Monitoring method and system based on Internet of Things

Abstract

The invention discloses a monitoring method and system based on the Internet of Things, and relates to the technical field of application of the computer technology in safety production, and the method comprises the steps: carrying out the partitioning of a construction site region according to different construction types, and obtaining the preliminary regions of a construction site; calculating risk change indexes of all areas in real time according to the equipment use state score, the personnel comprehensive score and the environment score; and setting risk change index thresholds Tric1 and Tric2, extracting areas of which the risk change indexes are greater than or equal to Tric1 and less than or equal to Tric2, sending the areas into a safety area database, extracting other areas and corresponding operating personnel, sending the other areas and the corresponding operating personnel into a personnel exchange matching strategy, and readjusting the personnel operating area. The problem that when the construction operation risk changes, the operation risk is increased due to excessive personnel resource allocation is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of application of computer technology in safe production, and in particular to a monitoring method and system based on the Internet of Things. Background Art

[0002] With the acceleration of urbanization, the number of construction projects is increasing, and the safety management of construction sites is becoming more and more important. The construction site environment is complex and there are many potential risk factors, such as equipment failure, personnel operation errors and bad weather, which often lead to frequent safety accidents. This not only threatens the life safety of the operators, but also has a serious impact on the progress and quality of the project. Therefore, it is particularly necessary to build an efficient and intelligent construction safety monitoring system.

[0003] In this context, monitoring methods based on the Internet of Things technology have emerged. Through real-time data collection and analysis, dynamic monitoring of the construction site can be achieved, high-risk areas can be identified in a timely manner, and corresponding measures can be taken to reduce the probability of accidents. At the same time, intelligent personnel exchange and matching strategies can ensure that operators work in a safe environment, effectively improving construction efficiency and safety.

[0004] For example, the existing Chinese patent with publication number CN112671824A discloses a construction site supervision method based on intelligent multi-dimensional perception and distributed storage, including the following steps: first, blockchain accounting nodes are deployed on the supervision end, each construction site management end, and each construction site site end; one construction site management end corresponds to one or more construction site sites; then, each construction site site end collects and processes the personnel identification information, environmental pollution information, and production safety information of the corresponding site, and transmits the processing result data to each blockchain accounting node; then, the supervision end and the construction site management end supervise and make decisions based on the data on the blockchain accounting node. The present invention uses the Internet of Things and blockchain technology to achieve the effect of improving the intelligence and transparency of construction site management, and solves the problem of difficulty in construction site management.

[0005] However, this design system has a complex structure, and the integration of the Internet of Things and blockchain technology requires a high level of technical skills, which increases the difficulty of training and maintenance. Moreover, due to its reliance on a fixed blockchain structure and preset node configurations, the system may be difficult to quickly adjust to cope with changes in the construction site environment or demand, resulting in poor adaptability, limiting the versatility of the system and making it impossible to flexibly deploy operators. To this end, the present invention provides a monitoring method and system based on the Internet of Things. Summary of the invention

[0006] The purpose of the present invention is to provide a monitoring method and system based on the Internet of Things to solve the existing problems raised in the above background technology.

[0007] To achieve the above object, the present invention provides the following technical solution: a monitoring method based on the Internet of Things, comprising the following steps: S1. Divide the construction site area into different zones according to different construction types to obtain preliminary zones of the construction site; S2. Calculate the risk change indicators of all areas in real time based on the equipment usage status score, personnel comprehensive score, and environmental score; S3, setting the risk change index thresholds Tric1 and Tric2, extracting the areas where the risk change index is greater than or equal to Tric1 and less than or equal to Tric2, and sending them to the safe area database, and extracting the remaining areas and their corresponding operators and sending them to step S4; S4. Set up personnel exchange and matching strategies and readjust personnel work areas.

