CN117082097A - Intelligent machine room management method and system based on Internet of things - Google Patents
Intelligent machine room management method and system based on Internet of things Download PDFInfo
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- CN117082097A CN117082097A CN202311092473.4A CN202311092473A CN117082097A CN 117082097 A CN117082097 A CN 117082097A CN 202311092473 A CN202311092473 A CN 202311092473A CN 117082097 A CN117082097 A CN 117082097A
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- 238000007726 management method Methods 0.000 title claims description 24
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 153
- 238000009825 accumulation Methods 0.000 claims abstract description 106
- 238000012544 monitoring process Methods 0.000 claims abstract description 66
- 238000011156 evaluation Methods 0.000 claims abstract description 47
- 230000008859 change Effects 0.000 claims abstract description 36
- 238000012216 screening Methods 0.000 claims abstract description 24
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- 238000009434 installation Methods 0.000 claims description 2
- 238000012502 risk assessment Methods 0.000 claims description 2
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- H—ELECTRICITY
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Abstract
The invention provides a method and a system for intelligent machine room management based on the Internet of things, which belong to the technical field of the Internet of things and specifically comprise the following steps: the method comprises the steps of monitoring humidity in a machine room in real time through Internet of things equipment, determining the water accumulation depth of the machine room through an image analysis result of a monitoring device when the potential safety hazard exists in the machine room according to the humidity, determining the water accumulation hidden danger assessment value of the machine room by combining with change data of the water accumulation depth of the machine room, and screening the potential safety hazard machine room through the water accumulation hidden danger assessment value; and determining the importance evaluation value of the potential safety hazard machine room according to the type of the machine room, determining the machine room capable of being controlled by power failure through the importance evaluation value of the potential safety hazard machine room, and determining the power failure water depth of the server equipment through the type of the server equipment of the machine room capable of being controlled by power failure, the type of the machine room and the change data of the water accumulation depth, thereby further improving the operation safety of the server and the reliability of data transmission.
Description
Technical Field
The invention belongs to the technical field of the Internet of things, and particularly relates to a smart machine room management method and system based on the Internet of things.
Background
In order to realize real-time transmission of monitoring data of power equipment and scheduling data of power load in a power system, a data machine room is used as an intermediate node for data analysis and transmission, the operation safety and stability of the data machine room are important to the operation stability of the power system, in order to realize safety monitoring of the data machine room, in the prior art, the data machine room is often monitored by temperature or humidity, or by monitoring entering personnel, so that how to realize ponding monitoring of the data machine room, and differentiated management of server equipment of the data machine room differentiated according to the ponding monitoring condition of the data machine room becomes a technical problem to be solved.
In order to solve the technical problems, in the invention patent 'a method and equipment for detecting water leakage in a machine room', the water leakage transition information corresponding to the target water leakage point position is determined according to the water leakage coordinate time sequence, so that the water leakage danger degree of the target water leakage point position is monitored according to the water leakage transition information, the safety management of water leakage in the machine room is realized, but the following technical problems exist:
in the prior art, the determination of the outage time of the server equipment according to the water depth variation condition of the machine room is neglected, and specifically, when the depth of accumulated water in the machine room is not high, the server can still normally operate at the moment, so that the communication stability and the safety of the power system cannot be ensured if the outage is directly performed.
In the prior art, the determination of differentiated power-off control measures according to the type of the server of the machine room and the type of the machine room is ignored, and the requirement on the running time of the server which is in a key communication node or bears important functions such as dispatching instruction issuing is obviously higher, so that if the determination of differentiated power-off control measures cannot be performed, the communication stability and the safety of the power system can not be ensured.
Aiming at the technical problems, the invention provides a smart machine room management method and system based on the Internet of things.
Disclosure of Invention
In order to achieve the purpose of the invention, the invention adopts the following technical scheme:
according to one aspect of the invention, a smart machine room management method based on the Internet of things is provided.
