Machine room equipment state monitoring method and equipment based on Internet of Things, and medium

Abstract

The invention discloses a machine room equipment state monitoring method and device based on the Internet of Things and a medium. The method comprises the steps that an acquisition module acquires state data in a machine room; the data processing module preprocesses the state data, determines a type identifier corresponding to the preprocessed state data, determines a corresponding detection program according to the type identifier, and analyzes the state data according to the detection program to determine a dangerous signal in the machine room; the data processing module generates a positioning request according to the danger signal and starts the acquisition module according to the positioning request so as to enable the acquisition module to enter a positioning mode, and the dangerous position in the machine room is determined through the acquisition module in the positioning mode; and the early warning module obtains the danger signal and the danger position and carries out reminding according to the danger signal and the danger position. According to the system, the Internet of Things technology is adopted, automation and intellectualization of data acquisition, processing and early warning are achieved, and the stability and reliability of the system are improved.

Description

Technical Field

[0001] The present application relates to the technical field of Internet of Things, and in particular to a method, device and medium for monitoring the status of equipment in a computer room based on the Internet of Things. Background Art

[0002] With the rapid development of information technology, data centers and computer rooms, as the core infrastructure supporting the operation of various information systems, have become particularly important in terms of stability and reliability. However, a large number of servers, network equipment, cooling systems and other key equipment running in the computer room will inevitably experience various faults during long-term high-load operation, such as overheating, abnormal vibration, and aging of components. If these problems are not discovered and handled in a timely manner, they will seriously affect the normal operation of the computer room and even lead to data loss and system paralysis. Summary of the invention

[0003] In order to solve the above problems, the present application proposes a computer room equipment status monitoring method based on the Internet of Things, which is applied in a computer room equipment status monitoring system based on the Internet of Things. The system includes an acquisition module, a data processing module, and an early warning module. The method includes: the acquisition module obtains the status data in the computer room and sends the status data to a pre-set data processing module. The types of the status data include but are not limited to temperature, vibration, smoke, and noise; the data processing module pre-processes the status data, determines the type identifier corresponding to the pre-processed status data, determines the corresponding detection program according to the type identifier, and analyzes the status data according to the detection program to determine the danger signal in the computer room; the data processing module generates a positioning request according to the danger signal, and starts the acquisition module according to the positioning request, so that the acquisition module enters the positioning mode, and determines the dangerous position in the computer room through the acquisition module in the positioning mode; the early warning module obtains the danger signal and the dangerous position, and reminds according to the danger signal and the dangerous position.

[0004] In one example, the acquisition module includes a transmission device and multiple sensor groups, each sensor group consists of multiple sensors, wherein the types of the sensor groups include but are not limited to a temperature sensor group, a vibration sensor group, a smoke sensor group, and a noise sensor group, and the multiple sensor groups are arranged at different positions in the computer room; before the acquisition module obtains the status data in the computer room, the method also includes: initializing the acquisition module so that the acquisition module enters the acquisition mode, thereby acquiring data in the computer room through the acquisition module in the acquisition mode to obtain the status data.

[0005] In one example, data is collected in the computer room by the collection module in the collection mode, and the method further includes: determining a first sensor corresponding to the type, and starting multiple first sensors according to the collection mode; and collecting data in the computer room by multiple first sensors to obtain the status data.

[0006] In one example, after the acquisition module enters the positioning mode, the method further includes: starting all sensors of the sensor group according to the positioning mode, so as to locate the danger signal through all sensors, thereby obtaining the danger position.

[0007] In one example, determining the dangerous position in the computer room specifically includes: determining the data type corresponding to the dangerous signal, determining the corresponding sensor group according to the data type, and starting all sensors of the sensor group; synchronously collecting data according to the dangerous signal by all sensors to obtain a positioning signal group, the positioning signal group includes multiple positioning signals, and the positioning signal includes a signal emission time and a signal recovery time, and determining a distance matrix between all sensors and the emission position of the dangerous signal according to the positioning signal group; establishing a corresponding type of spatial coordinate system for the computer room according to the multiple sensor groups, and determining corresponding coordinate points in the corresponding type of spatial coordinate system according to the distance matrix, so as to determine the dangerous position according to the coordinate points.

