An artificial intelligence-based data machine room environment management system and method

Abstract

The application provides an artificial intelligence-based data machine room environment management system and method, and belongs to the technical field of artificial intelligence, and specifically comprises: determining the correction evaluation quantity of the machine room equipment according to the number of cooling fans of the machine room equipment, the ventilation volume, the PCB area and the operation life, and dividing the machine room equipment into the concerned machine room equipment and other machine room equipment through the correction evaluation quantity; when it is determined that the temperature and humidity threshold needs to be corrected through the number of the concerned machine room equipment and other machine room equipment and the correction evaluation quantity of the machine room equipment, the temperature and humidity threshold is corrected to obtain an adjustment threshold through the dust content of the data machine room, the number of the concerned machine room equipment and other machine room equipment and the correction evaluation quantity of the machine room equipment, and the temperature and humidity of the data machine room is controlled according to the adjustment threshold, so that the safety of the temperature and humidity control is further improved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of artificial intelligence, and particularly relates to a data machine room environment management system and method based on artificial intelligence. BACKGROUND

[0002] In order to realize the management of the data machine room environment, the prior art scheme controls the main drying equipment and the temperature control equipment according to the monitoring of the weighted average of the equipment temperature monitoring value and the environment temperature monitoring value and the secondary humidity threshold value, but has the following technical problems:

[0003] The influence of the environment dust content in the machine room on the humidity threshold value is ignored, specifically, when the environment dust content in the machine room is large, if the humidity is too high, not only the probability of static electricity of the machine room equipment will become large, but also the dust deposition probability of the heat dissipation device of the machine room equipment will become large, which leads to poor heat dissipation of the machine room equipment, and further affects the safety of the operation of the machine room equipment.

[0004] In view of the above technical problems, the present application provides a data machine room environment management system and method based on artificial intelligence. SUMMARY

[0005] In order to achieve the purpose of the present application, the present application adopts the following technical solutions:

[0006] According to one aspect of the present application, a data machine room environment management method based on artificial intelligence is provided.

[0007] A data machine room environment management method based on artificial intelligence, characterized in that it specifically comprises:

[0008] S11 divides the machine room equipment into general equipment and special equipment through the type of the machine room equipment of the data machine room, the type of the processed data and the data volume, and determines the temperature and humidity threshold value of the data machine room through the number of the general equipment and the special equipment and the area of the data machine room;

[0009] S12 determines the correction evaluation quantity of the machine room equipment by using an artificial intelligence model according to the number of the heat dissipation fan of the machine room equipment, the ventilation volume, the PCB area and the operation life, and divides the machine room equipment into attention machine room equipment and other machine room equipment through the correction evaluation quantity, determines whether the temperature and humidity threshold value needs to be corrected through the number of the attention machine room equipment and the other machine room equipment and the correction evaluation quantity of the machine room equipment, if yes, enters step S14, and if no, enters step S13;

[0010] S13 determines whether the dust content of the data center needs to be corrected according to the temperature and humidity threshold value, if yes, enters step S14, if not, controls the temperature and humidity of the data center according to the temperature and humidity threshold value;

[0011] S14 corrects the temperature and humidity threshold value according to the dust content of the data center, the number of the concerned data center equipment and other data center equipment, and the correction evaluation value of the data center equipment, and controls the temperature and humidity of the data center according to the adjusted threshold value.

[0012] Further, the type of the data center equipment of the data center includes but is not limited to servers, switches, routers, hardware gateways, and hardware firewalls.

[0013] Further, the data center equipment is divided into general equipment and special equipment according to the type of the data center equipment, the type of the processed data, and the data volume, and specifically includes:

[0014] S21 obtains the type of the data center equipment, and determines whether the type of the data center equipment belongs to a specific equipment type, if yes, determines that the data center equipment is special equipment, if not, enters step S22;

[0015] S22 obtains the type of the data processed by the data center equipment, and determines whether the data needs to be judged according to the data volume, if yes, enters step S23, if not, enters step S24;

[0016] S23 obtains the data volume processed by the data center equipment within a set time, determines the maximum value and the average value of the data volume processed by the data center equipment within the set time according to the data volume processed by the data center equipment within the set time, determines the data evaluation value of the data center equipment according to the cumulative data volume processed by the data center equipment, and determines whether the data center equipment belongs to special equipment according to the data evaluation value of the data center equipment, if yes, determines that the data center equipment is special equipment, if not, enters step S24;

[0017] S24 determines the type evaluation value of the data center equipment according to the type of the data center equipment, the type of the processed data, and the data evaluation value, and divides the data center equipment into general equipment and special equipment according to the type evaluation value.

