Emergency power supply monitoring system and method based on Internet of Things

Abstract

The invention discloses an emergency power supply monitoring system and method based on the Internet of Things in the technical field of emergency power supplies, and the system comprises an emergency power supply sensing module, a master control device, a detection module and an alarm module, and the emergency power supply sensing module is used for carrying out the gapless switching between a commercial power supply and a standby power supply, so as to guarantee the uninterrupted power supply of a connected load. Power supply of the system is prevented from being influenced during mains supply outage; the emergency power supply sensing module is electrically connected to three pins of the main control device, and the main control device is used for classifying and managing communication data and converging communication links. By monitoring the voltage, current, frequency and standby power duration of the host and the voltage, internal resistance and pole temperature parameters of each battery in real time, the use state of each battery in the emergency power supply can be monitored in real time, and early warning and the real-time working state of the emergency power supply can be provided on the premise that the standby power supply is abnormal.

Description

Technical Field

[0001] The present invention relates to the technical field of emergency power supplies, and specifically to an emergency power supply monitoring system and method based on the Internet of Things. Background Art

[0002] According to the definition of emergency power supply in the national standard GB50052-2009 "Code for Design of Electrical Supply and Distribution Systems": An emergency power supply is a power source that constitutes an emergency power supply system, also known as a safety facility power source, which refers to a power source that supplies power separately to particularly important loads to ensure safety in accidents and emergencies. The emergency power supply system is a power supply system used to maintain the operation of electrical equipment and electrical installations.

[0003] Most existing emergency power supply systems use lead-acid batteries as backup power sources. As the service life of lead-acid batteries increases, the backup power source is prone to phenomena such as battery bulging, pole leakage, release of sulfur dioxide and hydrogen during use. If the service life of the backup power source is further extended, it is extremely likely to cause a fire, and the fire caused by the backup power source is extremely difficult to extinguish; on the other hand, due to the lack of effective monitoring and warning mechanisms in most emergency power supply systems, the emergency power supply system cannot respond in a timely manner when the power supply is abnormal or fails, which is likely to cause serious safety accidents; at the same time, due to the lack of equipment capable of perceiving the state of each battery in the existing emergency power supply system and a mechanism capable of effectively evaluating the battery condition, the emergency power supply system cannot quickly determine whether there are phenomena such as battery bulging and leakage, making it difficult to effectively ensure the stability and safety of the operation of the emergency power supply system. Summary of the Invention

[0004] The purpose of the present invention is to provide an emergency power supply monitoring system and method based on the Internet of Things. By real-time monitoring of parameters such as the voltage, current, frequency, backup power duration of the main machine, and the voltage, internal resistance, and pole temperature of each battery, it can monitor the usage status of each battery in the emergency power supply in real time, and can provide early warnings and the real-time working status of the emergency power supply on the premise that the backup power source has abnormal conditions.

[0005] To achieve the above purpose, the present invention provides the following technical solutions: In a first aspect, the present invention provides an emergency power supply monitoring system based on the Internet of Things. The system includes an emergency power supply sensing module, a main control device, a detection module, and an alarm module. The emergency power supply sensing module is used to seamlessly switch between the mains power and the backup power supply to ensure uninterrupted power supply to the connected load and avoid affecting the power supply of the system when the mains power fails. The emergency power supply sensing module is electrically connected to three pins of the main control device. The main control device is used to classify and manage communication data and converge communication links. The fourth pin of the main control device is connected to the detection module, and the detection module is used to detect the voltage, current, and frequency parameters of the lead-acid battery pack. The fifth pin of the main control device is connected to the alarm module, and the alarm module is used to send an alarm signal to the main control device when the detection module detects abnormal data.

[0006] As a further aspect of the present invention: The emergency power supply sensing module includes a lead-acid battery pack and an uninterruptible power supply head. The capacity of the lead-acid battery pack determines the power supply duration of the emergency power supply sensing module. The lead-acid battery pack is serially connected to the first pin and the second pin of the main control device, and the uninterruptible power supply head is electrically connected to the third pin of the main control device.

