Power and environment monitoring method for data center or service center

Abstract

The invention provides a power and environment monitoring method for a data center or a service center. The power and environment monitoring method is applied to a power and environment monitoring system comprising a data acquisition system, a cloud data analysis system and an alarm system. The data acquisition system comprises an environment data acquisition module, a data preprocessing module and a data submission and network connection module; the alarm system comprises a local alarm system and a cloud alarm system. The data acquisition system integrates the functions of environmental data acquisition, data preprocessing and data submission at the same time, the acquired environmental data can be preprocessed in real time and then submitted to the cloud data analysis system, and the cloud data analysis system receives the environmental data from a monitored data center or a service center in real time. And data processing and analysis are carried out, so that a user can query environment data and alarm records of the current data center or service center in the cloud data analysis system. According to the invention, the alarm notification timeliness can be effectively improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of environmental monitoring, and in particular relates to a dynamic environment monitoring method for a data center or a service center. Background Art

[0002] Data centers or service centers are key physical infrastructure designed for storing and managing data. They contain IT infrastructure such as servers and storage devices, providing solid hardware support for data management. The core function of a data center or service center is to centrally store and uniformly manage enterprise data, so they have strict requirements on environmental conditions such as temperature and humidity to ensure the normal operation of equipment and the safe management of data.

[0003] Almost all modern enterprises and institutions have their own data centers or service centers, or choose to rent external data centers or service centers. If resources are sufficient, large enterprises and institutions usually tend to build and manage their own internal data centers or service centers.

[0004] In industries such as education, finance, telecommunications, retail, and social networking services, a large amount of data generated needs to be processed and analyzed every day, and these functions are highly dependent on data centers or service centers to maintain their normal operations. Without the support of a stable and secure data center or service center, these companies will not be able to quickly and securely access data or provide services to users, which may eventually lead to customer loss and reduced profits. Therefore, the security of data centers or service centers is not only a focus of business owners, but also closely related to consumers who rely on these services.

[0005] In the rapidly developing Internet era, we are increasingly relying on data centers or service centers to ensure the normal operation of our lives. Currently, more and more companies are migrating their professional applications to data centers or service centers to minimize the cost of operating internal servers. Therefore, the security of data centers or service centers is crucial for both enterprises and users.

[0006] During the continuous operation of a data center or service center, especially when operating 24 / 7, a lot of heat is generated, which can cause serious damage to equipment. If equipment fails due to overheating without any warning, it can have a serious negative impact on business operations.

[0007] Therefore, it is very important to monitor environmental factors such as temperature. Through an effective environmental monitoring and alarm system, the operating efficiency of the data center or service center can be improved, and downtime can be reduced, business interruptions can be prevented, and performance can be optimized.

[0008] The mainstream environmental monitoring methods currently on the market usually consist of two parts: a collection terminal and a monitoring center. The collection terminal is mainly responsible for collecting environmental data and transmitting it to the monitoring center through the central node. The monitoring center uses an RJ45 wired module or an infrared module as a receiver to receive the environmental data transmitted by the central node to achieve real-time display of environmental data and other monitoring functions. However, this monitoring solution requires the central node to completely extract the data from all collection terminals in the current environment and then submit it to the monitoring center. In this mode, it will inevitably take a certain amount of time to collect and integrate the current environmental data, and the timeliness of alarm notifications will be greatly reduced. Summary of the invention

[0009] In view of the defects in the prior art, the present invention provides a dynamic environment monitoring method for a data center or a service center, which can effectively solve the above problems.