[0018] Further, the specific equipment type includes but is not limited to hardware gateways and hardware firewalls.

[0019] Further, the data center equipment is divided into general equipment and special equipment according to the type evaluation value, and specifically includes:

[0020] When the type evaluation value of the machine room equipment is greater than a preset type value, the machine room equipment is determined as a special equipment, otherwise, the machine room equipment is determined as a general equipment.

[0021] Further technical solutions are that the value range of the correction evaluation quantity is between 0 and 1, wherein the greater the static correction evaluation quantity of the machine room equipment is, the greater the heat dissipation correction evaluation quantity is, the longer the operation life of the machine room equipment is, and the higher the historical dust content of the data machine room is, the greater the correction evaluation quantity of the machine room equipment is.

[0022] Further technical solutions are that when the dust content of the data machine room is greater than a preset value, it is determined that the temperature and humidity threshold needs to be corrected.

[0023] In a second aspect, the present application provides a computer system, comprising a memory and a processor connected in communication, and a computer program stored on the memory and capable of running on the processor, characterized in that the processor executes the computer program to perform the above-mentioned artificial intelligence-based data machine room environment management method.

[0024] In a third aspect, the present application provides a computer storage medium having a computer program stored thereon, when the computer program is executed in a computer, the computer program causes the computer to perform the above-mentioned artificial intelligence-based data machine room environment management method.

[0025] The beneficial effects of the present application are that:

[0026] The number of the general equipment and the special equipment and the area of the data machine room are used to determine the temperature and humidity threshold of the data machine room, so that the determination of the temperature and humidity threshold not only considers the influence of the area of the data machine room on the adjustment rate, but also considers the difference in reliability requirements of the number of different types of equipment, ensuring the safety of temperature and humidity adjustment.

[0027] The number of the general equipment and the special equipment and the area of the data machine room are used to determine the temperature and humidity threshold of the data machine room, so that the determination of the temperature and humidity threshold not only considers the influence of the area of the data machine room on the adjustment rate, but also considers the difference in reliability requirements of the number of different types of equipment, ensuring the safety of temperature and humidity adjustment.

[0028] The temperature and humidity threshold is corrected by the dust content of the data room, the number of the concerned data room equipment and other data room equipment, and the correction evaluation amount of the data room equipment, so as to consider the influence of different dust content on the temperature and humidity adjustment threshold, and the influence of the safe state of the data room equipment caused by the running time on the temperature and humidity adjustment threshold, so as to ensure the safety and reliability of the operation of the data room equipment.

[0029] Other features and advantages will be set forth in the descriptions that follow, and in part will be apparent from the description, or can be learned by practice of the application. The purposes and other advantages of the application will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.

[0030] To make the above objectives, features and advantages of the present application more apparent, the following preferred embodiments are specifically described with reference to the attached drawings, and the detailed description is as follows. BRIEF DESCRIPTION OF DRAWINGS

[0031] The above and other features and advantages of the present application will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings:

[0032] Figure 1 is a flow chart of an artificial intelligence-based data room environment management method according to embodiment 1;

[0033] Figure 2 is a flow chart of dividing the data room equipment into general equipment and special equipment according to the type of the data room equipment, the type of the processed data and the data volume of the data room equipment in the data room according to embodiment 1;

[0034] Figure 3 is a flow chart of the specific steps of the correction evaluation amount determination according to embodiment 1;

[0035] Figure 4 is a flow chart of determining whether the temperature and humidity threshold needs to be corrected according to the number of the concerned data room equipment and other data room equipment and the correction evaluation amount of the data room equipment according to embodiment 1;

[0036] Figure 5 is a flow chart of the specific steps of the adjustment threshold determination according to embodiment 1;

[0037] Figure 6 is a framework diagram of a computer system according to embodiment 2. DETAILED DESCRIPTION

[0038] In order for those skilled in the technical field to better understand the technical solutions in the specification, the technical solutions in the specification will be clearly and completely described below in combination with the drawings in the specification. Obviously, the described embodiments are only part of the embodiments of the specification, not all. Based on the embodiments of the specification, all other embodiments obtained by those skilled in the art without creative labor should be within the scope of protection of the specification.