[0008] A further improvement of the present invention is that the personnel exchange matching strategy specifically comprises the following steps: S41, randomly generate a set of initial solutions, each solution including a personnel exchange plan in a high-risk candidate pool and a low-risk candidate pool; S42, creating an exchange matching value function as a fitness function; and setting a matching threshold, selecting a replacement scheme with an exchange matching value greater than the matching threshold as a parent generation replacement scheme, and generating a new position for each selected replacement scheme through a scheme mutation probability to form a new child generation personnel replacement scheme; S43, calculating the exchange matching value of the new position, and calculating the absolute value of the difference between the exchange matching value of the new position and the exchange matching value of the old position to obtain a matching difference value; S44, setting a maximum matching difference value, during iteration, when the matching difference value is less than or equal to the maximum matching difference value, updating the position of the particle again according to the scheme update probability; when the matching difference value is greater than the maximum matching difference value, replacing the old position with the new position, forming a second offspring exchange scheme; S45, repeat S42-S44 until the set number of iterations is reached and the iteration is stopped, and the corresponding exchange plan is extracted when the regional risk change index of all regions in the low-risk candidate pool after the exchange is less than Tric1 and the mean of the exchange matching values ​​of all regions in the high-risk candidate pool is the largest.

[0009] A further improvement of the present invention is that the high-risk candidate pool extracts the areas where the risk change index is greater than Tric2 and calculates the corresponding comprehensive scores of the operators Pin, and extracts the operators whose comprehensive scores are greater than the set comprehensive score threshold in each area and their corresponding areas and sends them into the high-risk candidate pool; the low-risk candidate pool extracts the areas where the risk change index is less than Tric1 and calculates the corresponding operator ability scores Pca, and extracts the operators whose ability scores are less than the set ability score threshold in each area and their corresponding areas and sends them into the high-risk candidate pool.

[0010] A further improvement of the present invention is that the exchange matching value function first obtains the personnel exchange score of each staff member by extracting the weighted sum of the historical operation score mean and personnel ability score of each operator in the exchange plan in the area after the exchange; and calculates the difference between the mean of all personnel exchange scores after the exchange and the personnel exchange scores before the exchange as the exchange matching value function.

[0011] A further improvement of the present invention is that the scheme mutation probability is obtained by setting the initial value of the mutation probability P m (0) is obtained, and the personnel exchange score of each operator in the exchange plan in the exchange area is extracted as the post-exchange fitness, and a score benchmark value is set. When the post-exchange fitness is greater than the score benchmark value, the mutation probability is updated to P m (t) = P m (0)×(1-(t / T)), where P m (t) represents the mutation probability at the tth generation, and T is the maximum number of iterations; when the fitness after the swap is less than or equal to the scoring benchmark value, it is judged that when the fluctuation of the exchange matching value for three consecutive times is less than the set fluctuation value, the mutation probability is expanded to 30×P m (0).

[0012] A further improvement of the present invention is that the scheme update probability is obtained by calculating an exponential function of the ratio of the exchange matching value with base e to k×TD, k represents the Boltzmann constant, and TD represents a gradually decreasing parameter.

[0013] A further improvement of the present invention is that the calculation formula of the risk change index is: ; Among them, Eus represents the equipment usage status score, Pin represents the comprehensive score of personnel, and Env represents the environment score. Indicates the weight of the device usage status score. Indicates the comprehensive scoring weight of personnel, represents the environmental score weight, Indicates the risk baseline value.

[0014] A further improvement of the present invention is that the equipment usage status score is obtained by recording the number of equipment failures within a month and calculating the weighted average of the number of failures and the performance change rate; the performance change rate is obtained by the weighted average of the progress change index of the work completed in the unit time area and the equipment vibration change index; assuming that the maximum value of the percentage reduction of the degree of work per unit time in the past month is Mp, and the minimum value is mp, then the progress change index is expressed as (Mp-mp) / (Mp+mp); the equipment vibration change index is obtained by installing a vibration sensor in the equipment, assuming that the maximum value of the vibration speed per unit time in the past month is Zp, and the minimum value is zp, then the equipment vibration change index is expressed as (Zp-zp) / (Zp+zp).