[0010] The technical solution adopted by the present invention is as follows:

[0011] The present invention provides a dynamic environment monitoring method for a data center or a service center, which is applied to a dynamic environment monitoring system including a data acquisition system, a cloud data analysis system and an alarm system; wherein the data acquisition system includes an environmental data acquisition module, a data preprocessing module and a data submission and network connection module; the alarm system includes a local alarm system and a cloud alarm system;

[0012] The method comprises the following steps:

[0013] Step S1, the data acquisition system uses the environmental data acquisition module to perform real-time environmental monitoring on the monitored data center or service center, and acquires raw environmental data in real time;

[0014] Step S2, the data preprocessing module converts the raw environmental data into recognizable environmental data in real time, and then preliminarily determines whether the recognizable environmental data is obviously abnormal data. If so, the environmental data is abandoned and the process returns to step S1; if not, step S3 is executed;

[0015] Step S3, the data preprocessing module determines whether the environmental data reaches the system preset alarm value pushed by the cloud data analysis system. If so, the local alarm system is immediately notified to start the local alarm mechanism, and then step S4 is executed; if not, step S4 is directly executed;

[0016] Step S4, the data preprocessing module performs a first standardization process on the environmental data, converts the environmental data into a unified format, integrates the environmental data into a same data set with the same timestamp, and submits the data to the data submission and network connection module;

[0017] Step S5, the data submission and network connection module performs a second standardization process on the environmental data in the data set, converts it into a standard data format, and then packages the data to obtain a data packet; and uploads the data packet to the cloud data analysis system;

[0018] Step S6, the cloud data analysis system performs data analysis on the received data packet to determine whether the monitored data center or service center is currently abnormal. If abnormal, the cloud alarm system is notified to start the cloud alarm mechanism; at the same time, based on the received data packet, a new system preset alarm value is updated and generated, and pushed to the data preprocessing module of the data acquisition system.

[0019] Preferably, the original environmental data is real-time monitoring environmental data collected by various sensors in real time, including temperature, humidity and air pressure.

[0020] Preferably, the data acquisition system is configured with an acquisition module connected to various sensors via a serial port or an I2C interface; the data acquisition system collects environmental data in a scheduled or on-demand manner.

[0021] Preferably, step S6 specifically comprises:

[0022] Step S6.1, the cloud data analysis system performs preliminary formatting and verification on the received data packet to ensure the integrity and accuracy of the data packet;

[0023] Step S6.2, the cloud data analysis system reads each piece of environmental data in the data packet, and executes step S6.3 for each piece of environmental data read;

[0024] Step S6.3, the cloud data analysis system determines whether the environmental data is greater than the system preset alarm value, if yes, execute step S6.4; if no, directly execute step S6.5;

[0025] Step S6.4, triggering the cloud alarm system to send an alarm notification to the management personnel, so that the management personnel can verify whether the environmental data is consistent with the real event, and determine whether the notification of the management personnel confirming the event and submitting the environmental data is received within the set time. If yes, execute step S6.5; if not, return to step S6.2 and continue to read the next environmental data in the data packet;

[0026] Step S6.5, storing the environmental data in a temporary data storage repository, and determining whether all environmental data in the data packet have been read and analyzed, if yes, executing step S6.6; if no, returning to step S6.2;

[0027] Step S6.6, the cloud data analysis system predefines a designated time t for determining whether the preset alarm value of the system is updated every day, and determines whether the current time is the designated time t. If not, return to step S6.1 and continue to process and analyze the next received data packet; if yes, execute step S6.7;

[0028] Step S6.7, the cloud data analysis system extracts all environmental data of the previous day from the temporary data repository, and uses a truncated mean algorithm to calculate the daily average of all environmental data of the previous day, and stores it in a daily average database;

[0029] Step S6.8, the cloud data analysis system reads the daily average values ​​of the most recent 7 days from the daily average database, calculates the average of the 7 daily average values ​​read, obtains the 7-day average data, and determines whether the 7-day average data has changed compared with the system preset alarm value. If there is no change, return to step S6.6; if there is a change, use the 7-day average data to update the system preset alarm value, and send the updated system preset alarm value to the data acquisition system, and then return to step S6.6.

[0030] Preferably, the designated time t is a time close to midnight every day.