An intelligent machine room management method based on the Internet of things is characterized by comprising the following steps:
the method comprises the steps of monitoring humidity in a machine room in real time through Internet of things equipment, and monitoring accumulated water through a monitoring device of the machine room when potential safety hazards exist in the machine room according to the humidity;
determining the water accumulation depth of the machine room through an image analysis result of the monitoring device, determining a water accumulation hidden danger evaluation value of the machine room by combining with change data of the water accumulation depth of the machine room, and entering the next step when the water accumulation hidden danger evaluation value cannot meet the requirement;
determining a monitoring area to which the machine room belongs according to the position of the machine room, judging whether the machine room with abnormal or missing real-time humidity monitoring data exists in the monitoring area, if so, determining a screening monitoring area based on water accumulation hidden danger assessment values, precipitation data and humidity monitoring results of different machine rooms in the monitoring area, screening the water accumulation hidden danger assessment values and the safety hidden danger machine room through monitoring devices of all the machine rooms in the screening monitoring area, and if not, screening the safety hidden danger machine room through the water accumulation hidden danger assessment values of the machine rooms in the monitoring area;
and determining an importance evaluation value of the potential safety hazard machine room according to the type of the machine room, determining the machine room capable of being controlled in a power-off manner according to the importance evaluation value of the potential safety hazard machine room, and determining the power-off water depth of the server equipment according to the type of the server equipment of the machine room capable of being controlled in the power-off manner, the type of the machine room and the change data of the water accumulation depth.
Whether water accumulation monitoring is carried out through the monitoring device of the machine room is determined according to the humidity, so that the problems of overlarge treatment efficiency and treatment pressure of the Internet of things equipment caused by frequent water accumulation monitoring are avoided, and the safety and reliability of operation of the machine room are further ensured.
The assessment value of the hidden ponding trouble of the machine room is determined through the ponding depth of the machine room and the change data of the ponding depth, so that the hidden ponding trouble of the machine room is accurately assessed according to the change conditions of the ponding depth and the ponding depth of the machine room, the influence of different ponding depths is considered, and the influence of the difference of the change rates of different depths is also considered.
The type of the server equipment of the machine room capable of being controlled by power failure, the type of the machine room and the change data of the water accumulation depth are used for determining the power failure water depth of the server equipment, so that accurate assessment of the power failure water depth of the server equipment from three aspects of the server, the machine room and the water accumulation is realized, the running safety and stability of the server and the machine room with higher importance are ensured, and meanwhile, differentiated power failure control of the server equipment is realized.
The further technical scheme is that the potential safety hazard exists in the machine room according to the humidity determination, and the method specifically comprises the following steps:
judging whether the humidity is greater than a preset humidity threshold, if so, determining that the machine room has potential safety hazards, and if not, entering the next step;
and determining the abnormal value of the humidity of the machine room through the humidity and the fluctuation amount of the humidity in unit time, and determining whether the hidden danger exists in the machine room according to the abnormal value of the humidity.
Further technical solutions include, but are not limited to, a rate of change of the water accumulation depth of the machine room, a rate of change of the water accumulation depth, and a maximum amount of change of the water accumulation depth in unit time.
The further technical scheme is that the method for determining the machine room capable of being controlled by power failure comprises the following steps:
determining the position of a communication node and the data transmission type of the potential safety hazard machine room according to the machine room type, judging the data transmission type of the potential safety hazard machine room to determine whether the service type of the potential safety hazard machine room is management service, if so, determining that the potential safety hazard machine room is a machine room capable of being controlled by power failure, and if not, entering the next step;
and determining the importance evaluation value of the potential safety hazard machine room according to the position of the communication node of the potential safety hazard machine room, and determining the machine room capable of being controlled by power failure according to the importance evaluation value of the potential safety hazard machine room.
In another aspect, the present invention provides a computer system comprising: a communicatively coupled memory and processor, and a computer program stored on the memory and capable of running on the processor, characterized by: and executing the intelligent machine room management method based on the Internet of things when the processor runs the computer program.
Additional features and advantages will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
In order to make the above objects, features and advantages of the present invention more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
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 attached drawings.
FIG. 1 is a flow chart of a method for intelligent machine room management based on the Internet of things;
FIG. 2 is a flow chart of a method of determining an assessment of water accumulation potential in a machine room;
FIG. 3 is a block diagram of a computer system.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments can be embodied in many forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art. The same reference numerals in the drawings denote the same or similar structures, and thus detailed descriptions thereof will be omitted.
The terms "a," "an," "the," and "said" are used to indicate the presence of one or more elements/components/etc.; the terms "comprising" and "having" are intended to be inclusive and mean that there may be additional elements/components/etc. in addition to the listed elements/components/etc.