[0015] The present invention is further improved in that the specific calculation steps of the comprehensive score of the personnel include extracting the working hours ygy of the operator in the industry, and obtaining the rating of the operator through the entry assessment score when joining the company, and obtaining the personnel ability score Pca by multiplying the working hours and the personnel rating; when the operator restarts the operation, the system records the number of operation errors num of the operator and the number of operation errors imnum of the key operation nodes in real time, and calculates the operation score Hqu=num×(imnum / num) of the operator; then the calculation formula of the comprehensive score Pin of the personnel is: ,in Indicates the weight of personnel ability score, Indicates the score weight of this operation.

[0016] A further improvement of the present invention is that the environmental score is obtained by standardizing the collected wind speed, humidity and rainfall and then performing a weighted summation.

[0017] On the other hand, the present invention provides a monitoring system based on the Internet of Things, comprising: The work partition module is used to partition the construction site area according to different construction types to obtain preliminary partitions of the construction site; The risk change monitoring module is used to calculate the risk change indicators of all areas in real time based on the equipment usage status score, personnel comprehensive score, and environmental score; The risk judgment module is used to set the risk change index thresholds Tric1 and Tric2, extract the areas where the risk change index is greater than or equal to Tric1 and less than or equal to Tric2, and send them to the safe area database, and extract the remaining areas and their corresponding operators and send them to the personnel risk scheduling module; The personnel risk scheduling module sets personnel replacement and matching strategies and readjusts personnel work areas.

[0018] A further improvement of the present invention is that the personnel risk scheduling module includes an exchange matching value function calculation unit and a scheme variation unit; the exchange matching value function calculation unit is used to calculate the fitness function of the personnel exchange matching strategy; the scheme variation unit is used to update the offspring personnel exchange scheme of the personnel exchange matching strategy.

[0019] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention first calculates the risk change index of the area in real time, identifies the high-risk area in time, ensures that the construction personnel work in a safe environment, and effectively reduces the accident rate; 2. Adopt personnel exchange and matching strategies, dynamically adjust personnel operation areas according to real-time risk assessment, optimize human resource allocation, ensure that personnel in high-risk areas can be adjusted to low-risk areas in a timely manner, and improve resource utilization efficiency; 3. By adding SA perturbations to the personnel exchange matching strategy and setting the probability of scheme mutation based on the comprehensive scores of personnel in the exchange scheme, we can make smarter decisions on when to make more frequent mutations and adaptively adjust the probability of mutation, thereby improving the efficiency and effectiveness of the algorithm. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 This is a flow chart of a monitoring method based on the Internet of Things of the present invention; Figure 2 This is a flow chart of a personnel exchange matching strategy for a monitoring method based on the Internet of Things of the present invention; Figure 3 A flow chart of the sources of input data in the personnel exchange matching strategy of the present invention; Figure 4 This is a framework diagram of a monitoring system based on the Internet of Things of the present invention. DETAILED DESCRIPTION

[0021] The technical solution of the present invention is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations on the technical solution of the present invention. The embodiments of the present invention and the technical features in the embodiments may be combined with each other unless there is a conflict.

[0022] The term "and / or" is only a description of the association relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " generally indicates that the related objects are in an "or" relationship.

