Communication engineering construction safety monitoring and optimizing method and system

Abstract

The invention provides a communication engineering construction safety monitoring and optimizing method and system, and relates to the field of communication engineering construction.The method comprises the steps that a plurality of environment monitoring sensors are arranged in a communication engineering construction area; a plurality of equipment monitoring sensors are arranged on the communication engineering construction equipment; personnel activity monitoring sensors are arranged on communication engineering constructors; constructing a risk assessment model; performing data processing on data acquired by the plurality of environment monitoring sensors, data acquired by the plurality of equipment monitoring sensors and data acquired by the personnel activity monitoring sensor, and extracting multi-dimensional risk feature data; inputting the multi-dimensional risk feature data into a risk assessment model to determine communication engineering construction risk assessment information, and judging whether to perform optimization or not according to the communication engineering construction risk assessment information; the method has the advantages that real-time monitoring, safety evaluation and optimization decision making of the communication engineering construction site are achieved, so that the construction efficiency and the safety level are improved, and the accident rate is reduced.

Description

Technical Field

[0001] The present invention relates to the field of communication engineering construction, and in particular to a communication engineering construction safety monitoring and optimization method and system. Background Art

[0002] Safety management of communication engineering construction sites has always been a key and difficult point in the industry. Traditional safety management methods mainly rely on manual inspections and experience judgments, and there are the following problems: 1. Poor real-time performance: Manual inspections cannot achieve 24-hour uninterrupted monitoring, and it is difficult to detect potential safety hazards in a timely manner. For example, during night construction, the frequency and coverage of manual inspections are often insufficient, resulting in some hidden safety issues that cannot be discovered in a timely manner. 2. Inaccurate data: Manually recorded data is prone to errors and it is difficult to fully cover every corner of the construction site. For example, the measurement of environmental parameters (such as gas concentration, temperature and humidity, etc.) often relies on handheld devices, and the accuracy and consistency of data collection are difficult to guarantee. 3. Inefficiency: Manual analysis and processing of data are inefficient and cannot respond quickly to emergencies. For example, when an emergency occurs at a construction site, the manual processing process is cumbersome, delaying the best time to handle it. 4. Unreasonable resource allocation: Lack of scientific data support, construction plans and resource allocation are often not optimized, resulting in low construction efficiency. For example, the use and maintenance plans of equipment lack data support, and equipment is often idle or overused.

[0003] In recent years, with the rapid development of the Internet of Things and artificial intelligence technologies, more and more studies have begun to try to apply these advanced technologies to the safety management of construction sites. However, most of the existing systems are single-function, either focusing only on environmental monitoring or only on equipment status, lacking comprehensive solutions. For example, some systems can only monitor environmental parameters and cannot fully monitor equipment status and personnel activities. In addition, the existing systems also have deficiencies in data analysis and optimization decision-making, making it difficult to achieve truly intelligent management. For example, the data analysis algorithm is not smart enough to accurately identify complex safety hazards, resulting in inaccurate safety assessment results.

[0004] Therefore, it is necessary to provide a communication engineering construction safety monitoring and optimization method and system to achieve real-time monitoring, safety assessment and optimization decision-making of the communication engineering construction site, thereby improving construction efficiency and safety level and reducing the accident rate. Summary of the invention

[0005] The present invention provides a communication engineering construction safety monitoring and optimization method, comprising: setting a plurality of environmental monitoring sensors in a communication engineering construction area; setting a plurality of equipment monitoring sensors on communication engineering construction equipment; setting a personnel activity monitoring sensor on communication engineering construction personnel; constructing a risk assessment model; performing data processing on data collected by the plurality of environmental monitoring sensors, data collected by the plurality of equipment monitoring sensors and data collected by the personnel activity monitoring sensors to extract multi-dimensional risk feature data; inputting the multi-dimensional risk feature data into the risk assessment model to determine communication engineering construction risk assessment information; judging whether to perform optimization according to the communication engineering construction risk assessment information; and generating an optimal resource allocation plan if it is determined to perform optimization.