[0008] In one example, the system also includes a remote controller, and the method also includes: determining a corresponding radiation range according to the type, and determining a dangerous range according to the dangerous position and the radiation range; determining location information of all equipment in the computer room, and determining whether there is any equipment in the dangerous range according to the location information; if there is a equipment in the dangerous range, powering off the equipment through the remote controller.

[0009] In one example, before analyzing the status data according to the detection procedure, the method also includes: acquiring historical status data of the computer room, dividing the historical status data according to the type to obtain multi-dimensional historical data; performing feature extraction on the multi-dimensional historical data to obtain a feature set, establishing a status monitoring model according to the feature set, and determining the detection procedure according to the status monitoring model.

[0010] In one example, the method also includes: splitting the state monitoring model according to the type to obtain multiple sub-state monitoring modules; determining the type identifier corresponding to the state data, and determining the corresponding single or multiple sub-state monitoring modules according to the type identifier; if the type identifier corresponds to a single sub-state monitoring module, determining the detection program according to the single sub-state monitoring module; if the type identifier corresponds to multiple sub-state monitoring modules, determining the detection program according to the multiple sub-state monitoring modules.

[0011] On the other hand, the present application also proposes a computer room equipment status monitoring device based on the Internet of Things, which is applied in a computer room equipment status monitoring system based on the Internet of Things. The system includes an acquisition module, a data processing module, and an early warning module. The device includes: at least one processor; and a memory connected to the at least one processor in communication; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the computer room equipment status monitoring device based on the Internet of Things can execute: the acquisition module obtains the status data in the computer room, and sends the status data to a pre-set data processing module. The types of the status data include but are not limited to Limited to temperature, vibration, smoke and noise; the data processing module pre-processes the status data, determines the type identification corresponding to the pre-processed status data, determines the corresponding detection program according to the type identification, and analyzes the status data according to the detection program to determine the danger signal in the computer room; the data processing module generates a positioning request according to the danger signal, and starts the acquisition module according to the positioning request, so that the acquisition module enters the positioning mode, and determines the dangerous position in the computer room through the acquisition module in the positioning mode; the early warning module obtains the danger signal and the dangerous position, and gives a reminder based on the danger signal and the dangerous position.

[0012] On the other hand, the present application also proposes a non-volatile computer storage medium storing computer executable instructions, which is applied in a computer room equipment status monitoring system based on the Internet of Things, wherein the system includes an acquisition module, a data processing module, and an early warning module, and the computer executable instructions are set as follows: the acquisition module acquires status data in the computer room and sends the status data to a pre-set data processing module, and the types of the status data include but are not limited to temperature, vibration, smoke, and noise; the data processing module pre-processes the status data, determines a type identifier corresponding to the pre-processed status data, determines a corresponding detection program according to the type identifier, and analyzes the status data according to the detection program to determine a danger signal in the computer room; the data processing module generates a positioning request according to the danger signal, and starts the acquisition module according to the positioning request, so that the acquisition module enters a positioning mode, and determines the dangerous position in the computer room through the acquisition module in the positioning mode; the early warning module acquires the danger signal and the dangerous position, and gives a reminder based on the danger signal and the dangerous position.

[0013] This application uses a multi-type sensor group to collect temperature, vibration, smoke, noise and other status data in the computer room in real time, so as to realize comprehensive monitoring of the computer room environment. Once a dangerous signal is found, the dangerous position can be quickly located, and the early warning module can be used to remind in time to shorten the emergency response time. The sensor group is used to synchronously collect data in the positioning mode, and the dangerous position is accurately calculated by the algorithm, which improves the accuracy and reliability of positioning. At the same time, the state monitoring model established by historical data can intelligently analyze the current state data and accurately identify potential dangers. The system can automatically determine the dangerous range according to the dangerous signal and the radiation range, and remotely control the equipment in the dangerous range to cut off the power, effectively preventing the accident from expanding and reducing losses. This application splits the state monitoring model into multiple sub-modules, flexibly selects the corresponding detection program according to the data type, and improves the data processing efficiency and the scalability of the system. The Internet of Things technology is used to realize the automation and intelligence of data collection, processing and early warning, reduce the need for manual intervention, and improve the stability and reliability of the system. At the same time, this application can be widely used in the status monitoring of various types of computer room equipment, with high practical value and promotion prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0015] Figure 1 A flowchart of a method for monitoring the status of equipment in a computer room based on the Internet of Things in an embodiment of the present application;

[0016] Figure 2 This is a schematic diagram of a computer room equipment status monitoring device based on the Internet of Things in an embodiment of the present application. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in combination with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0018] The technical solutions provided by various embodiments of the present application are described in detail below in conjunction with the accompanying drawings.

