A collaborative interaction device based on artificial intelligence algorithm

Abstract

The present invention provides a collaborative interaction device based on an artificial intelligence algorithm, which belongs to the technical field of data transmission, and comprises a communication conversion module and a data analysis module, which is applied to a collaborative interaction method, specifically comprising: dividing the monitoring device into a delayed identification device and a normal identification device through identification delay data of construction safety risks of different monitoring devices at a construction site, determining the setting position of the collaborative interaction device by matching the setting position of an auxiliary identification device and an idle matching coefficient, and the setting position of the delayed identification device, and using the collaborative interaction device to obtain the idle situation of the matching auxiliary identification device, and assisting in the identification processing of the construction safety risk image of the delayed identification device based on the idle situation, thereby ensuring the efficiency of the identification processing of the construction safety risk image.

Description

Technical Field

[0001] The present invention belongs to the technical field of data transmission, and in particular relates to a collaborative interaction device based on artificial intelligence algorithm. Background Art

[0002] In the process of construction on a construction site, there will inevitably be various types of construction safety risks. In the existing solutions, the construction safety risks of the construction site during the construction process are often identified through an IoT monitoring device. Specifically, a similar technical solution is given in the invention patent application CN202410143900.5 "Smart construction site safety supervision method and system based on the Internet of Things". However, the existing technical solutions have the following technical problems:

[0003] In the process of identifying and processing construction safety risks, due to the deviations in the construction status of the monitoring areas corresponding to different IoT monitoring devices, there are also deviations in the need for different IoT monitoring devices to identify safety risks using preset artificial intelligence models. For example, if the monitoring image of the IoT monitoring device has not changed within a certain period of time, there is no need to identify construction safety risks.

[0004] Therefore, if the idle data of the IoT monitoring device cannot be combined to generate an interactive recognition and processing strategy for the monitoring images of construction safety risks, the accuracy of the identification and processing of construction safety risks cannot be improved.

[0005] In response to the above technical problems, the present invention takes into account the idle situation of identifying security risks of IoT monitoring devices, and uses idle IoT monitoring devices to assist in identifying IoT monitoring devices with greater demand for identifying security risks. This improves the efficiency of identifying and processing security risks without increasing the hardware cost of the monitoring devices. Specifically, the present application provides a collaborative interaction device based on an artificial intelligence algorithm. Summary of the invention

[0006] To achieve the purpose of the present invention, the present invention adopts the following technical solutions:

[0007] According to one aspect of the present invention, a collaborative interaction device based on an artificial intelligence algorithm is provided.

[0008] A collaborative interaction device based on an artificial intelligence algorithm, including a communication conversion module and a data analysis module, is applied to a collaborative interaction method, specifically including:

[0009] S1 divides the monitoring devices at the construction site into delayed identification devices and normal identification devices based on the identification delay data of construction safety risks of different monitoring devices at the construction site;

[0010] S2, based on different types of construction safety risk factors in the monitoring area corresponding to the normal identification device, determining an available auxiliary identification device in the normal identification device;

[0011] S3: determining matching data of idle time of the available auxiliary recognition device and busy time of the delayed recognition device based on the recognition results of the monitoring images of the available auxiliary recognition device and the delayed recognition device, and determining idle matching coefficients of different available auxiliary recognition devices and the delayed recognition device and matching auxiliary recognition devices based on the matching data;

[0012] S4 determines the setting position of the collaborative interaction device through the setting position of the matching auxiliary identification device, the idle matching coefficient, and the setting position of the delayed identification device, and uses the collaborative interaction device to obtain the idle status of the matching auxiliary identification device, and assists in the recognition and processing of the construction safety risk image of the delayed identification device based on the idle status.

[0013] The beneficial effects of the present invention are:

[0014] By using the delay data of construction safety risk identification of different monitoring devices at the construction site, the delay identification device in the monitoring device is determined, thereby realizing the identification of the delay identification device from the perspective of the identification delay of the monitoring image of the construction safety risk. It also lays the foundation for the targeted auxiliary identification processing of the construction safety risk image of the delay identification device, and improves the efficiency of the identification processing of the construction safety risk image.