[0007] As a further aspect of the present invention: The lead-acid battery pack includes a plurality of emergency power supplies and a plurality of sensing units. The plurality of emergency power supplies are serially connected in sequence and form a closed-loop ring link with the convergence point of the main control device. Each emergency power supply includes a battery and a sensing unit. Each sensing unit is connected to the positive and negative electrodes of the corresponding emergency power supply. The sensing unit is used to monitor the operating state of the battery connected thereto in real time.

[0008] As a further aspect of the present invention: The operating state of the battery includes battery voltage, terminal temperature, and battery internal resistance.

[0009] As a further aspect of the present invention: A plurality of communication interfaces are provided between the uninterruptible power supply head and the main control device. The plurality of communication interfaces are used to integrate different uninterruptible power supply heads on the main control device.

[0010] As a further aspect of the present invention: The main control device includes a communication link convergence module, an operating system, a network communication module, a first user interface module, an algorithm module, a second user interface module, and a display module; The communication link convergence module is called by the main control device to classify and manage the monitoring signals of the battery and the uninterruptible power supply head and point-to-point data communication.

[0011] As Figure 3 shown, the workflow steps of the communication link convergence module are as follows: The communication link convergence module listens to the physical hardware interface; Identifies the type of access device through a specific mode; Call the built-in module of the system to parse the algorithm and perform point-to-point parsing with the device; Append the measured point data to the memory and allocate a register storage area.

[0012] The communication link convergence module can continuously monitor the physical hardware interface of the main control device. By sensing the physical interface at a millisecond-level listening frequency, it can detect whether there is a sensing module, a detection module, or other communication devices. If a communication device is identified during a certain scan cycle, the built-in coding algorithm is called through the main control device to identify the type of the device connected to the main control device, and the matching parsing algorithm is called to perform point-to-point data parsing on the device. Then, the data measurement points of different devices are appended to the built-in memory, and a data register storage area is allocated to complete the data convergence work. After the data register storage area stores the data, the algorithm module needs to configure the data in the data register storage area to achieve data storage and optimization; The algorithm module includes a numerical verification algorithm, a numerical traceability algorithm, a permission algorithm, a numerical storage algorithm, an AI trend algorithm, and a numerical alarm algorithm. The algorithm module is used to configure and optimize data and to evaluate in real time whether there is bulging and leakage in the backup battery of the emergency power supply, so as to avoid battery fire faults by timely detecting abnormal phenomena of the emergency power supply.

[0013] The algorithm module can verify whether the data of the communication link convergence module is accurate through the numerical verification algorithm. If illegal data appears, the illegal error data can be discarded and the correct data can be retained through the numerical verification algorithm; the numerical storage algorithm can set the rules for data storage, such as timed storage / overlimit storage / difference storage of data, etc. For example, when the sulfur dioxide content value is input, the default algorithm is to store a data in the memory every 30 minutes. When there is a large change in the data within 30 minutes, the data is directly stored in the memory. When there is a large change in the data within 30 minutes, the data is directly stored in the memory. The traceability algorithm is used to query the historical records, operation records, and login log information in the memory under specified conditions, such as querying by time period, by device type, data measurement point, etc.; The permission algorithm is used to distinguish the permissions of accessing users. Users with different levels of permissions have different operation permissions, such as permission division for the monitoring interface, query function division for historical data, and permission distinction for control operations, etc.; The algorithm module follows the following process: Data sampling: Sample the data of battery voltage, battery internal resistance, and terminal temperature in the memory, and combine historical data as supporting data; Feature extraction: Extract the resistance change value and the number of sensors with resistance changes from the historical data; Extract temperature feature vectors from the denoised image, including the highest temperature, the lowest temperature, and the temperature in the leakage area; Model training: Construct a training sample set, take each discharge cycle as a sample, and extract the corresponding time series as features; Train a Support Vector Regression (SVR) model, and multiple SVRs form an SVR set; Use the ensemble learning algorithm to fuse multiple trained SVR models to obtain an integrated SVR model; Train a model based on Variable Probability Genetic Algorithm - Gaussian Process (VPGA - GPR), optimize the objective function to minimize the root mean square value of the actual output and the predicted output of the validation set; Model prediction: Use the integrated SVR model to predict the State of Health (SOH) of the lead - acid battery after each discharge cycle, use the VPGA - GPR model to predict the independent test set, compare the predicted value with the true value to verify the effectiveness of the model; Result analysis and marking: Calculate the operating conditions of each battery according to the logistic regression function and the linear regression function, and predict the approximate time of its abnormality on the chart.