Example 1
In order to solve the above problems, according to one aspect of the present invention, as shown in fig. 1, there is provided a smart machine room management method based on the internet of things, which is characterized in that the method specifically includes:
the method comprises the steps of monitoring humidity in a machine room in real time through Internet of things equipment, and monitoring accumulated water through a monitoring device of the machine room when potential safety hazards exist in the machine room according to the humidity;
determining the water accumulation depth of the machine room through an image analysis result of the monitoring device, determining a water accumulation hidden danger evaluation value of the machine room by combining with change data of the water accumulation depth of the machine room, and entering the next step when the water accumulation hidden danger evaluation value cannot meet the requirement;
determining a monitoring area to which the machine room belongs according to the position of the machine room, judging whether the machine room with abnormal or missing real-time humidity monitoring data exists in the monitoring area, if so, determining a screening monitoring area based on water accumulation hidden danger assessment values, precipitation data and humidity monitoring results of different machine rooms in the monitoring area, screening the water accumulation hidden danger assessment values and the safety hidden danger machine room through monitoring devices of all the machine rooms in the screening monitoring area, and if not, screening the safety hidden danger machine room through the water accumulation hidden danger assessment values of the machine rooms in the monitoring area;
and determining an importance evaluation value of the potential safety hazard machine room according to the type of the machine room, determining the machine room capable of being controlled in a power-off manner according to the importance evaluation value of the potential safety hazard machine room, and determining the power-off water depth of the server equipment according to the type of the server equipment of the machine room capable of being controlled in the power-off manner, the type of the machine room and the change data of the water accumulation depth.
Whether water accumulation monitoring is carried out through the monitoring device of the machine room is determined according to the humidity, so that the problems of overlarge treatment efficiency and treatment pressure of the Internet of things equipment caused by frequent water accumulation monitoring are avoided, and the safety and reliability of operation of the machine room are further ensured.
The assessment value of the hidden ponding trouble of the machine room is determined through the ponding depth of the machine room and the change data of the ponding depth, so that the hidden ponding trouble of the machine room is accurately assessed according to the change conditions of the ponding depth and the ponding depth of the machine room, the influence of different ponding depths is considered, and the influence of the difference of the change rates of different depths is also considered.
The type of the server equipment of the machine room capable of being controlled by power failure, the type of the machine room and the change data of the water accumulation depth are used for determining the power failure water depth of the server equipment, so that accurate assessment of the power failure water depth of the server equipment from three aspects of the server, the machine room and the water accumulation is realized, the running safety and stability of the server and the machine room with higher importance are ensured, and meanwhile, differentiated power failure control of the server equipment is realized.
It should be noted that, according to the humidity, it is determined that the potential safety hazard exists in the machine room, specifically including:
judging whether the humidity is greater than a preset humidity threshold, if so, determining that the machine room has potential safety hazards, and if not, entering the next step;
and determining the abnormal value of the humidity of the machine room through the humidity and the fluctuation amount of the humidity in unit time, and determining whether the hidden danger exists in the machine room according to the abnormal value of the humidity.
Specifically, the fluctuation data of the water accumulation depth of the machine room include, but are not limited to, the fluctuation rate of the water accumulation depth, the fluctuation condition of the fluctuation rate of the water accumulation depth and the maximum fluctuation amount of the water accumulation depth in unit time.
Specifically, as shown in fig. 2, the method for determining the evaluation value of the hidden water accumulation risk in the machine room is as follows:
s21, acquiring the water accumulation depth of the machine room, determining whether the machine room belongs to a potential safety hazard machine room or not according to the water accumulation depth of the machine room, if so, entering the next step, and if not, entering the step S24;
s22, determining the minimum value of the fluctuation rate of the water accumulation depth of the machine room according to the fluctuation data of the water accumulation depth of the machine room, determining whether the machine room belongs to a potential safety hazard machine room or not according to the minimum value of the fluctuation rate of the water accumulation depth of the machine room, if so, determining that the machine room belongs to the potential safety hazard machine room, and entering a step S24, otherwise, entering a step S23;
s23, determining the fluctuation speed of the water accumulation depth of the machine room, the maximum fluctuation amount and the minimum fluctuation amount of the water accumulation depth in unit time according to fluctuation data of the water accumulation depth of the machine room, determining the fluctuation hidden danger value of the machine room according to the fluctuation hidden danger value of the machine room by combining the fluctuation times of different fluctuation directions of the fluctuation speed of the water accumulation depth of the machine room, and determining whether the machine room belongs to the safety hidden danger machine room or not according to the fluctuation hidden danger value of the machine room, if not, determining the water accumulation hidden danger evaluation value of the machine room according to the water accumulation depth of the machine room, and if yes, entering step S24;
s24, determining the potential water accumulation risk assessment value of the machine room through the potential water accumulation depth and the potential water fluctuation value of the machine room.