[0019] like Figure 1 As shown, in order to solve the above problems, an embodiment of the present application provides a computer room equipment status monitoring method based on the Internet of Things, which is applied in a computer room equipment status monitoring system based on the Internet of Things. The system includes a collection module, a data processing module, an early warning module, and a remote controller. The method includes:

[0020] S101, the acquisition module acquires status data in the computer room, and sends the status data to a preset data processing module, where types of the status data include but are not limited to temperature, vibration, smoke, and noise.

[0021] The acquisition module comprehensively and meticulously monitors the internal environment of the computer room, capturing and recording real-time status data including temperature, vibration, smoke concentration, noise, etc. The collected data is connected to the pre-configured data processing module through the transmission equipment, and the data is quickly screened, integrated and preliminarily analyzed, providing solid data support for subsequent fault warning, performance optimization and resource scheduling.

[0022] In one embodiment, the acquisition module is composed of a transmission device and a plurality of sensor groups. These sensor groups are numerous and are divided into multiple types according to their functions, including a temperature sensor group, a vibration sensor group, a smoke sensor group, and a noise sensor group. Each sensor group contains multiple sensors of the same type. Such a design not only ensures the comprehensiveness of data acquisition, but also improves the reliability and accuracy of the system. Before the data acquisition task is formally executed, the acquisition module is initialized. Through the initialization process, the acquisition module is set to the acquisition mode, which is the basic state for it to perform the data acquisition task. In the acquisition mode, the sensor group starts to continuously monitor various status data in the computer room, and transmits these data to the subsequent data processing module in real time through the transmission device, so as to provide timely and accurate information support for the operation and maintenance management of the computer room. Each sensor group is set at different positions in the computer room according to its type. For example, all smoke sensors of the smoke sensor group are installed on the ceiling of the computer room, and all noise sensors of the noise sensor group are installed on various walls and ceilings of the computer room.

[0023] In one embodiment, after the acquisition module is initialized and confirmed to enter the acquisition mode, the first sensor corresponding to the required monitoring type is determined. These first sensors are selected from their respective sensor groups, and they represent the main data collection points for their respective types of monitoring. Once the first sensors corresponding to each type are determined, the system will start them according to the settings of the acquisition mode to ensure that the sensors can accurately and stably start data collection. Subsequently, multiple first sensors will work together to perform basic data collection on the environment in the computer room. The temperature sensor will monitor the temperature changes in the computer room, the vibration sensor will capture the vibration of the equipment operation, the smoke sensor will detect potential smoke threats, and the noise sensor will evaluate the noise level in the computer room. The data collected by these sensors will jointly constitute the status data of the computer room, providing an important basis for subsequent data processing and analysis.

[0024] S102, the data processing module preprocesses the status data, determines a type identifier corresponding to the preprocessed status data, determines a corresponding detection program according to the type identifier, and analyzes the status data according to the detection program to determine a danger signal in the computer room.

[0025] After receiving the status data from the acquisition module, the data processing module will first perform a series of preprocessing operations to improve the accuracy and availability of the data, including data cleaning, data compression, data conversion, etc. After completing the preprocessing, the data processing module will determine the corresponding type identification for each set of status data. These type identifications correspond to the type of status data and provide reference information for subsequent data analysis. Next, the data processing module will select the corresponding detection program from the preset detection program library according to the type identification. These detection programs are designed for specific types of data, and the data processing module will conduct an in-depth analysis of the preprocessed status data according to the selected detection program. Determine whether there are dangerous signals in the computer room. Once a dangerous signal is detected, the data processing module will immediately trigger the alarm mechanism to notify relevant personnel to take timely measures to deal with it, thereby ensuring the safe and stable operation of the computer room.