[0031] The dynamic environment monitoring method for a data center or service center provided by the present invention has the following advantages:

[0032] The present invention provides a dynamic environment monitoring method for a data center or service center. The data acquisition system integrates environmental data acquisition, data preprocessing and data submission functions at the same time. The collected environmental data can be submitted to the cloud data analysis system in real time after data preprocessing. The cloud data analysis system receives environmental data from the monitored data center or service center in real time, and performs data processing and analysis. Users can query the environmental data and alarm records of the current data center or service center in the cloud data analysis system. The present invention can effectively improve the timeliness of alarm notification. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 A schematic diagram of the working process of a data acquisition system in a dynamic environment monitoring method for a data center or a service center provided by the present invention;

[0034] Figure 2 A schematic diagram of the workflow of a cloud data analysis system in a dynamic environment monitoring method for a data center or service center provided by the present invention. DETAILED DESCRIPTION

[0035] In order to make the technical problems, technical solutions and beneficial effects solved by the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0036] The present invention provides a dynamic environment monitoring method for a data center or service center. The data acquisition system integrates environmental data acquisition, data preprocessing and data submission functions at the same time. The collected environmental data can be submitted to the cloud data analysis system in real time after data preprocessing. The cloud data analysis system receives environmental data from the monitored data center or service center in real time, and performs data processing and analysis. Users can query the environmental data and alarm records of the current data center or service center in the cloud data analysis system. The present invention can effectively improve the timeliness of alarm notification.

[0037] The present invention provides a dynamic environment monitoring method for a data center or a service center, which is applied to a dynamic environment monitoring system including a data acquisition system, a cloud data analysis system and an alarm system; wherein the data acquisition system includes an environmental data acquisition module, a data preprocessing module and a data submission and network connection module; the alarm system includes a local alarm system and a cloud alarm system;

[0038] like Figure 1 and Figure 2 As shown, the method comprises the following steps:

[0039] Step S1, the data acquisition system uses the environmental data acquisition module to perform real-time environmental monitoring on the monitored data center or service center, and acquires raw environmental data in real time;

[0040] The data acquisition system is configured with an acquisition module connected to various sensors via a serial port or an I2C interface; the data acquisition system collects environmental data in a scheduled or on-demand manner. The raw environmental data is real-time monitoring environmental data collected by various sensors in real time, including but not limited to temperature, humidity and air pressure.

[0041] Step S2, the data preprocessing module converts the raw environmental data into recognizable environmental data in real time, and then preliminarily determines whether the recognizable environmental data is obviously abnormal data. If so, the environmental data is abandoned and the process returns to step S1; if not, step S3 is executed;

[0042] Step S3, the data preprocessing module determines whether the environmental data reaches the system preset alarm value pushed by the cloud data analysis system. If so, the local alarm system is immediately notified to start the local alarm mechanism, and then step S4 is executed; if not, step S4 is directly executed;

[0043] Step S4, the data preprocessing module performs a first standardization process on the environmental data, converts the environmental data into a unified format, integrates the environmental data into a same data set with the same timestamp, and submits the data to the data submission and network connection module;

[0044] Step S5, the data submission and network connection module performs a second standardization process on the environmental data in the data set, converts it into a standard data format, and then packages the data to obtain a data packet; and uploads the data packet to the cloud data analysis system;

[0045] It can be seen that the data acquisition system of the present invention integrates the environmental data acquisition module, the data preprocessing module and the data submission and network connection module at the same time, and adopts the acquisition, data preprocessing and sending integrated mode to perform data acquisition, data preprocessing and data push. The data acquisition system can adopt the arm architecture and is equipped with an independent data transmission function. It can use all types of Internet of Things cards currently on the market for networking, and the data acquisition system is compatible with wired / Wi-Fi networking methods at the same time, which is convenient for users to build a local offline alarm system. The advantages of using the arm architecture are: the environmental data acquisition module can collect a variety of different sensors to collect different environmental data; the environmental data is pre-processed and packaged by the data preprocessing module, and submitted to the cloud through the built-in data submission and network connection module for data monitoring and alarm.