Specifically, the value range of the evaluation value of the hidden danger of accumulated water in the machine room is between 0 and 1, and specifically, when the depth of accumulated water in the machine room is deeper, the larger the value of the hidden danger of fluctuation in the machine room is, the larger the evaluation value of the hidden danger of accumulated water in the machine room is.
It should be noted that, the monitoring area is determined according to the distribution condition of the machine rooms to be monitored, and the monitoring area is specifically divided by adopting a fixed number of machine rooms or a fixed area.
Further, when the humidity variation condition of the machine room or the deviation amount of the real-time humidity and the historical humidity of the machine room does not meet the requirement, determining that the real-time humidity monitoring data of the machine room is abnormal.
Specifically, the method for determining the screening monitoring area comprises the following steps:
s31, acquiring precipitation data in the monitoring area, determining whether a machine room in the monitoring area has a water accumulation risk according to the precipitation data, if so, entering a step S33, and if not, entering a step S32;
s32, determining a water accumulation high-risk machine room according to water accumulation hidden danger evaluation values of different machine rooms in the monitoring area, determining whether a water accumulation high-risk area exists in the monitoring area according to the position of the water accumulation high-risk machine room, if so, entering the next step, and if not, determining a screening monitoring area according to the position of the water accumulation high-risk machine room and a preset area;
s33, determining a precipitation monitoring area according to precipitation data in the monitoring area, determining a water accumulation high risk area according to the position of the water accumulation high risk machine room, and determining a screening basic monitoring area according to the precipitation monitoring area and the water accumulation high risk area;
s34, determining precipitation amount and the precipitation amount in the latest appointed time according to precipitation data of the screening basic monitoring area, determining the expansion area of the screening basic monitoring area according to the screening basic monitoring area and the expansion area of the screening basic monitoring area by combining the accumulated water hidden danger evaluation values of different machine rooms in the screening basic monitoring area, the number of accumulated water high-risk machine rooms and humidity monitoring results of different machine rooms.
When the expansion area of the screening basic monitoring area is larger than the set area threshold, the monitoring area is used as a screening monitoring area, and the water accumulation hidden danger assessment value and the screening of the potential safety hazard machine room are carried out through monitoring devices of all machine rooms in the monitoring area.
It can be understood that the method for determining the machine room capable of being controlled by power outage comprises the following steps:
determining the position of a communication node and the data transmission type of the potential safety hazard machine room according to the machine room type, judging the data transmission type of the potential safety hazard machine room to determine whether the service type of the potential safety hazard machine room is management service, if so, determining that the potential safety hazard machine room is a machine room capable of being controlled by power failure, and if not, entering the next step;
and determining the importance evaluation value of the potential safety hazard machine room according to the position of the communication node of the potential safety hazard machine room, and determining the machine room capable of being controlled by power failure according to the importance evaluation value of the potential safety hazard machine room.
Further, the method for determining the deepwater depth of outage of the server equipment comprises the following steps:
s41, determining the installation height of circuit equipment of the server equipment according to the type of the server equipment of the machine room capable of being controlled by power outage, and determining the recommended depth of the power outage water depth of the server equipment according to the type of the service data processed by the server equipment;
s42, determining an importance evaluation value of the machine room according to the type of the machine room, determining whether the recommended depth of the power-off water depth of the server equipment meets the requirement according to the importance evaluation value of the machine room, if so, entering the next step, and if not, entering the step S44;
s43, determining the average change rate of the water accumulation depth of the machine room and the maximum value of the change rate through change data of the water accumulation depth of the machine room, determining the change evaluation quantity of the water accumulation depth of the machine room by combining the times that the change rate of the water accumulation depth is larger than the set rate, determining whether the recommended depth of the power-off water depth of the server equipment meets the requirement or not through the change evaluation quantity of the water accumulation depth of the machine room, if yes, determining the power-off water depth of the server equipment through the recommended depth of the power-off water depth of the server equipment, and if no, entering the next step;
s44, determining a water cut-off depth correction amount according to the fluctuation evaluation value of the water accumulation depth of the machine room and the importance evaluation value of the machine room, and determining the water cut-off depth of the server equipment according to the water cut-off depth correction amount and the recommended depth of the water cut-off depth of the server equipment.