[0015] Based on the matching data, the idle matching coefficients of different available auxiliary identification devices and delayed identification devices and the matching auxiliary identification devices are determined, thereby avoiding the inability to accurately realize the auxiliary identification of the delayed identification device due to the non-overlapping idle time periods of the matching auxiliary identification device and the delayed identification device, and realizing the screening of available auxiliary identification devices with a higher idle degree from the perspective of the matching of the idle time periods in the historical identification process, thereby ensuring the matching and reliability of the auxiliary identification processing.

[0016] A further technical solution is that the communication conversion module is responsible for data interaction processing of the communication data between the matching auxiliary identification device and the delayed identification device.

[0017] A further technical solution is that the data analysis module is responsible for obtaining the idle status of the matching auxiliary identification device, and using the idle status to determine the matching auxiliary identification device that assists in the identification processing of the construction safety risk image of the delayed identification device.

[0018] A further technical solution is that the recognition delay data includes the number of recognition delays and recognition delays for different numbers of recognition delays.

[0019] A further technical solution is that the idle state of the matching auxiliary identification device is determined based on changes in the monitoring image of the matching auxiliary identification device. Specifically, when the monitoring image of the matching auxiliary identification device does not change within a preset time period, it is determined that the matching auxiliary identification device is in an idle state.

[0020] A further technical solution is to assist in the identification and processing of the construction safety risk image of the delayed identification device based on the idle situation, specifically including:

[0021] Determine the continuous idle time of different matching auxiliary identification devices based on the analysis result of the idle situation;

[0022] The matching auxiliary recognition device with the longest continuous idle time is used to perform recognition processing on the construction safety risk image of the delayed recognition device.

[0023] Other features and advantages will be described in the following description. The objects and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description and drawings.

[0024] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the accompanying drawings;

[0026] Figure 1 It is a framework diagram of a collaborative interaction device based on artificial intelligence algorithms;

[0027] Figure 2 is a flow chart of a method for dividing a monitoring device into a delayed identification device and a normal identification device;

[0028] Figure 3 is a flow chart of a method for determining an available auxiliary identification device in a normal identification device;

[0029] Figure 4 The present invention is a flow chart of a method for determining a setting position of a collaborative interaction device. DETAILED DESCRIPTION

[0030] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

[0031] The present invention considers the idle situation of the security risk identification of the Internet of Things monitoring devices, utilizes the idle Internet of Things monitoring devices to assist in identifying the Internet of Things monitoring devices with greater security risk identification requirements, and improves the efficiency of security risk identification processing without increasing the hardware cost of the monitoring devices.

[0032] Delayed identification device: Determine the delayed identification device of the monitoring device according to the number of times the delay in identifying construction safety risks is greater than 1 minute. Specifically, a monitoring device with a delay time greater than 5 times will be regarded as a delayed identification device.

[0033] Available auxiliary identification devices: Normal identification devices with the number of construction safety risk factors less than 3 are regarded as available auxiliary identification devices.

[0034] The idle matching coefficient between the available auxiliary identification device and the delayed identification device is determined by the ratio of the matching number of the idle moments of the available auxiliary identification device to the busy moments of the delayed identification device. If the matching number ratio is 0.6, the idle matching coefficient is 0.6. Devices with an idle matching coefficient greater than 0.5 are regarded as matching auxiliary identification devices.

[0035] Setting position of collaborative interaction device: Determine the comprehensive matching coefficient of the candidate setting position according to the position matching with the delayed recognition device, and use the comprehensive matching coefficient to determine the setting position of the collaborative interaction device, and take the candidate setting position with the largest comprehensive matching coefficient as the setting position of the collaborative interaction device.