[0026] In one embodiment, before analyzing the real-time collected status data according to the detection program, the system obtains the historical status data of the computer room, which is a record of the operation of the computer room in the past period of time, and contains rich information and risk analysis experience. The data processing module divides the historical data according to predetermined types, such as temperature, vibration, smoke, noise, etc., to form a historical data set of multiple dimensions. Feature extraction is performed on these multi-dimensional historical data. Feature extraction is an important step in data mining and machine learning, which extracts key information useful for subsequent analysis from the original data. Through feature extraction, a feature set can be obtained, which contains various types of key features that can describe the status of the computer room. Based on this feature set, the data processing module will establish a status monitoring model for real-time monitoring and evaluation of the status of the computer room. It can predict the operating status of the computer room based on the input status data and identify potential danger signals. In the process of building the model, the module will use historical data to train and verify the model to ensure its accuracy and reliability. After the status monitoring model is established, the data processing module determines the detection program based on this model. The detection program is a specific implementation of the model, which includes algorithms for analyzing status data, identifying danger signals, and rules for judging whether it is dangerous. During the real-time data collection process, the data processing module will process and analyze the status data according to the instructions of the detection program to promptly discover and respond to potential dangerous problems in the computer room.

[0027] In one embodiment, in the actual application of the state monitoring model, in order to improve the flexibility and efficiency of processing, the model is split according to the data type. Specifically, the data processing module splits the state monitoring model into multiple sub-state monitoring modules according to the type of state data. Each sub-state monitoring module focuses on processing a certain type of data and has corresponding analysis capabilities and detection rules. When the real-time state data is collected and preprocessed, the data processing module will first determine the type identification corresponding to these data.

[0028] The data processing module determines the corresponding single or multiple sub-status monitoring modules according to the type identifier. In some cases, the status data may contain one type of data, which corresponds to only one sub-status monitoring module. In this case, the module will directly call the detection program in the sub-module for analysis. In other cases, the status data may contain multiple types of data, and multiple sub-status monitoring modules are required to work together to comprehensively evaluate the status of the computer room. For the case where only a single sub-status monitoring module is corresponding, the data processing module will directly analyze the status data according to the detection program in the sub-module. These detection programs may include feature extraction methods, analysis algorithms, and danger signal identification rules for specific data types. For the case where multiple sub-status monitoring modules need to work together, the data processing module will first call the detection programs in each sub-module to perform a preliminary analysis of the status data. Then, it will conduct a comprehensive evaluation of these preliminary analysis results to determine the overall operating status and potential danger signals in the computer room. In this process, the module may use a pre-set fusion algorithm to integrate the output results of different sub-modules and make a final judgment and suggestion. In this way, the data processing module can process the status data in the computer room more efficiently and accurately identify potential danger signals, providing a strong guarantee for the safe and stable operation of the computer room.

[0029] S103, the data processing module generates a positioning request according to the danger signal, and starts the acquisition module according to the positioning request, so that the acquisition module enters the positioning mode, and determines the dangerous position in the computer room through the acquisition module in the positioning mode.

[0030] When the data processing module analyzes the existence of danger signals in the computer room through the status monitoring model, further action needs to be taken to determine the specific location of the danger. First, the data processing module generates a positioning request based on the danger signal. This positioning request contains key information such as the type of danger to be located, the possible scope of impact, and the priority. The data processing module starts the acquisition module based on this positioning request and puts it into positioning mode. The positioning mode requires the acquisition module to monitor the environmental changes in the computer room more carefully, and pay special attention to the specific location and related areas of the danger signal.

[0031] In positioning mode, the acquisition module uses all its internal sensor groups to collect data more intensively and accurately from the computer room. These sensors focus on monitoring areas where there may be dangers according to the instructions in the positioning request, and transmit the collected data to the data processing module in real time. This positioning process not only helps the computer room operation and maintenance personnel to quickly and accurately locate the source of danger, but also provides them with timely response guidance, so that they can quickly take measures to eliminate the danger and ensure the safe and stable operation of the computer room.

[0032] In one embodiment, after the acquisition module enters the positioning mode, all sensors of the sensor group are activated according to the positioning mode, so as to locate the danger signal through all sensors, thereby obtaining the danger position.

[0033] In one embodiment, in determining the specific processing flow of the danger signal in the machine room, the data type corresponding to the danger signal is first determined, such as temperature, vibration, smoke, noise, etc. According to the data type, the corresponding sensor group that needs to be activated can be determined, and these sensor groups are specially designed to detect this type of data. After the sensor group is determined, all sensors in the group are activated, and the danger signal is synchronously collected from multiple angles and dimensions to obtain more comprehensive and accurate data. Through synchronous collection, the positioning signal received by each sensor can be obtained, and these signals include key information such as signal emission time and signal recovery time. Next, based on these positioning signals, a positioning signal group can be constructed. Each positioning signal in the positioning signal group represents the association between the sensor and the location where the danger signal is emitted. By calculating the difference between the signal emission time and the recovery time, combined with the location information of the sensor, the distance between each sensor and the danger signal source can be preliminarily estimated, thereby establishing a distance matrix.