[0046] As an embodiment, the data acquisition system has the following characteristics:

[0047] The data acquisition system is responsible for collecting environmental data. The system monitors environmental parameters in real time through various sensors, such as temperature, humidity, air pressure, etc. The data acquisition system supports Wi-Fi and wired connection to the network to adapt to different deployment requirements. Before data transmission, the data acquisition system uses the data preprocessing module to preliminarily process and filter the collected environmental data, filter out extremely obvious abnormal values, ensure the accuracy of environmental data, reduce the burden on the cloud data analysis system and improve data quality; after filtering out extremely obvious abnormal values, based on the system preset alarm value pushed by the cloud data analysis system, once abnormal data reaching the system preset alarm value is detected during the data preprocessing process, the local alarm system is immediately notified and the local alarm mechanism is activated for timely response.

[0048] Specifically, the functions of the environmental data acquisition module, data preprocessing module, and data submission and network connection module are as follows:

[0049] Environmental data collection module:

[0050] The environmental data acquisition module completes environmental data acquisition by connecting to highly sensitive sensors. The sensors include humidity, temperature and other sensors. The environmental data acquisition module connects to the sensors through the serial port or I2C interface to collect environmental data. The environmental data acquisition module is carried out in a scheduled or on-demand manner to ensure timely acquisition of environmental data. Scheduled acquisition is suitable for stable monitoring, and on-demand acquisition needs to be carried out under specific conditions to improve the flexibility of environmental data acquisition.

[0051] Data preprocessing module:

[0052] The collected environmental data may contain noise or obvious extreme outliers. Therefore, the environmental data is cleaned (data correction and data filtering) to improve data quality. Different sensors may use different units and formats for data collection. In the preprocessing stage, the data preprocessing module converts each environmental data into a unified format for further analysis. The environmental data comes from multiple sensors and has different but similar timestamps. The timestamps are not exactly the same. The data preprocessing module unifies all environmental data collected in the same batch into one data set. The data set is uniformly assigned a unique timestamp to ensure the synchronization of each environmental data in time.

[0053] Data submission and network connection module:

[0054] The data submission and network connection modules play a key role in data collection and analysis, ensuring that environmental data is smoothly transmitted from the data collection system to the cloud data analysis system for processing and storage.

[0055] During the data packaging process, the data submission and network connection module will standardize the environmental data preprocessed by the data preprocessing module and convert it into standard data formats, such as JSON, XML, etc., to reduce the time and bandwidth consumption of data on the OSI transmission layer. The data submission and network connection module uses Wi-Fi wireless connection and can upload the packaged data to the cloud data analysis system through transmission protocols such as http / https, MQTT, etc. as needed.

[0056] The data submission and network connection modules of the data acquisition system are the basis for ensuring the normal operation of the monitoring system. Data submission needs to ensure the accuracy, integrity and security of the data, while network connection needs to ensure the reliability and efficiency of data transmission. Through careful design and implementation of these two aspects, the performance and stability of the data center or service center monitoring system can be improved, providing reliable support for data analysis and decision-making.

[0057] Step S6, the cloud data analysis system performs data analysis on the received data packet to determine whether the monitored data center or service center is currently abnormal. If abnormal, the cloud alarm system is notified to start the cloud alarm mechanism; at the same time, based on the received data packet, a new system preset alarm value is updated and generated, and pushed to the data preprocessing module of the data acquisition system.

[0058] Step S6 is specifically as follows:

[0059] Step S6.1, the cloud data analysis system performs preliminary formatting and verification on the received data packet to ensure the integrity and accuracy of the data packet;

[0060] Step S6.2, the cloud data analysis system reads each piece of environmental data in the data packet, and executes step S6.3 for each piece of environmental data read;

[0061] Step S6.3, the cloud data analysis system determines whether the environmental data is greater than the system preset alarm value, if yes, execute step S6.4; if no, directly execute step S6.5;