[0036] To solve the above problems, according to one aspect of the present invention, Figure 1 As shown, a collaborative interaction device based on an artificial intelligence algorithm is provided, including a communication conversion module and a data parsing module, which is applied to a collaborative interaction method, specifically including:

[0037] S1 divides the monitoring devices at the construction site into delayed identification devices and normal identification devices based on the identification delay data of construction safety risks of different monitoring devices at the construction site;

[0038] Furthermore, the communication conversion module is responsible for data interaction processing of communication data between the matching auxiliary identification device and the delayed identification device.

[0039] Specifically, the data analysis module is responsible for obtaining the idle status of the matching auxiliary identification device, and using the idle status to determine the matching auxiliary identification device that assists the delayed identification device in the identification process of the construction safety risk image.

[0040] It should be noted that the recognition delay data includes the number of recognition delays and recognition delays of different recognition delay numbers.

[0041] Optional, such as Figure 2 As shown, the monitoring device is divided into a delayed identification device and a normal identification device, specifically including:

[0042] Determining the number of identification delays of the monitoring device for different types of construction safety risks based on the identification delay data of the construction safety risks of the monitoring device;

[0043] Determine the identification delay risk coefficients of different types of construction safety risks based on the proportion of the identification delay times of different types of construction safety risks;

[0044] The delay risk coefficient of the monitoring device is determined by the sum of the delay risk coefficients of identification of different types of construction safety risks, and the monitoring device is divided into a delay identification device and a normal identification device according to the delay risk coefficient.

[0045] Furthermore, the monitoring device is divided into a delay identification device and a normal identification device according to the delay risk coefficient, specifically including:

[0046] When the delay risk coefficient of the monitoring device is within a preset risk range, the monitoring device is determined to be a delay identification device;

[0047] When the delay risk coefficient of the monitoring device is not within a preset risk range, it is determined that the monitoring device is a normal identification device.

[0048] It should also be noted that the monitoring device is divided into a delayed recognition device and a normal recognition device, specifically including:

[0049] The total number of identification delays of the monitoring device is determined by using the number of identification delays, and the monitoring device is divided into a delayed identification device and a normal identification device by using the total number of identification delays.

[0050] Optionally, the monitoring device is divided into a delayed identification device and a normal identification device, including steps S11-S13:

[0051] S11 determines the number of identification delays of the monitoring device for different types of construction safety risks based on the identification delay data of the construction safety risks of the monitoring device;

[0052] Optionally, before entering step S12, it is also necessary to determine whether the total number of identification delays of the monitoring device for different types of construction safety risks meets the requirements. When the total number of identification delays of the monitoring device for different types of construction safety risks does not meet the requirements, the monitoring device is directly determined to be a delayed identification device. When the total number of identification delays meets the requirements, step S12 is entered again.

[0053] S12 determines the risk identification delay coefficients of different types of construction safety risks by using the identification delay times and the identification delays of different identification delay times;

[0054] S13 determines the delay risk coefficient of the monitoring device according to the average value of the risk identification delay coefficient, and divides the monitoring device into a delay identification device and a normal identification device according to the delay risk coefficient.

[0055] Optionally, step S12 includes steps S121-S122, specifically:

[0056] S121 determines whether there are types of construction safety risks whose identification delay times do not meet the requirements by using the identification delay times. When the number of types of construction safety risks whose identification delay times do not meet the requirements is greater than the preset number of types, the monitoring device is directly determined to be a delay identification device. When the number of types of construction safety risks whose identification delay times do not meet the requirements is not greater than the preset number of types, the process proceeds to step S122.

[0057] S122 uses the identification delay times and the identification delays of different identification delay times to determine the risk identification delay coefficients of different types of construction safety risks. When the number of types of construction safety risks that do not meet the requirements for the risk identification delay coefficient is greater than the preset number of types, the monitoring device is directly determined to be a delay identification device. When the number of types of construction safety risks that do not meet the requirements for the risk identification delay coefficient is not greater than the preset number of types, the process proceeds to step S13.