[0034] Based on the data provided by multiple sensor groups, a corresponding type of spatial coordinate system is established for the computer room. The type of spatial coordinate system depends on the specific layout of the computer room and the configuration of the sensor group. For example, if the layout of the computer room is relatively regular and the sensors are evenly distributed, a rectangular coordinate system can be used; if the layout of the computer room is complex, a polar coordinate system or other types of coordinate systems may be required. For example, if the data type is smoke, a plane coordinate system is established with the ceiling of the computer room, without considering the longitudinal height factor of the computer room; if the data type is noise, a three-dimensional coordinate system is established with the three-dimensional space of the computer room. After the spatial coordinate system is established, the corresponding coordinate points are determined in the coordinate system according to the distance matrix calculated previously. These coordinate points represent the estimates of the locations of the danger signals emitted by each sensor, and determine the most likely location of the danger signal, that is, the danger location. The entire process achieves rapid and accurate positioning of danger signals in the computer room through precise data collection, spatial modeling and data analysis, providing strong support for the safe operation and maintenance of the computer room.

[0035] S104: The early warning module obtains the danger signal and the danger position, and issues a warning based on the danger signal and the danger position.

[0036] After receiving the danger signal and its location, the early warning module immediately activates the reminder mechanism. The module conveys danger information to the computer room manager through various means such as sound and light alarms, text messages or emails. The reminder content not only includes the specific type and severity of the danger signal, but also clearly points out the specific location of the danger so that the manager can respond quickly and take appropriate measures. Such a timely early warning mechanism helps to ensure the safety of the computer room, reduce potential losses, and improve the overall operation and maintenance efficiency.

[0037] In one embodiment, during the process of processing the danger signal, the system determines its possible radiation range according to the type of danger signal. This radiation range is an area that may be affected by danger and is estimated based on historical data and professional knowledge. For example, after a smoke danger occurs in the computer room, the smoke will quickly spread to the surrounding area from the point where it is emitted. According to the diffusion speed of smoke under normal circumstances, the radiation range of the smoke danger is predetermined. Next, the system will query and determine the location information of all devices in the computer room. This location information is obtained through the network positioning function of the device itself, or it can be determined through the computer room layout map and the records in the equipment management system. Based on this location information, the system can determine which devices are located in the previously determined danger range. If it is found that a device is in the danger range, in order to avoid further damage or safety accidents, the system will immediately power off these devices through a remote controller. The remote controller is a device that can remotely control the switch status of the device, which allows the computer room manager to quickly perform necessary operations on the device without being on site. Through such a process, the system can quickly and effectively protect the safety of equipment and personnel in the computer room when a danger is detected.

[0038] like Figure 2 As shown, the embodiment of the present application also provides a computer room equipment status monitoring device based on the Internet of Things, which is applied in a computer room equipment status monitoring system based on the Internet of Things. The system includes a collection module, a data processing module, and an early warning module. The device includes:

[0039] at least one processor; and,

[0040] a memory communicatively connected to at least one processor; wherein,

[0041] The memory stores instructions that can be executed by at least one processor, and the instructions are executed by at least one processor to enable a computer room equipment status monitoring device based on the Internet of Things to execute:

[0042] The acquisition module acquires status data in the computer room and sends the status data to a pre-set data processing module. The types of the status data include but are not limited to temperature, vibration, smoke, and noise;

[0043] The data processing module preprocesses the status data, determines a type identifier corresponding to the preprocessed status data, determines a corresponding detection program according to the type identifier, and analyzes the status data according to the detection program to determine a danger signal in the computer room;

[0044] The data processing module generates a positioning request according to the danger signal, and starts the acquisition module according to the positioning request, so that the acquisition module enters a positioning mode, and determines the dangerous position in the computer room through the acquisition module in the positioning mode;

[0045] The early warning module obtains the danger signal and the danger position, and issues a warning according to the danger signal and the danger position.