[0062] Step S6.4, triggering the cloud alarm system to send an alarm notification to the management personnel, so that the management personnel can verify whether the environmental data is consistent with the real event, and determine whether the notification of the management personnel confirming the event and submitting the environmental data is received within the set time. If yes, execute step S6.5; if not, return to step S6.2 and continue to read the next environmental data in the data packet;

[0063] In this step, the triggering method for executing the cloud alarm system can be SMS, email, in-application, alarm device, etc. The cloud alarm system sends an alarm notification to the management personnel, including abnormal data details, such as abnormal time, abnormal corresponding computer room number, abnormal type, current situation, etc. After receiving the alarm notification from the cloud alarm system, the management personnel need to verify whether the environmental data is consistent with the real event, for example, whether the relevant abnormal event has actually occurred in the corresponding computer room. Through this operation, the authenticity of the environmental data at this time can be ensured, rather than the environmental data generated by the computer room performance test, etc., which improves the accuracy and reliability of the subsequent update of the preset alarm value of the system.

[0064] Step S6.5, storing the environmental data in a temporary data storage repository, and determining whether all environmental data in the data packet have been read and analyzed, if yes, executing step S6.6; if no, returning to step S6.2;

[0065] Step S6.6, the cloud data analysis system predefines a designated time t for determining whether the preset alarm value of the system is updated every day, the designated time t is a time close to midnight every day, for example, the designated time t is 1 a.m. every day, and determines whether the current time is the designated time t. If not, return to step S6.1 and continue to process and analyze the next received data packet; if yes, execute step S6.7;

[0066] Step S6.7, the cloud data analysis system extracts all environmental data of the previous day from the temporary data repository, the previous day can be specifically considered to be 00:00:00 of the current day to 00:00:00 of the previous day, and uses the truncated mean algorithm to calculate the daily average of all environmental data of the previous day, and stores it in the daily average database;

[0067] The truncated mean algorithm adopted by the present invention is:

[0068] Assume that there are n environmental data in total on the previous day. Arrange the n environmental data in ascending order. The sorted environmental data sequence is: X1, X2, …, X n ;

[0069] Set the truncation ratio to m%, for example, m% is 10%;

[0070] The following formula is used to calculate the number of environmental data N that needs to be removed at each end: N = float (n*m%); float () represents rounding down to an integer;

[0071] Therefore, in the environmental data sequence X1,X2,…,X n In the process, remove the N environmental data at the beginning and the N environmental data at the end, and the remaining n-2*N environmental data; then calculate the average value of the remaining environmental data, which is the final calculated daily average value.

[0072] The truncated mean algorithm of the present invention is adopted to calculate the average value by cleaning the outliers and extreme values ​​in the environmental data sequence, thereby providing a more representative central trend, having the advantages of strong anti-interference ability and high tolerance to noise and false monitoring errors in the data, thereby being able to improve the accuracy of the system preset alarm value obtained subsequently.

[0073] Step S6.8, the cloud data analysis system reads the daily average values ​​of the most recent 7 days from the daily average database, calculates the average of the 7 daily average values ​​read, obtains the 7-day average data, and determines whether the 7-day average data has changed compared with the system preset alarm value. If there is no change, return to step S6.6; if there is a change, the 7-day average data is used to update the system preset alarm value, and the updated system preset alarm value is sent to the data acquisition system to ensure that the system preset alarm value of the data acquisition system of each node is synchronously updated, and then return to step S6.6.

[0074] The local alarm mechanism of the local alarm system of the present invention and the cloud alarm mechanism of the cloud alarm system can both be implemented using the following principles:

[0075] The alarm system is designed to achieve comprehensive monitoring of systems and equipment, timely detect abnormal situations, and generate and process alarms to ensure system stability and performance.

[0076] The alarm system includes: an alarm processing module and an alarm notification module.

[0077] (I) Alarm processing module

[0078] The alarm processing module is the core of the alarm system, responsible for the entire process from receiving alarms to final processing and feedback of alarms. The design of the alarm processing module includes functions such as alarm receiving submodule, alarm response and processing submodule, alarm feedback recording submodule and alarm performance monitoring submodule, ensuring that alarms can be processed efficiently and accurately, thereby maintaining the stability and reliability of the system.