[0039] The applicant finds that the existing data room temperature and humidity threshold is often constructed by a fixed way, but too low humidity can cause the possibility of static electricity of PCB circuit board to increase, and too high temperature can also cause the dust probability of heat dissipation fan and PCB circuit board to increase, therefore, the application adjusts the dynamic temperature and humidity threshold by comprehensively considering the actual situation of the PCB circuit board of the server and the actual situation of the heat dissipation fan, and ensures the reliability of the temperature and humidity adjustment of the data room. Embodiment 1

[0040] To solve the above problems, according to one aspect of the application, as shown in Figure 1 According to one aspect of the application, a data room environment management method based on artificial intelligence is provided, which is characterized by comprising the following steps:

[0041] S11 divides the room equipment of the data room into general equipment and special equipment according to the type of the room equipment, the type of processed data and the data volume, and determines the temperature and humidity threshold of the data room according to the number of the general equipment and the special equipment and the area of the data room;

[0042] It should be noted that the type of the room equipment of the data room includes but is not limited to servers, switches, routers, hardware gateways and hardware firewalls.

[0043] Specifically, as shown in Figure 2 The room equipment of the data room is divided into general equipment and special equipment according to the type of the room equipment, the type of processed data and the data volume, and specifically comprises the following steps:

[0044] S21 obtains the type of the room equipment of the data room, and judges whether the type of the room equipment belongs to a specific equipment type, if yes, determines that the room equipment is special equipment, and if not, goes to step S22;

[0045] It should be noted that the specific equipment type includes but is not limited to hardware gateways and hardware firewalls.

[0046] S22 obtains the data type processed by the machine room equipment, and determines whether the data type needs to be processed by the data volume, if yes, goes to step S23, if no, goes to step S24;

[0047] Specifically, when the data type is a preset data type, it is meaningful to determine the data volume at this time, for example, user data, historical loan data and other data types that have a greater impact on credit approval processing.

[0048] S23 obtains the data volume processed by the machine room equipment within a set time, determines the maximum value and the average value of the data volume processed by the machine room equipment within a set time through the data volume processed by the machine room equipment within a set time, determines the data evaluation value of the machine room equipment in combination with the cumulative processing data volume of the machine room equipment, and determines whether the machine room equipment belongs to a special equipment through the data evaluation value of the machine room equipment, if yes, determines that the machine room equipment is a special equipment, if no, goes to step S24;

[0049] It should be noted that the data evaluation value reflects the data volume processed by the machine room equipment in multiple time dimensions, so the importance of the machine room equipment can be evaluated more macroscopically.

[0050] S24 determines the type evaluation value of the machine room equipment through the type of the machine room equipment, the data type processed, and the data evaluation value, and divides the machine room equipment into a general equipment and a special equipment through the type evaluation value.

[0051] It can be understood that the machine room equipment is divided into a general equipment and a special equipment through the type evaluation value, specifically including:

[0052] When the type evaluation value of the machine room equipment is greater than a preset type value, it is determined that the machine room equipment is a special equipment, if no, it is determined that the machine room equipment is a general equipment.

[0053] In the embodiment, the temperature and humidity threshold of the data room is determined through the number of the general equipment and the special equipment and the area of the data room, so that the determination of the temperature and humidity threshold not only considers the influence of the area of the data room on the adjustment rate, but also considers the difference in reliability requirements of the number of different types of equipment, ensuring the safety of temperature and humidity adjustment.

[0054] S12 determines the correction evaluation quantity of the machine room equipment by using an artificial intelligence model according to the number of cooling fans of the machine room equipment, the ventilation volume, the PCB area, and the operation time, and divides the machine room equipment into the concerned machine room equipment and other machine room equipment through the correction evaluation quantity, and determines whether the temperature and humidity threshold needs to be corrected through the number of the concerned machine room equipment and other machine room equipment and the correction evaluation quantity of the machine room equipment, if yes, goes to step S14, and if no, goes to step S13;

[0055] Specifically, as shown in Figure 3 The specific steps of the correction evaluation quantity determination are as follows:

[0056] S31 obtains the operation time of the machine room equipment, and determines whether the machine room equipment belongs to other machine room equipment through the operation time of the machine room equipment, if yes, determines the correction evaluation quantity of the machine room equipment by using an artificial intelligence model through the operation time of the machine room equipment, and if no, goes to the next step;

[0057] It can be understood that when the operation time of the machine room equipment is less than 2 years or other set value, the operation time is relatively short at this time, and the influence of the operation time on the cooling fan and the PCB is not considered temporarily.