[0046] The embodiment of the present application further provides a non-volatile computer storage medium storing computer executable instructions, which is applied in a computer room equipment status monitoring system based on the Internet of Things. The system includes a collection module, a data processing module, and an early warning module. The computer executable instructions are set as:

[0047] The acquisition module acquires status data in the computer room and sends the status data to a pre-set data processing module. The types of the status data include but are not limited to temperature, vibration, smoke, and noise;

[0048] The data processing module preprocesses the status data, determines a type identifier corresponding to the preprocessed status data, determines a corresponding detection program according to the type identifier, and analyzes the status data according to the detection program to determine a danger signal in the computer room;

[0049] The data processing module generates a positioning request according to the danger signal, and starts the acquisition module according to the positioning request, so that the acquisition module enters a positioning mode, and determines the dangerous position in the computer room through the acquisition module in the positioning mode;

[0050] The early warning module obtains the danger signal and the danger position, and issues a warning according to the danger signal and the danger position.

[0051] In the 1990s, improvements to a technology could be clearly distinguished as hardware improvements (for example, improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the method flow). However, with the development of technology, many improvements to the method flow today can be regarded as direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that an improvement in a method flow cannot be implemented using a hardware entity module. For example, a programmable logic device (PLD) (such as a field programmable gate array (FPGA)) is such an integrated circuit whose logical function is determined by the user's programming of the device. Designers can "integrate" a digital system on a PLD by programming it themselves, without having to ask a chip manufacturer to design and produce a dedicated integrated circuit chip. Moreover, nowadays, instead of manually making integrated circuit chips, this kind of programming is mostly implemented by "logic compiler" software, which is similar to the software compiler used when developing and writing programs, and the original code before compilation must also be written in a specific programming language, which is called hardware description language (HDL). There is not only one HDL, but many kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. The most commonly used ones are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also know that it is only necessary to program the method flow slightly in the above-mentioned hardware description languages ​​and program it into the integrated circuit, and then it is easy to obtain the hardware circuit that implements the logic method flow.

[0052] The controller can be implemented in any appropriate manner, for example, the controller can take the form of a microprocessor or processor and a computer-readable medium storing a computer-readable program code (such as software or firmware) that can be executed by the (micro)processor, a logic gate, a switch, an application-specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320. The memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art also know that in addition to implementing the controller in a purely computer-readable program code manner, the controller can be implemented in the form of a logic gate, a switch, an application-specific integrated circuit, a programmable logic controller, and an embedded microcontroller by logically programming the method steps. Therefore, this controller can be considered as a hardware component, and the devices included therein for implementing various functions can also be regarded as structures within the hardware component. Or even, the devices for implementing various functions can be regarded as both software modules for implementing the method and structures within the hardware component.

[0053] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0054] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing this specification, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0055] Each embodiment in this application 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 and 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 embodiments.

[0056] The devices and media provided in the embodiments of the present application correspond one-to-one to the methods. Therefore, the devices and media also have similar beneficial technical effects as the corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media will not be repeated here.

[0057] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0058] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0059] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0060] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0061] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0062] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0063] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0064] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0065] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for monitoring the status of equipment in a computer room based on the Internet of Things, characterized in that: Applied in a computer room equipment status monitoring system based on the Internet of Things, the system includes a collection module, a data processing module, and an early warning module, and the method includes: The acquisition module acquires status data in the computer room and sends the status data to a pre-set data processing module. The types of the status data include but are not limited to temperature, vibration, smoke, and noise; The data processing module preprocesses the status data, determines a type identifier corresponding to the preprocessed status data, determines a corresponding detection program according to the type identifier, and analyzes the status data according to the detection program to determine a danger signal in the computer room; The data processing module generates a positioning request according to the danger signal, and starts the acquisition module according to the positioning request, so that the acquisition module enters a positioning mode, and determines the dangerous position in the computer room through the acquisition module in the positioning mode; The early warning module obtains the danger signal and the danger position, and issues a warning according to the danger signal and the danger position.

2. The method according to claim 1, characterized in that The acquisition module includes a transmission device and multiple sensor groups, each sensor group is composed of multiple sensors, wherein the types of the sensor groups include but are not limited to a temperature sensor group, a vibration sensor group, a smoke sensor group, and a noise sensor group, and the multiple sensor groups are arranged at different locations in the machine room; Before the acquisition module acquires the status data in the computer room, the method further includes: The acquisition module is initialized to enable the acquisition module to enter an acquisition mode, thereby acquiring data in the computer room through the acquisition module in the acquisition mode to obtain the status data.