[0058] S2, based on different types of construction safety risk factors in the monitoring area corresponding to the normal identification device, determining an available auxiliary identification device in the normal identification device;

[0059] Furthermore, the construction safety risk factors include falling from heights, being hit by objects, mechanical injuries, electric shock, collapse, fire and explosion, poisoning and suffocation, occupational diseases, vehicle injuries, drowning, and burns.

[0060] Optional, such as Figure 3 As shown, the method for determining the available auxiliary identification device in the normal identification device is:

[0061] Taking the monitoring area corresponding to the normal identification device as the matching monitoring area, and determining different types of construction safety risk factors in the matching monitoring area through the construction data of the matching monitoring area;

[0062] Acquire the number of construction safety risk factors of the matching monitoring area on different dates, and determine the monitoring demand coefficient of the matching monitoring area on different dates according to the number of construction safety risk factors on different dates;

[0063] The regional monitoring demand coefficient of the matching monitoring area is determined based on the monitoring demand coefficients on different dates, and the regional monitoring demand coefficient is used to determine whether the normal identification device is an available auxiliary identification device.

[0064] Furthermore, the value range of the area monitoring requirement coefficient is between 0 and 1, wherein when the area monitoring area requirement coefficient of the normal identification device is greater than a preset requirement coefficient, it is determined that the normal monitoring device does not belong to the available auxiliary identification device.

[0065] It should also be noted that the method for determining the available auxiliary identification device in the normal identification device is:

[0066] Taking the monitoring area corresponding to the normal identification device as the matching monitoring area, and determining different types of construction safety risk factors in the matching monitoring area through the construction data of the matching monitoring area;

[0067] Acquire the number of construction safety risk factors of the matching monitoring area on different dates, and determine the monitoring demand coefficient of the matching monitoring area on different dates according to the number of construction safety risk factors on different dates;

[0068] The regional monitoring demand coefficient of the matching monitoring area is determined based on the monitoring demand coefficients on different dates, and the regional monitoring demand coefficient is used to determine whether the normal identification device is an available auxiliary identification device.

[0069] Optionally, the method for determining the available auxiliary identification device in the normal identification device is:

[0070] Taking the monitoring area corresponding to the normal identification device as the matching monitoring area, and determining different types of construction safety risk factors in the matching monitoring area through the construction data of the matching monitoring area;

[0071] Obtaining the number of dates corresponding to the construction safety risk factors of the matching monitoring area, and using the number of dates to determine the risk monitoring requirement coefficients of different types of construction safety risk factors;

[0072] The risk monitoring requirement coefficient is used to perform monitoring requirement risk factors in the construction safety risk factors, and whether the normal identification device is an available auxiliary identification device is determined by the number of the monitoring requirement risk factors.

[0073] Optionally, the determination of the available auxiliary identification device in the normal identification device includes steps S21-S23, specifically:

[0074] S21: taking the monitoring area corresponding to the normal identification device as a matching monitoring area, and determining different types of construction safety risk factors in the matching monitoring area through the construction data of the matching monitoring area;

[0075] S22: obtaining the number of construction safety risk factors of the matching monitoring area on different dates, and determining the monitoring demand coefficient of the matching monitoring area on different dates according to the number of construction safety risk factors on different dates;

[0076] S23 determines the proportion of dates when the monitoring demand coefficient is greater than a preset demand coefficient threshold based on the monitoring demand coefficient on different dates, and uses the proportion of dates when the monitoring demand coefficient is greater than the preset demand coefficient threshold to determine whether the normal identification device is an available auxiliary identification device.

[0077] It should be noted that, when the proportion of the number of days on which the monitoring demand coefficient is greater than the preset demand coefficient threshold is greater than the proportion of the preset number of days, it is determined that the normal identification device does not belong to the available auxiliary identification device.