[0023] Example 1 Figure 1 and Figure 2The flowcharts of a monitoring method based on the Internet of Things disclosed in this embodiment are respectively shown, and the steps are as follows: S1. Divide the construction site area into different zones according to different construction types to obtain preliminary zones of the construction site; For example, the roadbed construction area is mainly responsible for the basic construction of the road, including earth excavation, backfilling, compaction and other operations; Pavement construction area: After the roadbed construction is completed, the pavement is paved and maintained. This area involves the paving, compaction and maintenance of materials such as asphalt and cement; Bridge construction area: For transportation infrastructure projects that include bridges, a separate bridge construction area needs to be divided. This area involves the construction of bridge pile foundations, caps, piers, beams and slabs; Tunnel construction area: For transportation infrastructure projects that need to cross mountains or waters, tunnel construction areas are indispensable. This area involves tunnel excavation, support, lining and other operations; S2. Calculate the risk change indicators of all areas in real time based on the equipment usage status score, personnel comprehensive score, and environmental score; The equipment usage status score is obtained by recording the number of equipment failures within a month and calculating the weighted average of the number of failures and the performance change rate; the performance change rate is obtained by the weighted average of the progress change index of the work completed in the unit time area and the equipment vibration change index; assuming that the maximum value of the percentage reduction of the degree of work per unit time in the past month is Mp, and the minimum value is mp, then the progress change index is expressed as (Mp-mp) / (Mp+mp); in this embodiment, the unit time is every day, and the difference between the work progress percentage of the previous day and the work progress percentage of the previous two days from the current time node is calculated, and the work progress percentage is obtained by real-time reporting by the staff; the equipment vibration change index is obtained by installing a vibration sensor in the equipment, assuming that the maximum value of the vibration speed per unit time in the past month is Zp, and the minimum value is zp, then the equipment vibration change index is expressed as (Zp-zp) / (Zp+zp).

[0024] The specific calculation steps of the comprehensive personnel score include extracting the working hours ygy of the operator in the industry, obtaining the rating of the operator through the entry assessment score at the time of employment, and obtaining the personnel ability score Pca by multiplying the working hours by the personnel rating; for example, A is 100 - 80 points, B is 80 - 60 points, C is 60 - 40 points, D is 40 - 20 points, and those below 20 points are classified as basic staff. Among them, A is assigned 1, B is assigned 2, C is assigned 3, and D is assigned 4; when the operator resumes work, the system records the number of operation errors num of the operator in this operation in real time, and the number of operation errors imnum at the key operation nodes, and calculates the operation score Hqu of this operation of the operator = num×(imnum / num); then the calculation formula of the comprehensive personnel score Pin is , where represents the weight of the personnel ability score, represents the weight of this operation score.

[0025] The environmental score is obtained by standardizing and then weighted summing the collected wind speed, humidity, and rainfall.

[0026] The calculation formula of the risk change index is: ; Among them, Eus represents the equipment usage status score, Pin represents the comprehensive personnel score, Env represents the environmental score, represents the weight of the equipment usage status score, represents the weight of the comprehensive personnel score, represents the weight of the environmental score, represents the risk benchmark value.

[0027] S3. Set the risk change index thresholds Tric1 and Tric2, where Tric1 < Tric2, extract the area where the risk change index is greater than or equal to Tric1 and less than or equal to Tric2, send it to the safe area database, and extract the remaining areas and their corresponding operators and send them to step S4; S4. Set the personnel transfer matching strategy and readjust the operator's work area.

[0028] The setting of the thresholds and weights can be set by the operator according to the experimental results or experience.

[0029] Embodiment 2 Figure 2 The flowchart of the personnel transfer matching strategy in a monitoring method based on the Internet of Things in this embodiment is shown, and the specific steps include: S41. Randomly generate a set of initial solutions, each solution including a personnel exchange plan in a high-risk candidate pool and a low-risk candidate pool; that is, two binary arrays. For example, a solution may be a binary array consisting of a length of hnm and a length of lnm, and a 1 at each position indicates that the person at that position is exchanged to another group. Figure 3 The flow chart of the input data source in the personnel exchange matching strategy of this embodiment is shown; the high-risk candidate pool extracts the areas where the risk change index is greater than Tric2, and calculates the corresponding comprehensive score Pin of the operators, and extracts the operators in each area whose comprehensive score is greater than the set comprehensive score threshold and their corresponding areas and sends them to the high-risk candidate pool; the low-risk candidate pool extracts the areas where the risk change index is less than Tric1. Since the processes in different areas are different, the reference significance of the operation score of the operators in the low-risk candidate pool is not great, so the corresponding operator's personnel ability score Pca is calculated, and the operators in each area whose personnel ability score is less than the set personnel ability score threshold and their corresponding areas are extracted and sent to the high-risk candidate pool.