[0058] S32 determines the cooling correction evaluation quantity of the machine room equipment through the number of cooling fans of the machine room equipment and the number of cooling fans of different ventilation volumes, and in combination with the ventilation volume of the machine room equipment;

[0059] S33 determines the electrostatic correction evaluation quantity of the machine room equipment through the number of PCBs of the machine room equipment, the number of PCBs of different area levels, and the PCB area of the machine room equipment;

[0060] S34 determines the correction evaluation quantity of the machine room equipment by using an artificial intelligence model in combination with the electrostatic correction evaluation quantity, the cooling correction evaluation quantity, the operation time of the machine room equipment, and the historical dust content of the data center.

[0061] Specifically, the value range of the correction evaluation quantity is between 0 and 1, wherein the greater the electrostatic correction evaluation quantity of the machine room equipment, the greater the cooling correction evaluation quantity, the longer the operation time of the machine room equipment, and the higher the historical dust content of the data center, the greater the correction evaluation quantity of the machine room equipment.

[0062] Specifically, as shown in Figure 4 whether the temperature and humidity threshold needs to be corrected through the number of the concerned machine room equipment and other machine room equipment and the correction evaluation quantity of the machine room equipment, specifically includes:

[0063] S41acquire the number of the concerned equipment room devices, and determine whether the temperature and humidity threshold needs to be corrected according to the number of the concerned equipment room devices, if yes, it is determined that the temperature and humidity threshold needs to be corrected, if no, it goes to step S42;

[0064] It can be understood that when the number of the concerned equipment room devices is large, the temperature and humidity threshold needs to be corrected at this time, so as to ensure the safety of the equipment operation.

[0065] S42acquire the number of the other equipment room devices, and determine whether the correction evaluation quantity needs to be determined according to the number of the other equipment room devices and the number of the concerned equipment room, if yes, it goes to step S43, if no, it goes to step S44;

[0066] S43determine whether the temperature and humidity threshold needs to be corrected according to the sum of the correction evaluation quantities of the equipment room devices, if yes, it is determined that the temperature and humidity threshold needs to be corrected, if no, it goes to step S44;

[0067] S44determine the temperature and humidity influence correction quantity of the equipment room devices according to the number of the other equipment room devices and the average of the correction evaluation quantities, the number of the concerned equipment room devices and the average of the correction evaluation quantities, and the sum of the correction evaluation quantities of the equipment room devices, and determine whether the temperature and humidity threshold needs to be corrected according to the temperature and humidity influence correction quantity.

[0068] In the embodiment, it is determined whether the temperature and humidity threshold needs to be corrected according to the number of the concerned equipment room devices and the other equipment room devices and the correction evaluation quantity of the equipment room devices, so as to realize the influence of the service life of the equipment room devices and the different service life on the heat dissipation efficiency and the static electricity generation probability, and meanwhile, the safety of the entire equipment room devices is considered, and the safety of the temperature and humidity adjustment is further ensured.

[0069] S13determine whether the temperature and humidity threshold needs to be corrected according to the dust content of the data equipment room, if yes, it goes to step S14, if no, the temperature and humidity of the data equipment room is controlled according to the temperature and humidity threshold;

[0070] It should be noted that when the dust content of the data equipment room is greater than the preset value, it is determined that the temperature and humidity threshold needs to be corrected.

[0071] S14correct the temperature and humidity threshold according to the dust content of the data equipment room, the number of the concerned equipment room devices and the other equipment room devices, and the correction evaluation quantity of the equipment room devices to obtain an adjustment threshold, and control the temperature and humidity of the data equipment room according to the adjustment threshold.

[0072] Specifically, as shown in Figure 5 The specific steps of determining the adjustment threshold value are as follows:

[0073] S51, the dust content of the data center is obtained, and it is determined whether the change amount of the dust content of the data center in the latest set time is greater than a set dust content value. If yes, the average value of the dust content of the data center in the latest set time is taken as the dust content selection amount. If no, the dust content of the data center is taken as the dust content selection amount.

[0074] S52, the dust content selection amount of the data center is obtained, and the dust content influence value of the data center is determined in combination with the number of general equipment and the number of special equipment of the data center.

[0075] S53, the number of the concerned data center equipment and the number of other data center equipment are obtained, and the equipment influence value of the data center is determined in combination with the sum of the correction evaluation amounts of the data center equipment.