[0078] Optionally, the step S22 includes steps S221 to S223, specifically:

[0079] S221 obtains the number of dates corresponding to the construction safety risk factors of the matching monitoring area. When the number of construction safety risk factors corresponding to the number of dates is greater than the number of preset dates and does not meet the requirement, it is directly determined that the normal identification device does not belong to the available auxiliary identification device. When the number of construction safety risk factors corresponding to the number of dates is greater than the number of preset dates and meets the requirement, enter step S222;

[0080] S222 obtains the number of construction safety risk factors of the matching monitoring area on different dates. When the number of construction risk safety factors is greater than the number of preset factors, and the ratio of the number of dates does not meet the requirement, it is directly determined that the normal identification device does not belong to the available auxiliary identification device. When the number of construction risk safety factors is greater than the number of preset factors, and the ratio of the number of dates meets the requirement, step S223 is entered;

[0081] S223 determines the monitoring demand coefficient of the matching monitoring area on different dates according to the number of construction safety risk factors on different dates;

[0082] Optionally, the step S23 includes step S231 and step S232, which specifically include:

[0083] S231 determines the proportion of dates when the monitoring demand coefficient is greater than a preset demand coefficient threshold based on the monitoring demand coefficient on different dates. When the proportion of dates when the monitoring demand coefficient is greater than the preset demand coefficient threshold does not meet the requirement, it is directly determined that the normal identification device does not belong to the available auxiliary identification device. When the proportion of dates when the monitoring demand coefficient is greater than the preset demand coefficient threshold meets the requirement, enter step S232;

[0084] S232 uses the proportion of the number of dates when the monitoring demand coefficient is greater than the preset demand coefficient threshold and the monitoring demand coefficients of different dates to match the regional monitoring demand coefficient of the monitoring area, and uses the regional monitoring demand coefficient to determine whether the normal identification device is an available auxiliary identification device.

[0085] S3: determining matching data of idle time of the available auxiliary recognition device and busy time of the delayed recognition device based on the recognition results of the monitoring images of the available auxiliary recognition device and the delayed recognition device, and determining idle matching coefficients of different available auxiliary recognition devices and the delayed recognition device and matching auxiliary recognition devices based on the matching data;

[0086] Furthermore, the matching data includes the number of matching time periods and the matching durations of different matching time periods.

[0087] Specifically, the matching period is a period in which the matching duration is greater than a preset matching duration.

[0088] It should be noted that the method for determining the matching auxiliary identification device is:

[0089] Determine the matching time periods of the available auxiliary identification device and the delayed identification device on different dates through the matching data;

[0090] Based on the matching time periods on different dates, determining the total matching duration in the matching time periods on different dates, and determining the date idle matching coefficients of the available auxiliary recognition devices and the delayed recognition device on different dates through the total matching duration;

[0091] The idle matching coefficients of the available auxiliary identification device and the delayed identification device are determined based on the idle matching coefficients on different dates, and the idle matching coefficients are used to determine whether the available auxiliary identification device is a matching auxiliary identification device.

[0092] Furthermore, the idle matching coefficient is an average value of the idle matching coefficients on different dates.

[0093] In addition, it can be understood that when the idle matching coefficient is greater than a preset matching coefficient threshold, the available auxiliary identification device is determined to be a matching auxiliary identification device.

[0094] Optionally, the method for determining the matching auxiliary identification device includes steps S31 to S33, specifically including:

[0095] S31 determines the matching time periods of the available auxiliary identification device and the delayed identification device on different dates through the matching data;

[0096] Optionally, step S31 includes step S311 and step S312, specifically:

[0097] S311: when it is determined through the matching data that there is no matching period between the available auxiliary identification device and the delayed identification device, it is directly determined that the available auxiliary identification device does not belong to the matching auxiliary identification device. When there is a matching period, the process proceeds to step S312;

[0098] S312: Determine the matching time periods of the available auxiliary identification device and the delayed identification device on different dates through the matching data. When the proportion of the number of dates in the matching time period does not meet the requirement, directly determine that the available auxiliary identification device does not belong to the matching auxiliary identification device. When the proportion of the number of dates in the matching time period meets the requirement, proceed to step S32.