Further, the value of the water-break depth correction quantity is smaller than zero and is related to the variation evaluation value of the water accumulation depth of the machine room and the importance evaluation value of the machine room, wherein the larger the variation evaluation value of the water accumulation depth of the machine room is, the smaller the importance evaluation value of the machine room is, and the larger the water-break depth correction quantity is.
Example 2
As shown in fig. 3, the present invention provides a computer system comprising: a communicatively coupled memory and processor, and a computer program stored on the memory and capable of running on the processor, characterized by: and executing the intelligent machine room management method based on the Internet of things when the processor runs the computer program.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for apparatus, devices, non-volatile computer storage medium embodiments, the description is relatively simple, as it is substantially similar to method embodiments, with reference to the section of the method embodiments being relevant.
The foregoing describes specific embodiments of the present disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
The foregoing is merely one or more embodiments of the present description and is not intended to limit the present description. Various modifications and alterations to one or more embodiments of this description will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, or the like, which is within the spirit and principles of one or more embodiments of the present description, is intended to be included within the scope of the claims of the present description.
Claims (10)
1. An intelligent machine room management method based on the Internet of things is characterized by comprising the following steps:
the method comprises the steps of monitoring humidity in a machine room in real time through Internet of things equipment, and monitoring accumulated water through a monitoring device of the machine room when potential safety hazards exist in the machine room according to the humidity;
determining the water accumulation depth of the machine room through an image analysis result of the monitoring device, determining a water accumulation hidden danger evaluation value of the machine room by combining with change data of the water accumulation depth of the machine room, and entering the next step when the water accumulation hidden danger evaluation value cannot meet the requirement;
determining a monitoring area to which the machine room belongs according to the position of the machine room, judging whether the machine room with abnormal or missing real-time humidity monitoring data exists in the monitoring area, if so, determining a screening monitoring area based on water accumulation hidden danger assessment values, precipitation data and humidity monitoring results of different machine rooms in the monitoring area, screening the water accumulation hidden danger assessment values and the safety hidden danger machine room through monitoring devices of all the machine rooms in the screening monitoring area, and if not, screening the safety hidden danger machine room through the water accumulation hidden danger assessment values of the machine rooms in the monitoring area;
and determining an importance evaluation value of the potential safety hazard machine room according to the type of the machine room, determining the machine room capable of being controlled in a power-off manner according to the importance evaluation value of the potential safety hazard machine room, and determining the power-off water depth of the server equipment according to the type of the server equipment of the machine room capable of being controlled in the power-off manner, the type of the machine room and the change data of the water accumulation depth.
2. The intelligent machine room management method based on the internet of things of claim 1, wherein determining that the machine room has potential safety hazards according to the humidity specifically comprises:
judging whether the humidity is greater than a preset humidity threshold, if so, determining that the machine room has potential safety hazards, and if not, entering the next step;
and determining the abnormal value of the humidity of the machine room through the humidity and the fluctuation amount of the humidity in unit time, and determining whether the hidden danger exists in the machine room according to the abnormal value of the humidity.
3. The intelligent machine room management method based on the internet of things as set forth in claim 1, wherein the change data of the water accumulation depth of the machine room includes, but is not limited to, a change rate of the water accumulation depth, a change condition of the change rate of the water accumulation depth, and a maximum change amount of the water accumulation depth in a unit time.
4. The intelligent machine room management method based on the internet of things as set forth in claim 1, wherein the method for determining the assessment value of the hidden water accumulation risk of the machine room is as follows:
s21, acquiring the water accumulation depth of the machine room, determining whether the machine room belongs to a potential safety hazard machine room or not according to the water accumulation depth of the machine room, if so, entering the next step, and if not, entering the step S24;
s22, determining the minimum value of the fluctuation rate of the water accumulation depth of the machine room according to the fluctuation data of the water accumulation depth of the machine room, determining whether the machine room belongs to a potential safety hazard machine room or not according to the minimum value of the fluctuation rate of the water accumulation depth of the machine room, if so, determining that the machine room belongs to the potential safety hazard machine room, and entering a step S24, otherwise, entering a step S23;
s23, determining the fluctuation speed of the water accumulation depth of the machine room, the maximum fluctuation amount and the minimum fluctuation amount of the water accumulation depth in unit time according to fluctuation data of the water accumulation depth of the machine room, determining the fluctuation hidden danger value of the machine room according to the fluctuation hidden danger value of the machine room by combining the fluctuation times of different fluctuation directions of the fluctuation speed of the water accumulation depth of the machine room, and determining whether the machine room belongs to the safety hidden danger machine room or not according to the fluctuation hidden danger value of the machine room, if not, determining the water accumulation hidden danger evaluation value of the machine room according to the water accumulation depth of the machine room, and if yes, entering step S24;
s24, determining the potential water accumulation risk assessment value of the machine room through the potential water accumulation depth and the potential water fluctuation value of the machine room.