[0076] S54, the equipment influence value and the dust content influence value of the data center are obtained, and the temperature and humidity correction amount of the data center is determined in combination with the area of the data center and the power of the artificial intelligence-based data center environment management device. The adjustment threshold value of the data center is determined by the temperature and humidity correction amount and the temperature and humidity threshold value.

[0077] It should be noted that the temperature and humidity control of the data center according to the adjustment threshold value specifically includes:

[0078] When the measured value of the temperature and humidity of the data center is not within the range of the adjustment threshold value, the temperature and humidity of the data center is controlled by the artificial intelligence-based data center environment management device.

[0079] Specifically, the temperature and humidity control device includes but is not limited to an air conditioner, a ventilation device, and a humidifier.

[0080] In this embodiment, the adjustment threshold value is obtained by correcting the temperature and humidity threshold value by the dust content of the data center, the number of the concerned data center equipment and other data center equipment, and the correction evaluation amount of the data center equipment. The influence of different dust content differences on the temperature and humidity adjustment threshold value is considered, and the influence of the safety state of the data center equipment caused by the running time on the temperature and humidity adjustment threshold value is also considered, so that the safety and reliability of the operation of the data center equipment are ensured. Embodiment 2

[0081] As shown in Figure 6As shown, the present application provides a computer system, comprising a memory and a processor connected in communication, and a computer program stored on the memory and capable of running on the processor, characterized in that: when the processor runs the computer program, it performs the above-mentioned artificial intelligence-based data machine room environment management method.

[0082] The above-mentioned artificial intelligence-based data machine room environment management method specifically includes:

[0083] Obtain the data type processed by the machine room equipment, obtain the data amount processed by the machine room equipment within a set time, and determine the maximum value and the average value of the data amount processed by the machine room equipment within a set time through the data amount processed by the machine room equipment within a set time, and determine the data evaluation amount of the machine room equipment in combination with the cumulative processing data amount of the machine room equipment, and when the data evaluation amount of the machine room equipment determines that the machine room equipment does not belong to special equipment, proceed to the next step;

[0084] Determine the type evaluation value of the machine room equipment through the type of the machine room equipment, the data type processed, and the data evaluation amount, and divide the machine room equipment into general equipment and special equipment through the type evaluation value, and determine the temperature and humidity threshold of the data machine room through the number of general equipment and special equipment and the area of the data machine room;

[0085] Obtain the number of other machine room equipment, and when the number of other machine room equipment and the number of concerned machine rooms determine that the determination of the correction evaluation amount is not needed, proceed to the next step;

[0086] When the sum of the correction evaluation amounts of the machine room equipment determines that the temperature and humidity threshold does not need to be corrected, proceed to the next step;

[0087] Determine the temperature and humidity influence correction amount of the machine room equipment through the number of other machine room equipment and the average of the correction evaluation amount, the number of concerned machine room equipment and the average of the correction evaluation amount, and the sum of the correction evaluation amounts of the machine room equipment, and when the temperature and humidity influence correction amount determines that the temperature and humidity threshold needs to be corrected, proceed to the next step;

[0088] Obtain the dust content of the data machine room, and determine whether the change amount of the dust content of the data machine room within the nearest set time is greater than the set value of the dust content, if yes, take the average of the dust content of the data machine room within the nearest set time as the dust content selection amount, if not, take the dust content of the data machine room as the dust content selection amount;

[0089] The dust content of the data machine room is selected, and the dust content influence value of the data machine room is determined in combination with the number of general equipment and the number of special equipment of the data machine room.

[0090] The equipment influence value of the data machine room is determined through the number of attention machine room equipment and the number of other machine room equipment of the data machine room, and in combination with the sum of the correction evaluation amount of the machine room equipment, the dust content influence value of the data machine room, and in combination with the area of the data machine room and the power of the data machine room environment management device based on artificial intelligence, the temperature and humidity correction amount of the data machine room is determined, and the adjustment threshold of the data machine room is determined through the temperature and humidity correction amount and the temperature and humidity threshold, and the temperature and humidity control of the data machine room is performed according to the adjustment threshold.