[0006] Furthermore, multiple environmental monitoring sensors are set up in the communication engineering construction area, including: determining multiple environmental temperature and humidity monitoring positions in the communication engineering construction area; setting temperature and humidity sensors at the multiple environmental temperature and humidity monitoring positions; determining multiple gas concentration monitoring positions in the communication engineering construction area; and setting multiple gas concentration sensors at the multiple gas concentration monitoring positions.

[0007] Furthermore, multiple equipment monitoring sensors are set on the communication engineering construction equipment, including: determining multiple vibration monitoring positions of the communication engineering construction equipment; setting vibration sensors at the multiple vibration monitoring positions; determining multiple current monitoring positions of the power supply line of the communication engineering construction equipment; and setting current sensors at the multiple current monitoring positions.

[0008] Furthermore, personnel activity monitoring sensors are set on the communication engineering construction workers, including: setting up multiple positioning base stations in the communication engineering construction area; setting up wearable positioning devices on the communication engineering construction workers, wherein the wearable positioning device and the multiple positioning base stations are used to determine the positions of the communication engineering construction workers; and setting motion status sensors in the safety helmets or work clothes of the communication engineering construction workers.

[0009] Furthermore, data processing is performed on the data collected by the multiple environmental monitoring sensors, the data collected by the multiple equipment monitoring sensors, and the data collected by the personnel activity monitoring sensors to extract multidimensional risk feature data, including: denoising the data collected by the multiple environmental monitoring sensors, the data collected by the multiple equipment monitoring sensors, and the data collected by the personnel activity monitoring sensors to generate denoised data, normalizing the denoised data to generate normalized data; and extracting multidimensional risk feature data from the normalized data.

[0010] Furthermore, multi-dimensional risk feature data is extracted from the data after the denoising and normalization processing, including: extracting the changing trends and abnormal points of the ambient temperature and humidity; extracting the changing trends and abnormal points of the gas concentration; extracting the characteristic values ​​of the vibration frequency of the communication engineering construction equipment; extracting the characteristic values ​​of the current fluctuations of the power supply lines of the communication engineering construction equipment; extracting the spatiotemporal characteristics of the personnel positions and motion states.

[0011] Furthermore, the generating of the optimal resource allocation plan includes: constructing a resource allocation model; generating the optimal resource allocation plan based on the data collected by the multiple environmental monitoring sensors, the data collected by the multiple equipment monitoring sensors, and the data collected by the personnel activity monitoring sensors through the resource allocation model.

[0012] Furthermore, a communication engineering construction safety monitoring and optimization method also includes: visualizing the data collected by the multiple environmental monitoring sensors, the data collected by the multiple equipment monitoring sensors, and the data collected by the personnel activity monitoring sensors; generating an early warning notification based on the communication engineering construction risk assessment information, and sending the early warning notification to the management personnel terminal.

[0013] The present invention provides a communication engineering construction safety monitoring and optimization system, which applies the above-mentioned communication engineering construction safety monitoring and optimization method, including: a data acquisition module, including multiple environmental monitoring sensors, multiple equipment monitoring sensors and personnel activity monitoring sensors; multiple environmental monitoring sensors and multiple equipment monitoring sensors are all located in the communication engineering construction area, and the personnel activity monitoring sensor is set on the communication engineering construction personnel; a cloud server is used to receive the data collected by the multiple environmental monitoring sensors, the data collected by the multiple equipment monitoring sensors and the data collected by the personnel activity monitoring sensors uploaded by the data acquisition module through a wireless communication network, and the cloud server includes a model building unit, a data processing unit and a risk assessment unit, wherein the model building unit is used to build a risk assessment model, the data processing unit is used to process the data collected by the multiple environmental monitoring sensors, the data collected by the multiple equipment monitoring sensors and the data collected by the personnel activity monitoring sensors, and extract multi-dimensional risk feature data, and the risk assessment unit is used to input the multi-dimensional risk feature data into the risk assessment model to determine the communication engineering construction risk assessment information, and judge whether to optimize according to the communication engineering construction risk assessment information; if it is determined to optimize, generate an optimal resource allocation plan.

[0014] Furthermore, the data acquisition module is also used to: encrypt the data collected by the multiple environmental monitoring sensors, the data collected by the multiple equipment monitoring sensors, and the data collected by the personnel activity monitoring sensors, and upload them to the cloud server via the wireless communication network.