5. The intelligent machine room management method based on the internet of things as set forth in claim 4, wherein the evaluation value of the hidden danger of water accumulation in the machine room ranges from 0 to 1, and specifically, when the depth of water accumulation in the machine room is deeper, the larger the hidden danger value of fluctuation in the machine room is, the larger the hidden danger evaluation value of water accumulation in the machine room is.
6. The intelligent machine room management method based on the internet of things according to claim 1, wherein the monitoring area is determined according to the distribution condition of the machine rooms to be monitored, and the monitoring area is divided by adopting a fixed number of machine rooms or a fixed area.
7. The intelligent machine room management method based on the internet of things as set forth in claim 1, wherein when the humidity variation condition of the machine room or the deviation amount of the real-time humidity and the historical humidity of the machine room does not meet the requirement, determining that the real-time humidity monitoring data of the machine room is abnormal.
8. The intelligent machine room management method based on the internet of things as set forth in claim 1, wherein the method for determining the depth of the power-off water depth of the server device is as follows:
s41, determining the installation height of circuit equipment of the server equipment according to the type of the server equipment of the machine room capable of being controlled by power outage, and determining the recommended depth of the power outage water depth of the server equipment according to the type of the service data processed by the server equipment;
s42, determining an importance evaluation value of the machine room according to the type of the machine room, determining whether the recommended depth of the power-off water depth of the server equipment meets the requirement according to the importance evaluation value of the machine room, if so, entering the next step, and if not, entering the step S44;
s43, determining the average change rate of the water accumulation depth of the machine room and the maximum value of the change rate through change data of the water accumulation depth of the machine room, determining the change evaluation quantity of the water accumulation depth of the machine room by combining the times that the change rate of the water accumulation depth is larger than the set rate, determining whether the recommended depth of the power-off water depth of the server equipment meets the requirement or not through the change evaluation quantity of the water accumulation depth of the machine room, if yes, determining the power-off water depth of the server equipment through the recommended depth of the power-off water depth of the server equipment, and if no, entering the next step;
s44, determining a water cut-off depth correction amount according to the fluctuation evaluation value of the water accumulation depth of the machine room and the importance evaluation value of the machine room, and determining the water cut-off depth of the server equipment according to the water cut-off depth correction amount and the recommended depth of the water cut-off depth of the server equipment.
9. The intelligent machine room management method based on the internet of things according to claim 1, wherein the value of the water-break depth correction amount is smaller than zero and is related to the evaluation value of the fluctuation of the water accumulation depth of the machine room and the evaluation value of the importance of the machine room, and the larger the evaluation value of the fluctuation of the water accumulation depth of the machine room is, the smaller the evaluation value of the importance of the machine room is, the larger the water-break depth correction amount is.
10. A computer system, comprising: a communicatively coupled memory and processor, and a computer program stored on the memory and capable of running on the processor, characterized by: the intelligent machine room management method based on the internet of things according to any one of claims 1-9 is executed when the processor runs the computer program.
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| CN202311092473.4A Pending CN117082097A (en) | 2023-08-29 | 2023-08-29 | Intelligent machine room management method and system based on Internet of things |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117433590A (en) * | 2023-12-20 | 2024-01-23 | 杭银消费金融股份有限公司 | Method and device for monitoring environmental temperature and humidity of data center machine room |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117433590A (en) * | 2023-12-20 | 2024-01-23 | 杭银消费金融股份有限公司 | Method and device for monitoring environmental temperature and humidity of data center machine room |
| CN117433590B (en) * | 2023-12-20 | 2024-03-01 | 杭银消费金融股份有限公司 | Method and device for monitoring environmental temperature and humidity of data center machine room |
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