[0091] In addition, it should be noted that the determination of the correction evaluation amount of the machine room equipment includes: determining the heat dissipation correction evaluation amount of the machine room equipment through the number of heat dissipation fans of the machine room equipment and the number of heat dissipation fans of different ventilation amounts, and in combination with the ventilation amount of the machine room equipment; determining the electrostatic correction evaluation amount of the machine room equipment through the number of PCB boards of the machine room equipment, the number of PCB boards of different area levels and the PCB board area of the machine room equipment; determining the correction evaluation amount of the machine room equipment through the electrostatic correction evaluation amount and the heat dissipation correction evaluation amount of the machine room equipment, in combination with the running years of the machine room equipment and the historical dust content of the data machine room using an artificial intelligence model. Embodiment 3

[0092] The application provides a computer storage medium, which stores a computer program, and when the computer program is executed in a computer, the computer program makes the computer execute the artificial intelligence-based data machine room environment management method.

[0093] The artificial intelligence-based data machine room environment management method specifically includes:

[0094] S11 divides the machine room equipment of the data machine room into general equipment and special equipment through the type of the machine room equipment, the type of processed data and the data amount, and determines the temperature and humidity threshold of the data machine room through the number of general equipment and special equipment and the area of the data machine room;

[0095] S12, according to the number of heat dissipation fans of the machine room equipment, the ventilation volume, the PCB area, the running time, the AI model is used to determine the corrected evaluation quantity of the machine room equipment, and the machine room equipment is divided into the concerned machine room equipment and other machine room equipment through the corrected evaluation quantity, and whether the temperature and humidity threshold needs to be corrected is determined through the number of the concerned machine room equipment and other machine room equipment and the corrected evaluation quantity of the machine room equipment, if yes, step S14 is entered, and if no, step S13 is entered;

[0096] S13, whether the temperature and humidity threshold needs to be corrected is determined through the dust content of the data machine room, if yes, step S14 is entered, and if no, the temperature and humidity of the data machine room is controlled according to the temperature and humidity threshold;

[0097] S14, the temperature and humidity threshold is corrected to obtain an adjusted threshold through the dust content of the data machine room, the number of the concerned machine room equipment and other machine room equipment, and the corrected evaluation quantity of the machine room equipment, and the temperature and humidity of the data machine room is controlled according to the adjusted threshold.

[0098] Each of the embodiments in the specification is described in a progressive manner, and the same and similar parts between the embodiments can be referred to each other, and each embodiment mainly describes the difference from other embodiments. Especially, 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 related parts can be referred to the part of the method embodiment.

[0099] The above describes specific embodiments of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different than the order in the embodiments and still achieve the desired result. In addition, the processes depicted in the figures do not necessarily require the particular order shown or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing can be advantageous or required.

[0100] The above only describes one or more embodiments of the specification, and is not used to limit the specification. One or more embodiments of the specification can have various changes and variations for those skilled in the art. Any modification, equivalent replacement, improvement, etc. within the spirit and principle of one or more embodiments of the specification shall be included in the scope of the claims of the specification.

Claims

1. An artificial intelligence-based data machine room environment management method, characterized by, Specifically comprising: S11 divides the equipment in the data center into general equipment and special equipment according to the type of the equipment in the data center, the type of the data processed and the data volume, and determines the temperature and humidity threshold of the data center according to the number of the general equipment and the special equipment and the area of the data center; S12 determines the correction evaluation of the equipment in the data center according to the number of the cooling fan of the equipment in the data center, the ventilation volume, the area of the PCB and the running time, divides the equipment in the data center into the equipment to be concerned and other equipment according to the correction evaluation, determines whether the temperature and humidity threshold needs to be corrected according to the number of the equipment to be concerned and other equipment and the correction evaluation of the equipment in the data center, if yes, goes to step S14, and if no, goes to step S13; S13 determines whether the temperature and humidity threshold needs to be corrected according to the dust content of the data center, if yes, goes to step S14, and if no, controls the temperature and humidity of the data center according to the temperature and humidity threshold; S14 corrects the temperature and humidity threshold according to the dust content of the data center, the number of the equipment to be concerned and other equipment and the correction evaluation of the equipment in the data center to obtain an adjusted threshold, and controls the temperature and humidity of the data center according to the adjusted threshold; The specific steps of determining the adjusted threshold are as follows: S51 obtains the dust content of the data center, and determines whether the change of the dust content of the data center in the latest set time is greater than a set dust content, if yes, takes the average of the dust content of the data center in the latest set time as a selected dust content, and if no, takes the dust content of the data center as the selected dust content; S52 determines the dust content influence value of the data center according to the selected dust content of the data center and in combination with the number of the general equipment and the number of the special equipment of the data center; S53 determines the equipment influence value of the data center according to the number of the equipment to be concerned and other equipment of the data center and in combination with the sum of the correction evaluation of the equipment in the data center; S54 determines the temperature and humidity correction value of the data center according to the equipment influence value and the dust content influence value of the data center and in combination with the area of the data center and the power of the data center environment management device based on artificial intelligence, and determines the adjusted threshold of the data center according to the temperature and humidity correction value and the temperature and humidity threshold.