[0015] Compared with the prior art, the communication engineering construction safety monitoring and optimization method and system provided by the present invention have at least the following beneficial effects:

[0016] By deploying a variety of IoT sensors, we can achieve 24-hour uninterrupted real-time monitoring of the construction site, and promptly discover and deal with potential safety hazards. We use high-precision sensors and automated data collection technology to ensure the accuracy and comprehensiveness of data and avoid errors in manual recording. We use artificial intelligence algorithms to efficiently analyze massive amounts of data, quickly identify potential risks, and improve response speed. Based on the results of data analysis, we can scientifically formulate construction plans and resource allocation plans to improve construction efficiency and resource utilization. Through the visualization platform, we can achieve remote monitoring and early warning of the construction site and improve emergency response capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] This specification will be further described in the form of exemplary embodiments, which will be described in detail by the accompanying drawings. These embodiments are not restrictive, and in these embodiments, the same number represents the same structure, wherein:

[0018] Figure 1 It is a flow chart of a communication engineering construction safety monitoring and optimization method according to some embodiments of this specification;

[0019] Figure 2 It is a module diagram of a communication engineering construction safety monitoring and optimization system according to some embodiments of this specification.

[0020] Description of reference numerals:

[0021] 210. Data collection module; 220. Cloud server. DETAILED DESCRIPTION

[0022] In order to more clearly illustrate the technical solutions of the embodiments of this specification, the following is a brief introduction to the drawings required for the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of this specification. For ordinary technicians in this field, this specification can also be applied to other similar scenarios based on these drawings without creative work. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0023] Figure 1 is a flow chart of a communication engineering construction safety monitoring and optimization method according to some embodiments of this specification, such as Figure 1 As shown, a communication engineering construction safety monitoring and optimization method may include the following steps.

[0024] Step 110, set up multiple environmental monitoring sensors in the communication engineering construction area.

[0025] Specifically include:

[0026] Determine multiple environmental temperature and humidity monitoring locations in the communication project construction area;

[0027] Set up temperature and humidity sensors at multiple environmental temperature and humidity monitoring locations;

[0028] Identify multiple gas concentration monitoring locations in the communication project construction area;

[0029] Various gas concentration sensors are set at multiple gas concentration monitoring locations.

[0030] For example, the environmental temperature and humidity monitoring position can be installed at each key node in the construction area of ​​the communication project to monitor the environmental temperature and humidity in real time to ensure that the construction environment meets safety standards. Gas concentration sensors can be deployed in areas where harmful gas leaks may occur in the construction area of ​​the communication project, such as cable laying points and equipment installation points, to monitor the concentration of oxygen, carbon dioxide, and harmful gases (such as methane, hydrogen sulfide, etc.) in real time. As an example only, the temperature and humidity sensor collects data every 5 minutes, and the gas concentration sensor collects data every 10 minutes.

[0031] Multiple ambient temperature and humidity monitoring locations and multiple gas concentration monitoring locations can be determined according to the following process:

[0032] S11. Relevant information (e.g., construction plan, construction environment, etc.) and monitoring location data of multiple historical communication engineering construction areas may be obtained, wherein the monitoring location data may include environmental temperature and humidity monitoring locations and gas concentration monitoring locations of the historical communication engineering construction areas;

[0033] S12, obtaining relevant information of the current communication engineering construction area (for example, construction plan, construction environment, etc.);

[0034] S13, according to the relevant information of the current communication engineering construction area (for example, construction plan, construction environment, etc.), determine a similar historical communication engineering construction area from multiple historical communication engineering construction areas;

[0035] S14. Predict multiple environmental temperature and humidity monitoring locations and multiple gas concentration monitoring locations in the current communication engineering construction area based on monitoring location data of similar historical communication engineering construction areas through a first position prediction model, wherein the first position prediction model may be a convolutional neural network model.

[0036] Step 120, setting a plurality of equipment monitoring sensors on the communication engineering construction equipment.