[0030] S42, creating an exchange matching value function as a fitness function; and setting a matching threshold, selecting a replacement scheme with an exchange matching value greater than the matching threshold as a parent generation replacement scheme; The exchange matching value function first obtains the personnel exchange score of each staff member by extracting the weighted sum of the historical operation score mean and personnel ability score of each operator in the exchange plan in the area after the exchange; and calculates the difference between the mean of all personnel exchange scores after the exchange and the personnel exchange scores before the exchange as the exchange matching value function.

[0031] For each selected exchange plan, a new position is generated through the plan mutation probability to form a new offspring personnel exchange plan. Because these particles may be closer to the local optimal solution, in the genetic algorithm or particle swarm algorithm, the better exchange plan can be easily destroyed due to the mutation process, which is manifested as the fitness function of the exchange plan, that is, the exchange matching value, remains unchanged for many consecutive times; therefore, it is necessary to control the mutation probability of the exchange plan to jump out of the local optimal solution in the algorithm; through the disturbance and acceptance probability mechanism of SA and the setting of the plan mutation probability for the personnel exchange plan, it is possible to jump out of the local optimum; first, the PSO algorithm is used to make each generated plan regularly search for the optimal point in space. When the particles gather near the optimal point, the SA algorithm is used to help some particles jump out of the local peak space while controlling the mutation probability of each plan, and searching again; then repeat this process.

[0032] The mutation probability of the scheme is set by setting the initial value of the mutation probability P m(0), extract the personnel exchange score of each operator in the exchange plan in the post-exchange area as the post-exchange fitness, set the score benchmark value, when the post-exchange fitness is greater than the score benchmark value, it indicates that the personnel in the exchange plan has higher ability, better tolerance and higher sensitivity to the exchange plan, at this time, the personnel in the plan can be made to jump out of the local optimal solution by reducing the mutation probability, then the updated mutation probability calculation formula is P m (t) = P m (0)×(1-(t / T)), where P m (t) represents the mutation probability at the tth generation, and T is the maximum number of iterations; On the contrary, when the fitness after the swap is less than or equal to the scoring benchmark value, it indicates that the scheme has a low sensitivity to the optimal solution. In order to enhance the ability of the individual to jump out of the local optimal solution, the performance of the person in the algorithm process is evaluated at this time. When the fluctuation of the swap matching value is less than the set fluctuation value for three consecutive times, the mutation probability is expanded to 30×P m (0).

[0033] S43, calculating the exchange matching value of the new position, and calculating the absolute value of the difference between the exchange matching value of the new position and the exchange matching value of the old position to obtain a matching difference value; S44. Set the maximum value of the matching difference. During iteration, when the matching difference value is less than or equal to the maximum value of the matching difference, update the position of the particle again according to the scheme update probability; when the matching difference value is greater than the maximum value of the matching difference, replace the old position with the new position to form the second child exchange scheme; the scheme update probability is obtained by calculating the exponential function of the ratio of the exchange matching value with base e to k×TD, where k represents the Boltzmann constant, and TD represents a gradually decreasing parameter. The step size of the reduction is set by the staff according to the experimental results. By adjusting the parameter TD, the exploration and development capabilities of the algorithm can be controlled; in the early stages of the algorithm, a higher TD helps the algorithm to explore the solution space extensively; as the algorithm proceeds, gradually reducing TD helps the algorithm to search for the optimal solution in the explored area.

[0034] S45, repeat S42-S44 until the set number of iterations is reached and the iteration is stopped, and the corresponding exchange plan is extracted when the regional risk change index of all regions in the low-risk candidate pool after the exchange is less than Tric1 and the mean of the exchange matching values ​​of all regions in the high-risk candidate pool is the largest.

[0035] The threshold and weight can be set by the operator according to experimental results or experience.