2. The artificial intelligence-based data machine room environment management method of claim 1, wherein, The type of the equipment in the data center includes but is not limited to servers, switches, routers, hardware gateways and hardware firewalls.

3. The artificial intelligence-based data machine room environment management method of claim 1, wherein, The equipment in the data center is divided into general equipment and special equipment according to the type of the equipment in the data center, the type of the data processed and the data volume, and specifically comprising: S21 obtains the type of the equipment in the data center, and determines whether the type of the equipment belongs to a specific equipment type, if yes, determines that the equipment is special equipment, and if no, goes to step S22; S22acquire the data type processed by the machine room equipment, and determine whether the data type needs to be processed by the data volume, if yes, go to step S23, if no, go to step S24; S23acquire the data volume processed by the machine room equipment within a set time, and determine the maximum value and the average value of the data volume processed by the machine room equipment within the set time by the data volume processed by the machine room equipment within the set time, determine the data evaluation value of the machine room equipment by the accumulated data volume of the machine room equipment, and determine whether the machine room equipment belongs to a special equipment by the data evaluation value of the machine room equipment, if yes, determine that the machine room equipment is a special equipment, if no, go to step S24; S24determine the type evaluation value of the machine room equipment by the type of the machine room equipment, the data type processed, and the data evaluation value, and divide the machine room equipment into a general equipment and a special equipment by the type evaluation value.

4. The artificial intelligence-based data machine room environment management method of claim 3, wherein, The specific equipment type includes but is not limited to a hardware gateway and a hardware firewall.

5. The artificial intelligence-based data machine room environment management method of claim 3, wherein, The machine room equipment is divided into a general equipment and a special equipment by the type evaluation value, and specifically includes: When the type evaluation value of the machine room equipment is greater than a preset type value, it is determined that the machine room equipment is a special equipment, if not, it is determined that the machine room equipment is a general equipment.

6. The artificial intelligence-based data machine room environment management method of claim 1, wherein, The specific steps of the correction evaluation value determination are: acquire the running life of the machine room equipment, and determine whether the machine room equipment belongs to other machine room equipment by the running life of the machine room equipment, if yes, determine the correction evaluation value of the machine room equipment by the running life of the machine room equipment by using an artificial intelligence model, if not, go to the next step; determine the heat dissipation correction evaluation value of the machine room equipment by the number of the heat dissipation fans of the machine room equipment and the number of the heat dissipation fans with different ventilation volumes, and combine the ventilation volume of the machine room equipment; determine the electrostatic correction evaluation value of the machine room equipment by the number of the PCB boards of the machine room equipment, the number of the PCB boards with different area levels, and the PCB board area of the machine room equipment; determine the correction evaluation value of the machine room equipment by the electrostatic correction evaluation value of the machine room equipment, the heat dissipation correction evaluation value, and the running life of the machine room equipment and the historical dust content of the data machine room by using an artificial intelligence model.

7. The artificial intelligence-based data machine room environment management method of claim 6, wherein, The value range of the correction evaluation value is between 0 and 1, wherein the greater the electrostatic correction evaluation value of the machine room equipment, the greater the heat dissipation correction evaluation value, the longer the running life of the machine room equipment, and the higher the historical dust content of the data machine room, the greater the correction evaluation value of the machine room equipment.

8. The artificial intelligence-based data machine room environment management method of claim 1, wherein, When the dust content of the data machine room is determined to be greater than a preset value, it is determined that the temperature and humidity threshold needs to be corrected.

9. A computer system comprising: The memory and the processor connected in communication, and the computer program stored on the memory and capable of running on the processor, characterized in that: when the processor runs the computer program, it executes the artificial intelligence-based data machine room environment management method of any one of claims 1-8.

10. A computer storage medium having stored thereon a computer program, which, when executed in a computer, causes the computer to perform the artificial intelligence based data machine room environment management method of any one of claims 1-8.

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