[0079] 1. Alarm receiving submodule:

[0080] The primary function of the alarm processing module is to receive alarm data from different sources. The alarm receiving submodule receives and caches alarm data through the message queue system (Kafka), which can handle high-concurrency alarm data and ensure that alarm data is not lost. In addition, a RESTful API interface is provided for receiving real-time alarm data from monitoring systems, sensors and other data sources, and integrating with the log system to extract alarm information from it.

[0081] The alarm data received by the alarm receiving submodule needs to be preprocessed. This process includes cleaning the data to filter out invalid or duplicate data, unifying the format to convert data from different sources into a standard format, and storing the processed alarm data in a database for subsequent analysis and processing. Data preprocessing ensures the consistency and integrity of the alarm data, facilitating further operation of the system.

[0082] 2. Alarm response and processing submodule:

[0083] After the alarm data is preprocessed, it enters the alarm response and processing submodule.

[0084] The alarm response and processing submodule executes automated scripts for alarms that can be automatically processed. These scripts are used to perform automatic repair operations, such as restarting services, adjusting resource configurations, etc. At the same time, the alarm response and processing submodule is integrated with system management tools to automatically adjust resource configurations or restart services.

[0085] For complex or high-priority alarm data, the alarm response and processing submodule will generate a work order and assign it to relevant personnel for processing. The relevant personnel will be notified in real time through the notification system to ensure that the work order is processed in a timely manner. During the manual processing process, the processing personnel will perform corresponding operations based on the alarm information and verify after the problem is solved to confirm that the system has returned to normal.

[0086] 3. Alarm feedback record submodule:

[0087] During the alarm processing process of the alarm response and processing submodule, the alarm feedback record submodule records and manages the relevant information in the alarm processing process, records the processing status, solutions and notes through the online feedback form, and synchronizes these feedback information to the alarm system to update the alarm status. The update of the alarm status includes marking the alarm as "resolved" or "pending confirmation" and notifying relevant personnel of the change in the alarm status. Feedback records not only help the alarm system track the progress of alarm processing, but also provide valuable data for subsequent analysis and improvement.

[0088] 4. Alarm performance monitoring submodule:

[0089] Performance monitoring of the alarm response and processing submodule is the key to ensuring the efficient operation of the alarm system. The alarm performance monitoring submodule collects and analyzes performance indicators, including alarm processing time, response speed, and processing success rate, and displays these performance data through a real-time dashboard to help operation and maintenance personnel quickly understand the status of the alarm system.

[0090] Based on performance data, the alarm system implements optimization strategies, such as adjusting the alarm processing process, optimizing algorithms, and adjusting system resource configuration according to alarm data to improve alarm processing efficiency. In addition, load balancing is performed based on monitoring data to ensure that the alarm system can maintain stable performance under high load conditions.

[0091] (II) Alarm Notification Module

[0092] The alarm notification module is one of the key components of the alarm system, responsible for effectively conveying alarm information to relevant personnel or systems. The alarm notification module includes notification generation submodule, notification method submodule, notification rule submodule, notification management submodule and system integration submodule, etc., to ensure that alarm information can reach relevant parties in a timely and accurate manner to support rapid response and processing.

[0093] 1. Notification generation submodule:

[0094] The notification generation submodule first generates notification information from the alarm data. This process includes extracting key alarm content, such as alarm type, severity, timestamp, alarm description, and recommended actions, and formatting this information into a suitable notification format, including text, HTML, or rich media format. In order to support notifications of different types and requirements, the system uses a template engine to generate notification content and marks the priority of notifications according to the priority of the alarm. This ensures the accuracy and personalization of notifications to adapt to different notification methods and channels.

[0095] 2. Notification method submodule:

[0096] The notification method determines how to pass the alarm information to relevant personnel or systems. The system supports multiple notification methods, including:

[0097] Email notification: Configure email templates and use SMTP servers to send emails. The email queue system is used to cache and send emails in batches to improve sending efficiency and reliability.