[0036] Example 3 Figure 4The framework diagram of a monitoring system based on the Internet of Things of the present invention is shown. Based on the same inventive concept as Embodiment 1 and Embodiment 2, the present invention provides a monitoring system based on the Internet of Things, including: The work partition module is used to partition the construction site area according to different construction types to obtain preliminary partitions of the construction site; The risk change monitoring module is used to calculate the risk change indicators of all areas in real time based on the equipment usage score, personnel comprehensive score, and environmental score; The risk judgment module is used to set the risk change index thresholds Tric1 and Tric2 (, extract the areas where the risk change index is greater than or equal to Tric1 and less than or equal to Tric2, and send them to the safe area database, and extract the remaining areas and their corresponding operators and send them to step S4; The personnel risk scheduling module sets the personnel exchange matching strategy and readjusts the personnel operation area. The personnel risk scheduling module includes an exchange matching value function calculation unit and a scheme variation unit; the exchange matching value function calculation unit is used to calculate the fitness function of the personnel exchange matching strategy; the scheme variation unit is used to update the offspring personnel exchange scheme of the personnel exchange matching strategy.

[0037] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0038] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0039] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0040] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0041] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the enlightenment of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the purpose of the present invention and the claims, which all fall within the protection of the present invention.

Claims

1. A monitoring method based on the Internet of Things, characterized in that: The following steps are involved: S1. Divide the construction site area into different zones according to different construction types to obtain preliminary zones of the construction site; S2. Calculate the risk change indicators of all areas in real time based on the equipment usage status score, personnel comprehensive score, and environmental score; S3, setting the risk change index thresholds Tric1 and Tric2, extracting the areas where the risk change index is greater than or equal to Tric1 and less than or equal to Tric2, and sending them to the safe area database, and extracting the remaining areas and their corresponding operators and sending them to step S4; S4. Set up personnel exchange and matching strategies and readjust personnel work areas.

2. The monitoring method based on the Internet of Things according to claim 1, characterized in that: The specific steps of the personnel exchange matching strategy include: S41, randomly generate a set of initial solutions, each solution including a personnel exchange plan in a high-risk candidate pool and a low-risk candidate pool; S42, creating an exchange matching value function as a fitness function; and setting a matching threshold, selecting a replacement scheme with an exchange matching value greater than the matching threshold as a parent generation replacement scheme, and generating a new position for each selected replacement scheme through a scheme mutation probability to form a new child generation personnel replacement scheme; S43, calculating the exchange matching value of the new position, and calculating the absolute value of the difference between the exchange matching value of the new position and the exchange matching value of the old position to obtain a matching difference value; S44, setting a maximum matching difference value, during iteration, when the matching difference value is less than or equal to the maximum matching difference value, updating the position of the particle again according to the scheme update probability; when the matching difference value is greater than the maximum matching difference value, replacing the old position with the new position, forming a second offspring exchange scheme; S45, repeat S42-S44 until the set number of iterations is reached and the iteration is stopped, and the corresponding exchange plan is extracted when the regional risk change index of all regions in the low-risk candidate pool after the exchange is less than Tric1 and the mean of the exchange matching values ​​of all regions in the high-risk candidate pool is the largest.

3. The monitoring method based on the Internet of Things according to claim 2, characterized in that: The high-risk candidate pool extracts the areas where the risk change index is greater than Tric2, calculates the corresponding comprehensive scores of the operators Pin, extracts the operators in each area whose comprehensive scores are greater than the set comprehensive score threshold and their corresponding areas and sends them into the high-risk candidate pool; the low-risk candidate pool extracts the areas where the risk change index is less than Tric1, calculates the corresponding operator capability scores Pca, extracts the operators in each area whose capability scores are less than the set capability score threshold and their corresponding areas and sends them into the high-risk candidate pool.

4. The monitoring method based on the Internet of Things according to claim 3 is characterized in that: The exchange matching value function first obtains the personnel exchange score of each staff member by extracting the weighted sum of the historical operation score mean and personnel ability score of each operator in the exchange plan in the area after the exchange; and calculates the difference between the mean of all personnel exchange scores after the exchange and the personnel exchange scores before the exchange as the exchange matching value function.