[0037] Specifically include:

[0038] Identify multiple vibration monitoring locations for communications engineering construction equipment;

[0039] Setting vibration sensors at multiple vibration monitoring locations;

[0040] Determine multiple current monitoring locations for power supply lines of communication engineering construction equipment;

[0041] Current sensors are arranged at multiple current monitoring locations.

[0042] For example, vibration sensors can be installed on heavy machinery to monitor the vibration frequency and amplitude of the equipment, evaluate the equipment's operating status, and prevent mechanical failures. Current sensors can be attached to the main power supply lines of electrical equipment to monitor the current size and fluctuations in real time to prevent electrical accidents such as overload and short circuit. As an example only, vibration sensors and current sensors collect data in real time and update once per second.

[0043] Multiple vibration monitoring positions and multiple current monitoring positions can be determined according to the following process:

[0044] S21, obtaining structural information, vibration monitoring positions, and current monitoring positions of multiple sample communication engineering construction equipment;

[0045] S22, obtaining structural information of current communication engineering construction equipment;

[0046] S23, determining similar sample communication engineering construction equipment from a plurality of sample communication engineering construction equipment according to the structure information of the current communication engineering construction equipment;

[0047] S24. Predict multiple vibration monitoring positions and multiple current monitoring positions of the current communication engineering construction area based on the vibration monitoring positions and current monitoring positions of similar sample communication engineering construction equipment through a second position prediction model, wherein the second position prediction model may be a convolutional neural network model.

[0048] Step 130, setting a personnel activity monitoring sensor on the communication engineering construction personnel.

[0049] Specifically include:

[0050] Set up multiple positioning base stations in the communication engineering construction area;

[0051] A wearable positioning device is provided on the communication engineering construction personnel, wherein the wearable positioning device and a plurality of positioning base stations are used to determine the position of the communication engineering construction personnel;

[0052] A motion state sensor is provided in the safety helmet or work clothes of the communication engineering construction workers.

[0053] For example, through wearable positioning devices and multiple positioning base stations set up in the communication engineering construction area, the specific location of construction workers can be tracked in real time to ensure their safety. The motion state sensor can be integrated into the safety helmet or work clothes of the communication engineering construction workers to monitor the motion state of the communication engineering construction workers (such as walking, stillness, falling, etc.) and detect abnormal situations in time. As an example only, the wearable positioning device and the motion state sensor update the data once a minute.

[0054] Step 140: construct a risk assessment model.

[0055] Specifically, a risk assessment model can be constructed by using machine learning algorithms (such as support vector machine (SVM), random forest (RF), convolutional neural network (CNN) or recurrent neural network (RNN), etc.).

[0056] Step 150 , processing the data collected by multiple environmental monitoring sensors, the data collected by multiple equipment monitoring sensors, and the data collected by personnel activity monitoring sensors to extract multi-dimensional risk feature data.

[0057] Specifically include:

[0058] De-noising the data collected by multiple environmental monitoring sensors, the data collected by multiple equipment monitoring sensors, and the data collected by personnel activity monitoring sensors to generate de-noised data, and normalizing the de-noised data to generate normalized data;

[0059] Extract multidimensional risk characteristic data from the normalized data.

[0060] Specifically, methods such as wavelet transform or Kalman filtering are used to remove noise interference in the data collected by multiple environmental monitoring sensors, multiple equipment monitoring sensors, and personnel activity monitoring sensors to ensure the purity of the data. For example, the temperature and humidity sensor data are de-noised by wavelet transform, and the gas concentration data is smoothed by Kalman filtering. The data of different dimensions collected by multiple environmental monitoring sensors, multiple equipment monitoring sensors, and personnel activity monitoring sensors are normalized, and all data are normalized to the [0,1] interval to unify the data scale for subsequent analysis.

[0061] As an example, multi-dimensional risk feature data is extracted from the denoised and normalized data, including:

[0062] Extract the changing trends and abnormal points of ambient temperature and humidity, such as sudden changes in temperature and humidity values;

[0063] Extract the changing trend and abnormal points of gas concentration, such as gas concentration exceeding the standard;

[0064] Extract characteristic values ​​of vibration frequency of communication engineering construction equipment, such as abnormal vibration frequency;

[0065] Extract characteristic values ​​of current fluctuations in the power supply lines of communication engineering construction equipment, such as abnormal current peaks;

[0066] Extract spatiotemporal features of people’s locations and motion states, such as abnormal stillness or falls.