[0099] S32 determines the number of matching time periods on different dates based on the matching time periods on different dates, and determines the date idle matching coefficients of the available auxiliary recognition devices and the delayed recognition device on different dates in combination with the matching durations of the different matching time periods on different dates;

[0100] S33 determines idle matching dates among the dates based on idle matching coefficients of different dates, and determines whether the available auxiliary identification device is a matching auxiliary identification device by using a ratio of the number of idle matching dates.

[0101] Optionally, the above step S32 includes steps S321 to S323, which are specifically:

[0102] S321 determines the number of matching time periods on different dates based on the matching time periods on different dates. When the average value of the number of matching time periods on different dates or the average value of the total matching duration of the matching time periods does not meet the requirements, it is directly determined that the available auxiliary identification device does not belong to the matching auxiliary identification device. When the average value of the number of matching time periods on different dates and the average value of the total matching duration of the matching time periods do not meet the requirements but meet the requirements, it proceeds to step S322.

[0103] S322 determines the number of matching time periods on different dates based on the matching time periods on different dates, and determines the date idle matching coefficients of the available auxiliary identification devices and the delayed identification device on different dates in combination with the matching durations of the different matching time periods on different dates. When there is no date with a date idle matching coefficient greater than a preset idle matching coefficient threshold, it is directly determined that the available auxiliary identification device does not belong to the matching auxiliary identification device. When there is a date with a date idle matching coefficient greater than the preset idle matching coefficient threshold, it proceeds to step S33.

[0104] S4 determines the setting position of the collaborative interaction device through the setting position of the matching auxiliary identification device, the idle matching coefficient, and the setting position of the delayed identification device, and uses the collaborative interaction device to obtain the idle status of the matching auxiliary identification device, and assists in the recognition and processing of the construction safety risk image of the delayed identification device based on the idle status.

[0105] Specifically, Figure 4 As shown, the method for determining the setting position of the collaborative interaction device is:

[0106] Determining an alternative installation position of the collaborative interaction device using available installation positions of the construction site;

[0107] Acquire the distances between different candidate setting positions and the setting position of the matching auxiliary identification device, and determine the position matching coefficient between the candidate setting position and the matching auxiliary identification device in combination with the idle matching coefficients of different matching auxiliary identification devices;

[0108] Determining a position matching coefficient between the candidate setting position and the setting position of the delay identification device based on a distance between the candidate setting position and the setting position of the delay identification device;

[0109] The position comprehensive matching coefficient of the candidate setting position is determined according to the position matching coefficient with the delayed recognition device and the position matching coefficient with the matching auxiliary recognition device, and the setting position of the collaborative interaction device is determined using the position comprehensive matching coefficient.

[0110] Further, determining the setting position of the collaborative interaction device by using the position comprehensive matching coefficient specifically includes:

[0111] The candidate setting position with the largest comprehensive position matching coefficient is used as the setting position of the collaborative interaction device.

[0112] Specifically, the idle state of the matching auxiliary identification device is determined according to changes in the monitoring image of the matching auxiliary identification device. Specifically, when the monitoring image of the matching auxiliary identification device does not change within a preset period of time, it is determined that the matching auxiliary identification device is in an idle state.

[0113] It can be understood that the auxiliary recognition processing of the construction safety risk image of the delayed recognition device based on the idle situation specifically includes:

[0114] Determine the continuous idle time of different matching auxiliary identification devices based on the analysis result of the idle situation;

[0115] The matching auxiliary recognition device with the longest continuous idle time is used to perform recognition processing on the construction safety risk image of the delayed recognition device.

[0116] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0117] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0118] The above description is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included in the scope of the claims of this specification.