[0098] SMS notification: Integrate SMS gateway service to send SMS notifications. Configure SMS templates to ensure that alarm information is conveyed concisely and clearly.

[0099] Push notification: integrated push service, supports push notifications on mobile and desktop. Configure push notification format and trigger conditions, supports multi-platform push service.

[0100] ·Instant Messaging: Integrate with instant messaging systems to send notifications through chat applications. Configure message formats and channels to ensure that notifications are delivered effectively.

[0101] 3. Notification rules submodule:

[0102] The notification rules submodule defines how to send notifications based on the alarm information and the needs of the recipients to ensure the effectiveness and relevance of the notifications. The rule engine of the notification rules submodule is used to configure and apply rules to determine the triggering conditions for notifications based on the type, severity, and recipient settings of the alarm. Set notification frequency rules to prevent too frequent or repeated notifications, and decide whether to send notifications based on the alarm type and priority. The recipient's notification preferences and channels will also affect the notification delivery strategy to ensure that notifications are delivered to the appropriate people and channels.

[0103] 4. Notification management submodule:

[0104] The notification management submodule is responsible for managing the notification sending records, configuration and status to ensure the normal operation of the notification system. The notification management submodule records the sending log of each notification, including the alarm information, sending time, sending channel and recipient, and tracks the status of the notification, such as whether it was successfully delivered. Configuration management includes the management of rules and templates, as well as the setting of various notification channels. The system also handles abnormal situations in the notification sending process, such as sending failures, network problems, etc., and implements a retry mechanism to ensure that the notification can be resent in the event of a temporary failure.

[0105] 5. System integration submodule:

[0106] The system integration submodule ensures that the notification management submodule can be seamlessly connected with other systems and services. It provides a notification sending API interface, allowing other systems or services to call to send alarm notifications, and provides a configuration API interface to set notification rules and templates. The system integration submodule synchronizes with the database of the alarm system to ensure real-time update and consistency of notification data, and integrates third-party services to support cross-platform notifications and data sharing.

[0107] Therefore, the cloud data analysis system analyzes and calculates the received environmental data to determine whether the current data center or service center is abnormal. If the current environment is abnormal, SMS notification, phone notification, WeChat notification, etc. will be made according to the abnormal level and the pre-set emergency contact directory. If the system does not receive the abnormal confirmation status within the specified time, the system will perform pre-processing. The program uses the abnormal plan pre-set by the abnormal data center or service center through a dedicated communication channel to pre-process the corresponding process and the local security equipment of the data center or service center that needs to be activated. According to the danger level, the data center or service center lights alarm, the monitoring screen scrolls alarm, automatically cuts off the power, starts ventilation, etc., to reduce the economic losses caused by abnormalities.

[0108] Compared with the prior art, the present invention has the following beneficial effects:

[0109] The present invention provides a dynamic environment monitoring method for a data center or service center. The data acquisition system integrates environmental data acquisition, data preprocessing and data submission functions at the same time. The collected environmental data can be submitted to the cloud data analysis system in real time after data preprocessing. The cloud data analysis system receives environmental data from the monitored data center or service center in real time, and performs data processing and analysis. Users can query the environmental data and alarm records of the current data center or service center in the cloud data analysis system. The present invention can effectively improve the timeliness of alarm notifications. It also has the advantages of more comprehensive monitoring content, clearer hierarchical structure, greatly reduced engineering costs and improved system stability, as well as simple wiring, higher transmission efficiency and independent alarm notification.

[0110] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be considered as the scope of protection of the present invention.