[0067] Step 160, input the multi-dimensional risk characteristic data into the risk assessment model to determine the communication engineering construction risk assessment information.

[0068] Among them, the communication engineering construction risk assessment information may be the communication engineering construction risk probability.

[0069] For example, if the temperature and humidity sensor data is abnormal at a certain moment, the risk assessment model will judge it as a high risk and issue an early warning immediately.

[0070] The risk assessment model can adopt an online learning mechanism to update the risk assessment model parameters in real time to adapt to the dynamic changes of the construction site. Regular cross-validation should be carried out to evaluate the performance of the risk assessment model, optimize the risk assessment model structure, and improve the accuracy of the assessment.

[0071] Step 170, determining whether to perform optimization based on the communication engineering construction risk assessment information.

[0072] Specifically, an optimization determination model may be used to determine whether to perform optimization based on the communication engineering construction risk assessment information, wherein the optimization determination model may be a convolutional neural network (CNN) model.

[0073] Step 180: If it is determined to be optimized, an optimal resource allocation plan is generated.

[0074] Specifically include:

[0075] Build resource allocation models;

[0076] The resource allocation model generates the optimal resource allocation plan based on the data collected by multiple environmental monitoring sensors, the data collected by multiple equipment monitoring sensors, and the data collected by personnel activity monitoring sensors.

[0077] Specifically, according to the complexity of the communication engineering construction site and the diversity of resource allocation, a suitable intelligent optimization algorithm is selected to build a resource allocation model. For example, the Multi-Objective Particle Swarm Optimization Algorithm (MOPSO) is used, which has good global search capabilities and convergence speed when dealing with multi-objective optimization problems. According to the characteristics of communication engineering construction, the MOPSO algorithm is appropriately adjusted, such as adding constraints (such as safety regulations, construction period requirements, etc.) and optimizing particle update strategies.

[0078] Integrate data such as environmental parameters, equipment status, and personnel activities to form a comprehensive construction site data set. Through data analysis, identify the resource requirements of the construction site, including manpower, equipment, materials, etc. Build a resource allocation model for multi-objective optimization, with the main objectives including minimizing construction costs, maximizing construction efficiency, minimizing safety risks, etc. Set constraints for resource allocation, such as the upper limit of the number of personnel, equipment usage time limit, material supply, etc. For example, the number of personnel does not exceed 20, the equipment usage time does not exceed 8 hours, and the material supply meets the construction needs. Input the integrated data, run the adjusted resource allocation model, and perform multi-objective optimization. The resource allocation model outputs the results and generates the optimal resource allocation plan, including personnel arrangement, equipment scheduling, material allocation, etc. For example, arrange 15 workers, 3 equipment, and 500 kg of materials. Evaluate the generated resource allocation plan to check whether all constraints are met and evaluate its feasibility and optimization effect. Based on the evaluation results, fine-tune the plan to ensure its feasibility and optimality in actual construction. For example, add 1 worker to meet the construction period requirements.

[0079] The objective function of the resource allocation model is:

[0080] f(x)=min(C(x),-E(x),R(x))

[0081] Among them, f(x) is the objective function of the resource allocation model, min() is the minimum value, C(x) is the construction cost, E(x) is the construction efficiency, and R(x) is the safety risk.

[0082] The constraints of the resource allocation model include:

[0083]

[0084] Among them, P(x) is the number of people, P max is the upper limit of the number of personnel, T(x) is the equipment usage time, T max is the equipment usage time, M(x) is the material usage, M supply The amount of material supplied.

[0085] By generating the optimal resource allocation plan, we can make scientific and efficient optimization decisions and resource allocation, significantly improve construction efficiency and safety levels, reduce resource waste, and ensure the smooth progress of construction projects.

[0086] In some embodiments, a communication engineering construction safety monitoring and optimization method may further include:

[0087] Visualize data collected by multiple environmental monitoring sensors, data collected by multiple equipment monitoring sensors, and data collected by personnel activity monitoring sensors;

[0088] Based on the risk assessment information of the communication engineering construction, an early warning notification is generated and sent to the management terminal. Specifically, based on the risk assessment information of the communication engineering construction, a safety report is automatically generated, including risk level, hidden danger type, recommended measures, etc., and supports visual display.