3. The method according to claim 2, characterized in that The data in the computer room is collected by the collection module in the collection mode, and the method further includes: Determine a first sensor corresponding to the type, and start a plurality of the first sensors according to the acquisition mode; Data is collected in the computer room through a plurality of the first sensors to obtain the status data.

4. The method according to claim 2, characterized in that: After the acquisition module enters the positioning mode, the method further includes: All sensors of the sensor group are activated according to the positioning mode, so as to locate the danger signal through all sensors, thereby obtaining the danger position.

5. The method according to claim 2, characterized in that: Determine the hazardous locations in the equipment room, including: Determine a data type corresponding to the danger signal, determine a corresponding sensor group according to the data type, and activate all sensors of the sensor group; Synchronously collecting data according to the danger signal through all the sensors to obtain a positioning signal group, wherein the positioning signal group includes multiple positioning signals, and the positioning signal includes a signal sending time and a signal recovery time, and determining a distance matrix between all the sensors and the sending position of the danger signal according to the positioning signal group; A space coordinate system of a corresponding type is established for the machine room according to the multiple sensor groups, and corresponding coordinate points are determined in the space coordinate system of the corresponding type according to the distance matrix, so as to determine the dangerous position according to the coordinate points.

6. The method according to claim 1, characterized in that The system further includes a remote controller, and the method further includes: Determine a corresponding radiation range according to the type, and determine a dangerous range according to the dangerous position and the radiation range; Determine the location information of all equipment in the computer room, and determine whether there is any equipment within the danger range according to the location information; If there is a device within the dangerous range, the device is powered off through the remote controller.

7. The method according to claim 1, characterized in that Before analyzing the status data according to the detection program, the method further includes: Acquire historical status data of the computer room, and divide the historical status data according to the type to obtain multi-dimensional historical data; Feature extraction is performed on the multi-dimensional historical data to obtain a feature set, and a state monitoring model is established according to the feature set, so as to determine the detection procedure according to the state monitoring model.

8. The method according to claim 7, characterized in that The method further comprises: Splitting the state monitoring model according to the type to obtain a plurality of sub-state monitoring modules; Determine a type identifier corresponding to the state data, and determine a corresponding single or multiple sub-state monitoring modules according to the type identifier; If the type identifier corresponds to a single sub-state monitoring module, determining the detection procedure according to the single sub-state monitoring module; If the type identifier corresponds to multiple sub-state monitoring modules, the detection program is determined according to the multiple sub-state monitoring modules.

9. A computer room equipment status monitoring device based on the Internet of Things, characterized in that: Applied in a computer room equipment status monitoring system based on the Internet of Things, the system includes a collection module, a data processing module, and an early warning module, and the equipment includes: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the device for monitoring the state of a computer room device based on the Internet of Things to execute: The acquisition module acquires status data in the computer room and sends the status data to a pre-set data processing module. The types of the status data include but are not limited to temperature, vibration, smoke, and noise; The data processing module preprocesses the status data, determines a type identifier corresponding to the preprocessed status data, determines a corresponding detection program according to the type identifier, and analyzes the status data according to the detection program to determine a danger signal in the computer room; The data processing module generates a positioning request according to the danger signal, and starts the acquisition module according to the positioning request, so that the acquisition module enters a positioning mode, and determines the dangerous position in the computer room through the acquisition module in the positioning mode; The early warning module obtains the danger signal and the danger position, and issues a warning according to the danger signal and the danger position.

10. A non-volatile computer storage medium storing computer executable instructions, characterized in that: The system is applied in a computer room equipment status monitoring system based on the Internet of Things, the system includes a collection module, a data processing module, and an early warning module, and the computer executable instructions are set as follows: The acquisition module acquires status data in the computer room and sends the status data to a pre-set data processing module. The types of the status data include but are not limited to temperature, vibration, smoke, and noise; The data processing module preprocesses the status data, determines a type identifier corresponding to the preprocessed status data, determines a corresponding detection program according to the type identifier, and analyzes the status data according to the detection program to determine a danger signal in the computer room; The data processing module generates a positioning request according to the danger signal, and starts the acquisition module according to the positioning request, so that the acquisition module enters a positioning mode, and determines the dangerous position in the computer room through the acquisition module in the positioning mode; The early warning module obtains the danger signal and the danger position, and issues a warning according to the danger signal and the danger position.

Images