge data from multiple sources into a unified system or database. It involves the integration, coordination and consistency checking of data to ensure that all data is compatible in format, structure and content. The data integration module enables data from different sources to be processed and analyzed on a unified platform. Comprehensive role In summary, the AI analysis unit 3 extracts useful features from raw data, identifies and classifies patterns in data, and fuses and integrates data from different sources through the collaboration of these modules. This series of processes enables the system to conduct deeper data analysis and intelligent decision support, helping to reveal implicit information and trends in the data.
[0028] The professional audit unit 4 includes an audit standard module, a rule definition module, an audit process management module, an audit execution module and an exception handling module.
[0029] The various modules of Professional Audit Unit 4 are designed to ensure that data, processes or systems comply with the set standards and regulations, and to ensure the accuracy and effectiveness of the audit. Here are the functions of each module: Audit Standards Module Function: The Audit Standards Module defines and manages the standards and requirements for audits. These standards can include regulations, industry standards, company policies, etc., to ensure that the audit process is carried out according to consistent and clear standards. Rule Definition Module Function: The Rule Definition Module sets and maintains the specific rules that need to be followed during the audit process. These rules guide the operations during the audit process, clarify the details and requirements of the audit to ensure the consistency and fairness of the audit. Audit Process Management Module Function: The Audit Process Management Module is responsible for planning and controlling the entire audit process. This includes developing audit plans, assigning tasks, monitoring progress and coordinating all parties to ensure that the audit proceeds smoothly according to the predetermined steps and schedule. Audit Execution Module Function: The Audit Execution Module actually performs the audit tasks. It checks and evaluates the audited object in accordance with the audit standards and rules to verify that it meets the specified requirements. This module usually includes specific operations such as data collection, audit checks and report generation. Exception Handling Module Function: The Exception Handling Module is responsible for identifying and handling abnormal situations that occur during the audit process. This may include problems, deviations or violations found. The exception handling module provides solutions and improvement suggestions to ensure the integrity and effectiveness of the audit process. Overall, the professional audit unit 4 ensures the standardization, systematicness and accuracy of the audit process through the collaborative work of these modules. It ensures the comprehensive implementation and high-quality completion of audit tasks through standard setting, rule definition, process management, actual execution and exception handling.
[0030] The broadcast push unit 5 includes a content management module, a user management module, a message delivery module, a push plan module and a scheduling module.
[0031] The broadcast push unit 5 is responsible for efficiently distributing information and content to users. The following are the specific functions of each module: Content management module: The content management module is responsible for creating, editing, storing and organizing broadcast content. It ensures the quality and suitability of the content, manages different types of information and media, and is ready for broadcast push. User management module: The user management module is responsible for managing and maintaining user information. This includes user registration, information update, grouping and permission setting. This module ensures that the broadcast push can accurately reach the target user group. Message delivery module: The message delivery module is responsible for actually sending the broadcast content to the user. It handles the transmission and distribution of messages to ensure that the information can be delivered to each user in a timely and accurate manner. Push plan module: The push plan module is used to formulate and manage the push plan for the broadcast content. This includes setting the time, frequency and target audience of the push to optimize the dissemination effect of the information and the user's receiving experience. Scheduling module: The scheduling module is responsible for arranging and executing broadcast tasks according to the predetermined push plan. It ensures the timely push of content and coordinates various resources to achieve efficient broadcast operations. Overall, the broadcast push unit 5 ensures the effective management of information content, accurate positioning of users, smooth delivery of messages, and efficient arrangement and scheduling of push activities through the collaboration of these modules, thereby achieving widespread dissemination of information and a good user experience.
[0032] The alarm notification unit 6 includes a data receiver module, an alarm determiner module, an alarm generator module, a communication interface module and a configuration interface module.
[0033] Each module of the alarm notification unit 6 is responsible for generating and delivering alarm information in a timely and accurate manner. The following is the role of each module: Data receiver module role: The data receiver module is responsible for receiving and collecting real-time data from various data sources. It receives sensor data, monitoring information, etc. as the basis for alarm generation. Alarm judge module role: The alarm judge module analyzes the received data to determine whether the conditions for triggering an alarm are met. It identifies abnormal conditions or potential threats based on the set thresholds and rules. Alarm generator module role: The alarm generator module is responsible for creating specific alarm information based on the analysis results of the alarm judge. This includes generating the content, type and urgency of the alarm and preparing it for notification. Communication interface module role: The communication interface module is responsible for delivering the generated alarm information to the relevant notification system or user. It handles the sending method of the alarm, such as SMS, email, in-application notification, etc., to ensure the effective communication of the alarm information. Configuration interface module role: The configuration interface module provides a user interface for setting and adjusting alarm rules, thresholds and notification options. Users can configure the behavior of the alarm system through this interface to meet specific needs and scenarios.
[0034] In summary, the alarm notification unit 6 realizes the reception and analysis of data, the generation and sending of alarms, and the management of system configuration through the collaborative work of these modules, thereby ensuring the timely and accurate transmission of alarm information and effective response.
[0035] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.
[0036] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.
Claims
1. A system for monitoring roads and bridges by AI, comprising a data acquisition unit (1), characterized in that: The data acquisition unit (1) is provided with a data transmission unit (2) at its output end, the data transmission unit (2) is provided with an AI analysis unit (3) at its output end, the AI analysis unit (3) is provided with a professional review unit (4) at its output end, the professional review unit (4) is provided with a broadcast push unit (5) at its output end, and the broadcast push unit (5) is provided with an alarm notification unit (6) at its output end.
2. A system for monitoring roads and bridges through AI according to claim 1, characterized in that: The data acquisition unit (1) comprises a sensor module, a data acquisition module, a communication module, a data storage module, a data preprocessing module and a control module.
3. The system for monitoring roads and bridges by AI according to claim 2, characterized in that: The data transmission unit (2) comprises a data encoding module, a data decoding module, a data transmission control module, a data buffer module and a data stream module.
4. The system for monitoring roads and bridges by AI according to claim 3, characterized in that: The AI analysis unit (3) comprises a feature engineering module, a pattern recognition module, a pattern classification module, a data fusion module and a data integration module.
5. The system for monitoring roads and bridges by AI according to claim 4, characterized in that: The professional audit unit (4) comprises an audit standard module, a rule definition module, an audit process management module, an audit execution module and an exception handling module.
6. The system for monitoring roads and bridges by AI according to claim 5, characterized in that: The broadcast push unit (5) comprises a content management module, a user management module, a message delivery module, a push plan module and a scheduling module.
7. The system for monitoring roads and bridges by AI according to claim 6, characterized in that: The alarm notification unit (6) comprises a data receiver module, an alarm determiner module, an alarm generator module, a communication interface module and a configuration interface module.