Claims

1. A collaborative interaction device based on artificial intelligence algorithm, including a communication conversion module and a data analysis module, applied to a collaborative interaction method, characterized in that: Specifically include: By using the identification delay data of construction safety risks of different monitoring devices at the construction site, the monitoring devices are divided into delayed identification devices and normal identification devices; Determining available auxiliary identification devices in the normal identification device based on different types of construction safety risk factors in the monitoring area corresponding to the normal identification device; Based on the recognition results of the monitoring images of the available auxiliary recognition device and the delayed recognition device, determining the matching data of the idle time of the available auxiliary recognition device and the busy time of the delayed recognition device, and determining the idle matching coefficients of different available auxiliary recognition devices and the delayed recognition device and matching auxiliary recognition devices based on the matching data; The setting position of the collaborative interaction device is determined by the setting position of the matching auxiliary identification device, the idle matching coefficient, and the setting position of the delayed identification device, and the collaborative interaction device is used to obtain the idle status of the matching auxiliary identification device, and the recognition processing of the construction safety risk image of the delayed identification device is assisted based on the idle status.

2. The collaborative interaction device based on artificial intelligence algorithm according to claim 1, characterized in that: The communication conversion module is responsible for data interaction processing of communication data between the matching auxiliary identification device and the delayed identification device.

3. The collaborative interaction device based on artificial intelligence algorithm according to claim 1, characterized in that: The data analysis module is responsible for obtaining the idle status of the matching auxiliary recognition device, and using the idle status to determine the matching auxiliary recognition device that assists the delayed recognition device in the recognition process of the construction safety risk image.

4. The collaborative interaction device based on artificial intelligence algorithm according to claim 1, characterized in that: The recognition delay data includes the number of recognition delays and recognition delays for different numbers of recognition delays.

5. The collaborative interaction device based on artificial intelligence algorithm according to claim 1, characterized in that: The monitoring device is divided into a delayed recognition device and a normal recognition device, specifically including: Determining the number of identification delays of the monitoring device for different types of construction safety risks based on the identification delay data of the construction safety risks of the monitoring device; Determine the identification delay risk coefficients of different types of construction safety risks based on the proportion of the identification delay times of different types of construction safety risks; The delay risk coefficient of the monitoring device is determined by the sum of the delay risk coefficients of identification of different types of construction safety risks, and the monitoring device is divided into a delay identification device and a normal identification device according to the delay risk coefficient.

6. The collaborative interaction device based on artificial intelligence algorithm according to claim 5, characterized in that: The monitoring device is divided into a delayed identification device and a normal identification device according to the delay risk coefficient, specifically including: When the delay risk coefficient of the monitoring device is within a preset risk range, the monitoring device is determined to be a delay identification device; When the delay risk coefficient of the monitoring device is not within a preset risk range, it is determined that the monitoring device is a normal identification device.

7. The collaborative interaction device based on artificial intelligence algorithm according to claim 1, characterized in that: The construction safety risk factors include falling from heights, being hit by objects, mechanical injuries, electric shock, collapse, fire and explosion, poisoning and suffocation, occupational diseases, vehicle injuries, drowning, and burns.

8. The collaborative interaction device based on artificial intelligence algorithm according to claim 1, characterized in that: The method for determining the available auxiliary identification device in the normal identification device is: Taking the monitoring area corresponding to the normal identification device as the matching monitoring area, and determining different types of construction safety risk factors in the matching monitoring area through the construction data of the matching monitoring area; Acquire the number of construction safety risk factors of the matching monitoring area on different dates, and determine the monitoring demand coefficient of the matching monitoring area on different dates according to the number of construction safety risk factors on different dates; The regional monitoring demand coefficient of the matching monitoring area is determined based on the monitoring demand coefficients on different dates, and the regional monitoring demand coefficient is used to determine whether the normal identification device is an available auxiliary identification device.

9. The collaborative interaction device based on artificial intelligence algorithm according to claim 1, characterized in that: The matching data includes the number of matching time periods and the matching durations of different matching time periods.

10. The collaborative interaction device based on artificial intelligence algorithm according to claim 1, characterized in that: The idle state of the matching auxiliary identification device is determined according to the change of the monitoring image of the matching auxiliary identification device. Specifically, when the monitoring image of the matching auxiliary identification device does not change within a preset period of time, it is determined that the matching auxiliary identification device is in an idle state.

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