[0089] Figure 2 is a module diagram of a communication engineering construction safety monitoring and optimization system according to some embodiments of this specification, such as Figure 2 As shown, a communication engineering construction safety monitoring and optimization system may include a data acquisition module 210 and a cloud server 220.

[0090] The data acquisition module 210 may include multiple environmental monitoring sensors, multiple equipment monitoring sensors and personnel activity monitoring sensors; the multiple environmental monitoring sensors and multiple equipment monitoring sensors are all located in the communication engineering construction area, and the personnel activity monitoring sensors are set on the communication engineering construction personnel.

[0091] The cloud server 220 can be used to receive data collected by multiple environmental monitoring sensors, multiple equipment monitoring sensors and personnel activity monitoring sensors uploaded by the data acquisition module through the wireless communication network. The cloud server 220 includes a model building unit, a data processing unit and a risk assessment unit, wherein the model building unit is used to build a risk assessment model, the data processing unit is used to process the data collected by multiple environmental monitoring sensors, multiple equipment monitoring sensors and personnel activity monitoring sensors, and extract multi-dimensional risk feature data, and the risk assessment unit is used to determine the communication engineering construction risk assessment information according to the multi-dimensional risk feature data through the risk assessment model.

[0092] Specifically, the data acquisition module 210 is also used to: encrypt the data collected by multiple environmental monitoring sensors, the data collected by multiple equipment monitoring sensors, and the data collected by personnel activity monitoring sensors, and upload them to the cloud server 220 through a wireless communication network (such as Wi-Fi, LoRa, NB-IoT, etc.) to ensure the security of the data. Wi-Fi is suitable for scenarios with large data volumes and short transmission distances, while LoRa and NB-IoT are suitable for long-distance, low-power data transmission. In order to ensure the security of data during transmission, the data acquisition module 210 can use a symmetric encryption algorithm (such as AES) or an asymmetric encryption algorithm (such as RSA) to encrypt the data. The symmetric encryption algorithm has a fast encryption speed and is suitable for data with high real-time requirements; the asymmetric encryption algorithm has higher security and is suitable for the transmission of critical data.

[0093] The cloud server 220 efficiently stores and manages data, using a distributed database system to ensure data integrity and traceability.

[0094] The cloud server 220 can use a distributed cloud computing platform, such as AWS, Azure or Alibaba Cloud, to ensure the high availability and scalability of the server. The distributed architecture can effectively avoid single point failures and improve the stability and reliability of the system. The cloud server can use a distributed database system (such as Cassandra, MongoDB, etc.) for data storage. These database systems support high concurrent reading and writing and automatic data sharding, and can efficiently manage massive data. The cloud server 220 can regularly back up data and adopt a multi-level backup strategy, including local backup and off-site backup, to ensure the recoverability of data in unexpected situations. The backup frequency is determined according to the importance and update frequency of the data, and important data can be backed up once an hour. During the data storage process, the cloud server 220 uses a checksum (such as CRC) or digital signature technology to check the integrity of the data to ensure that the data has not been tampered with during transmission and storage. The cloud server 220 can implement a strict access control policy based on role-based permission management to ensure that only authorized users can access sensitive data. At the same time, all data access and operation logs are recorded for post-audit and tracking.

[0095] Through the above technologies, a communication engineering construction safety monitoring and optimization system can efficiently and safely complete data transmission and storage, ensure the integrity and security of the data, and provide a solid data foundation for subsequent data analysis and optimization decisions.

[0096] A communication engineering construction safety monitoring and optimization system uses Web front-end technologies (such as HTML5, CSS3, and JavaScript) to build a user interface to ensure that the platform has good interactivity and cross-platform compatibility. Using back-end technologies such as Node.js or Python, the data processing and business logic layer is built to be responsible for receiving, processing, and forwarding real-time data.