Claims

1. A dynamic environment monitoring method for a data center or service center, characterized in that: Applicable to a dynamic environment monitoring system including a data acquisition system, a cloud data analysis system and an alarm system; wherein the data acquisition system includes an environmental data acquisition module, a data preprocessing module and a data submission and network connection module; the alarm system includes a local alarm system and a cloud alarm system; The method comprises the following steps: Step S1, the data acquisition system uses the environmental data acquisition module to perform real-time environmental monitoring on the monitored data center or service center, and acquires raw environmental data in real time; Step S2, the data preprocessing module converts the raw environmental data into recognizable environmental data in real time, and then preliminarily determines whether the recognizable environmental data is obviously abnormal data. If so, the environmental data is abandoned and the process returns to step S1; if not, step S3 is executed; Step S3, the data preprocessing module determines whether the environmental data reaches the system preset alarm value pushed by the cloud data analysis system. If so, the local alarm system is immediately notified to start the local alarm mechanism, and then step S4 is executed; if not, step S4 is directly executed; Step S4, the data preprocessing module performs a first standardization process on the environmental data, converts the environmental data into a unified format, integrates the environmental data into a same data set with the same timestamp, and submits the data to the data submission and network connection module; Step S5, the data submission and network connection module performs a second standardization process on the environmental data in the data set, converts it into a standard data format, and then packages the data to obtain a data packet; and uploads the data packet to the cloud data analysis system; Step S6, the cloud data analysis system performs data analysis on the received data packet to determine whether the monitored data center or service center is currently abnormal. If abnormal, the cloud alarm system is notified to start the cloud alarm mechanism; at the same time, based on the received data packet, a new system preset alarm value is updated and generated, and pushed to the data preprocessing module of the data acquisition system.

2. A dynamic environment monitoring method for a data center or service center according to claim 1, characterized in that: The raw environmental data is real-time monitoring environmental data collected by various sensors in real time, including temperature, humidity and air pressure.

3. The method for dynamic environment monitoring for a data center or service center according to claim 1, characterized in that: The data acquisition system is configured with an acquisition module connected to various sensors via a serial port or an I2C interface; the data acquisition system collects environmental data in a scheduled or on-demand manner.

4. The method for dynamic environment monitoring for a data center or service center according to claim 1, characterized in that: Step S6 is specifically as follows: Step S6.1, the cloud data analysis system performs preliminary formatting and verification on the received data packet to ensure the integrity and accuracy of the data packet; Step S6.2, the cloud data analysis system reads each piece of environmental data in the data packet, and executes step S6.3 for each piece of environmental data read; Step S6.3, the cloud data analysis system determines whether the environmental data is greater than the system preset alarm value, if yes, execute step S6.4; if no, directly execute step S6.5; Step S6.4, triggering the cloud alarm system to send an alarm notification to the management personnel, so that the management personnel can verify whether the environmental data is consistent with the real event, and determine whether the notification of the management personnel confirming the event and submitting the environmental data is received within the set time. If yes, execute step S6.5; if not, return to step S6.2 and continue to read the next environmental data in the data packet; Step S6.5, storing the environmental data in a temporary data storage repository, and determining whether all environmental data in the data packet have been read and analyzed, if yes, executing step S6.6; if no, returning to step S6.2; Step S6.6, the cloud data analysis system predefines a designated time t for determining whether the preset alarm value of the system is updated every day, and determines whether the current time is the designated time t. If not, return to step S6.1 and continue to process and analyze the next received data packet; if yes, execute step S6.7; Step S6.7, the cloud data analysis system extracts all environmental data of the previous day from the temporary data repository, and uses a truncated mean algorithm to calculate the daily average of all environmental data of the previous day, and stores it in a daily average database; Step S6.8, the cloud data analysis system reads the daily average values ​​of the most recent 7 days from the daily average database, calculates the average of the 7 daily average values ​​read, obtains the 7-day average data, and determines whether the 7-day average data has changed compared with the system preset alarm value. If there is no change, return to step S6.6; if there is a change, use the 7-day average data to update the system preset alarm value, and send the updated system preset alarm value to the data acquisition system, and then return to step S6.

6.

5. A dynamic environment monitoring method for a data center or service center according to claim 4, characterized in that: The designated time t is a time close to midnight every day.

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