5. The monitoring method based on the Internet of Things according to claim 4 is characterized in that: The mutation probability of the scheme is set by setting the initial value of the mutation probability P m (0) is obtained, and the personnel exchange score of each operator in the exchange plan in the exchange area is extracted as the post-exchange fitness, and a score benchmark value is set. When the post-exchange fitness is greater than the score benchmark value, the mutation probability is updated to P m (t) = P m (0)×(1-(t / T)), where P m (t) represents the mutation probability at the tth generation, and T is the maximum number of iterations; When the fitness after the swap is less than or equal to the scoring benchmark value, it is determined that when the fluctuation of the swap matching value for three consecutive times is less than the set fluctuation value, the mutation probability is expanded to 30×P m (0).

6. The monitoring method based on the Internet of Things according to claim 5, characterized in that: The scheme update probability is obtained by calculating an exponential function of the ratio of the exchange matching value with base e to k×TD, where k represents the Boltzmann constant and TD represents a gradually decreasing parameter.

7. The monitoring method based on the Internet of Things according to claim 6, characterized in that: The calculation formula of the risk change index is: ； Among them, Eus represents the equipment usage status score, Pin represents the comprehensive score of personnel, and Env represents the environment score. Indicates the weight of the device usage status score. Indicates the comprehensive scoring weight of personnel, represents the environmental score weight, Indicates the risk baseline value.

8. The monitoring method based on the Internet of Things according to claim 2, characterized in that: The equipment usage status score is obtained by recording the number of equipment failures within a month and calculating the weighted average of the number of failures and the performance change rate; the performance change rate is obtained by the weighted average of the progress change index of the work completed in the unit time area and the equipment vibration change index; assuming that the maximum value of the percentage reduction of the degree of work per unit time in the past month is Mp, and the minimum value is mp, then the progress change index is expressed as (Mp-mp) / (Mp+mp); the equipment vibration change index is obtained by installing a vibration sensor in the equipment, assuming that the maximum value of the vibration speed per unit time in the past month is Zp, and the minimum value is zp, then the equipment vibration change index is expressed as (Zp-zp) / (Zp+zp).

9. The monitoring method based on the Internet of Things according to claim 2, characterized in that: The specific calculation steps of the comprehensive score of the personnel include extracting the working hours ygy of the operator in the industry, and obtaining the rating of the operator through the entry assessment score at the time of employment, and obtaining the personnel ability score Pca by multiplying the working hours and the personnel rating; when the operator restarts the operation, the system records the number of operation errors num of the operator and the number of operation errors imnum of the key operation nodes in real time, and calculates the operation score Hqu=num×(imnum / num) of the operator; then the calculation formula of the comprehensive score Pin of the personnel is: ,in Indicates the weight of personnel ability score, Indicates the score weight of this operation.

10. The monitoring method based on the Internet of Things according to claim 2, characterized in that: The environmental score is obtained by standardizing the collected wind speed, humidity and rainfall and then taking a weighted sum.

11. A monitoring system based on the Internet of Things, used to execute a monitoring method based on the Internet of Things as claimed in any one of claims 1 to 10, characterized in that: include: The work partition module is used to partition the construction site area according to different construction types to obtain preliminary partitions of the construction site; The risk change monitoring module is used to calculate the risk change indicators of all areas in real time based on the equipment usage status score, personnel comprehensive score, and environmental score; The risk judgment module is used to set the risk change index thresholds Tric1 and Tric2, extract the areas where the risk change index is greater than or equal to Tric1 and less than or equal to Tric2, and send them to the safe area database, and extract the remaining areas and their corresponding operators and send them to the personnel risk scheduling module; The personnel risk scheduling module sets personnel replacement and matching strategies and readjusts personnel work areas.

12. The monitoring system based on the Internet of Things according to claim 10, characterized in that: The personnel risk scheduling module includes an exchange matching value function calculation unit and a scheme variation unit; the exchange matching value function calculation unit is used to calculate the fitness function of the personnel exchange matching strategy; the scheme variation unit is used to update the offspring personnel exchange scheme of the personnel exchange matching strategy.

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