[0097] A communication engineering construction safety monitoring and optimization system uses WebSocket or HTTP long polling technology to achieve real-time data interaction between the front-end interface and the back-end service, ensuring that managers can see the latest on-site data. Using data visualization libraries such as D3.js or ECharts, real-time data is converted into charts, such as line charts, bar charts, pie charts, etc., so that managers can quickly understand the trend of data changes. Time series analysis, machine learning and other methods are used to detect anomalies in real-time data and identify potential safety risks. Once an abnormal situation is detected, the system immediately sends an early warning notification to the manager through SMS, email or platform push to ensure timely response. The system adopts an advanced remote monitoring and early warning mechanism to achieve real-time monitoring of the construction site and timely response to potential safety hazards. The mechanism provides managers with an intuitive and real-time monitoring interface through an integrated visualization platform, ensuring that abnormal situations can be quickly identified and corresponding emergency measures can be taken.

[0098] A communication engineering construction safety monitoring and optimization system can adopt responsive web design to ensure that the platform can be well displayed on mobile devices of different sizes. For iOS and Android platforms, native mobile applications are developed to provide a more convenient mobile access experience. For the desktop, the chart rendering performance is optimized to ensure smooth display on large screens. Support multi-window operation to facilitate managers to monitor multiple construction sites at the same time. Integrate real-time voice call function to facilitate managers to communicate directly with on-site personnel and issue instructions quickly. Through the high-definition cameras deployed on site, real-time transmission of video streams is realized to provide a more intuitive on-site monitoring screen. Regularly generate data analysis reports, including construction progress, safety risks, resource usage, etc., to provide data support for managers' decision-making. Integrate expert systems to provide decision-making suggestions based on historical data and expert knowledge to assist managers in making scientific decisions.

[0099] A communication engineering construction safety monitoring and optimization system can be used to execute a communication engineering construction safety monitoring and optimization method. For more descriptions of a communication engineering construction safety monitoring and optimization system, please refer to more descriptions of a communication engineering construction safety monitoring and optimization method, which will not be repeated here.

[0100] A communication engineering construction safety monitoring and optimization system, by integrating IoT sensors and artificial intelligence algorithms, realizes real-time monitoring, safety assessment and optimization decision-making of the construction site, effectively solves many problems in existing technologies, significantly improves construction efficiency and safety level, and has broad application prospects and promotion value. The system not only improves the safety management level of the construction site, but also provides new ideas and methods for intelligent management in the industry, with important technical innovation and social benefits.

[0101] Finally, it should be understood that the embodiments described in this specification are only used to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, as an example and not a limitation, alternative configurations of the embodiments of this specification may be considered consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly introduced and described in this specification.

Claims

1. A communication engineering construction safety monitoring and optimization method, characterized in that: include: Set up multiple environmental monitoring sensors in the communication engineering construction area; Install multiple equipment monitoring sensors on the communication engineering construction equipment; Setting up personnel activity monitoring sensors on construction personnel of communication projects; Construct risk assessment models; Processing the data collected by the multiple environmental monitoring sensors, the data collected by the multiple equipment monitoring sensors, and the data collected by the personnel activity monitoring sensors to extract multi-dimensional risk feature data; Inputting the multi-dimensional risk characteristic data into the risk assessment model for evaluation to determine communication engineering construction risk assessment information; Determining whether to perform optimization based on the communication engineering construction risk assessment information; If it is determined to be optimized, an optimal resource allocation plan is generated.

2. A communication engineering construction safety monitoring and optimization method according to claim 1, characterized in that: Multiple environmental monitoring sensors are installed in the communication engineering construction area, including: Determine a plurality of environmental temperature and humidity monitoring locations in the communication engineering construction area; Setting temperature and humidity sensors at the plurality of environmental temperature and humidity monitoring locations; Determine a plurality of gas concentration monitoring locations in the communication engineering construction area; A plurality of gas concentration sensors are arranged at the plurality of gas concentration monitoring positions.

3. A communication engineering construction safety monitoring and optimization method according to claim 1, characterized in that: Multiple equipment monitoring sensors are installed on the communication engineering construction equipment, including: Determining a plurality of vibration monitoring locations of the communication engineering construction equipment; Setting vibration sensors at the plurality of vibration monitoring locations; Determining a plurality of current monitoring locations of a power supply line of the communication engineering construction equipment; Current sensors are arranged at the plurality of current monitoring positions.

4. A communication engineering construction safety monitoring and optimization method according to claim 1, characterized in that: Set up personnel activity monitoring sensors on communication engineering construction personnel, including: Setting up a plurality of positioning base stations in the communication engineering construction area; A wearable positioning device is provided on the communication engineering construction worker, wherein the wearable positioning device and the plurality of positioning base stations are used to determine the position of the communication engineering construction worker; A motion state sensor is arranged in the safety helmet or work clothes of the communication engineering construction workers.

5. A communication engineering construction safety monitoring and optimization method according to any one of claims 1 to 4, characterized in that: Processing the data collected by the multiple environmental monitoring sensors, the data collected by the multiple equipment monitoring sensors, and the data collected by the personnel activity monitoring sensors to extract multi-dimensional risk feature data, including: Performing denoising processing on the data collected by the multiple environment monitoring sensors, the data collected by the multiple equipment monitoring sensors, and the data collected by the personnel activity monitoring sensors to generate denoised data, and performing normalization processing on the denoised data to generate normalized data; Multidimensional risk feature data is extracted from the normalized data.

6. A communication engineering construction safety monitoring and optimization method according to claim 5, characterized in that: Extracting multidimensional risk feature data from the denoising and normalization processed data includes: Extract the changing trends and abnormal points of ambient temperature and humidity; Extract the changing trend and abnormal points of gas concentration; Extract the characteristic values ​​of vibration frequency of communication engineering construction equipment; Extract the characteristic value of current fluctuation of the power supply line of the communication engineering construction equipment; Extract the spatiotemporal features of personnel positions and motion states.

7. A communication engineering construction safety monitoring and optimization method according to any one of claims 1 to 4, characterized in that: The generating of the optimal resource allocation scheme comprises: Build resource allocation models; The resource allocation model generates an optimal resource allocation plan based on the data collected by the multiple environment monitoring sensors, the multiple equipment monitoring sensors and the personnel activity monitoring sensors.

8. A communication engineering construction safety monitoring and optimization method according to any one of claims 1 to 4, characterized in that: Also includes: Visualizing the data collected by the multiple environment monitoring sensors, the data collected by the multiple equipment monitoring sensors, and the data collected by the personnel activity monitoring sensors; Based on the communication engineering construction risk assessment information, a warning notification is generated and sent to a management personnel terminal.

9. A communication engineering construction safety monitoring and optimization system, characterized in that: A communication engineering construction safety monitoring and optimization method according to any one of claims 1 to 8 is applied, comprising: The data acquisition module includes a plurality of environment monitoring sensors, a plurality of equipment monitoring sensors and a personnel activity monitoring sensor; the plurality of environment monitoring sensors and the plurality of equipment monitoring sensors are all located in the communication engineering construction area, and the personnel activity monitoring sensor is arranged on the communication engineering construction personnel; A cloud server is used to receive the data collected by the multiple environmental monitoring sensors, the data collected by the multiple equipment monitoring sensors, and the data collected by the personnel activity monitoring sensors uploaded by the data acquisition module through the wireless communication network. The cloud server includes a model building unit, a data processing unit, and a risk assessment unit, wherein the model building unit is used to build a risk assessment model, the data processing unit is used to process the data collected by the multiple environmental monitoring sensors, the data collected by the multiple equipment monitoring sensors, and the data collected by the personnel activity monitoring sensors to extract multi-dimensional risk feature data, and the risk assessment unit is used to input the multi-dimensional risk feature data into the risk assessment model to determine the communication engineering construction risk assessment information, and determine whether to optimize according to the communication engineering construction risk assessment information; if it is determined to be optimized, generate an optimal resource allocation plan.

10. A communication engineering construction safety monitoring and optimization system according to claim 9, characterized in that: The data acquisition module is also used for: After encrypting the data collected by the multiple environmental monitoring sensors, the data collected by the multiple equipment monitoring sensors, and the data collected by the personnel activity monitoring sensors, the data are uploaded to the cloud server via the wireless communication network.

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