[0014] As a further solution of the present invention: The alarm module is used to alarm the illegal error data identified by the algorithm module, and the operating system is used to set logical comparison operators for users to select and configure, and set the upper limit value, upper - upper limit value, lower limit value and lower - lower limit value of the alarm to meet the configuration requirements.

[0015] As a further solution of the present invention: The network communication module is used to provide an Ethernet interface integrated on the main control device. The network communication module transmits data so that the third - party platform can obtain the monitoring data of the device measurement points in the main control device through the Ethernet interface and the corresponding communication protocol; The display module is used to display the monitoring data; The first user interface module and the second user interface module are used for information interaction in system configuration, such as setting the alarm threshold of a certain data, the device IP address, and the time.

[0016] In a second aspect, the present invention also provides an emergency power supply monitoring method based on the Internet of Things, which is applied to the emergency power supply monitoring system based on the Internet of Things as described in the above solution. The method includes: Collect the operation data of the emergency power supply perception module; The data analysis module analyzes the collected operation data in real - time and determines whether it is abnormal data; When it is determined to be abnormal data, the emergency power supply monitoring system starts the early - warning program; Send early - warning information through the mobile Internet. The ways of sending early - warning information through the mobile Internet include sending information by mobile phone text message and pushing information through the APP.

[0017] As a further solution of the present invention: The abnormal data includes voltage dip data, frequency deviation data, and data indicating that the internal resistance of the battery increases beyond the maximum threshold. Through the analysis and mining of a large amount of data, it can provide scientific and reasonable decision-making basis for decision-makers, improve decision-making efficiency and accuracy, provide support for intelligent decision-making, and popularize emergency knowledge to the public through terminal devices, which can improve the public's safety awareness and self-help and mutual rescue capabilities.

[0018] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. By real-time monitoring the parameters of the host voltage, current, frequency, backup power duration, as well as the voltage, internal resistance, and terminal temperature of each battery, the present invention can monitor the usage status of each battery in the emergency power supply in real time, and can provide early warnings and the real-time working status of the emergency power supply on the premise of abnormal situations in the backup power supply.

[0019] 2. Through the Internet of Things technology, the present invention can achieve remote monitoring and data collection, and automatically trigger an early warning mechanism when detecting abnormal situations to notify relevant personnel to take countermeasures. By optimizing the configuration of the emergency power supply, it can reduce losses caused by power outages or battery failures and improve power supply reliability.

[0020] 3. The present invention can achieve real-time monitoring and rapid response to the emergency power supply through the Internet of Things technology. For example, it can quickly switch to the emergency power supply when the power grid is interrupted, reduce the switching time, and improve the emergency response speed of the emergency power supply. By using the Internet of Things technology, it can remotely monitor the working status of the emergency power supply, and understand information such as the remaining power, voltage and current, and the status of backup batteries in real time, ensuring that key facilities continue to operate when the power grid is interrupted and enhancing the reliability of power supply.

[0021] 4. The present invention can automatically adjust the output power according to the real-time load demand, maximize the energy utilization efficiency, and achieve intelligent management of battery energy. By designing an emergency power supply system suitable for different environmental conditions, the emergency power supply can work in harsh environments such as high temperature, low temperature, and humidity to cope with a wider range of disaster situations and improve the adaptability to the environment.

[0022] 5. The present invention can save electric energy by reducing the preheating process of high-pressure sodium lamps when restarting after a power outage. On the other hand, the emergency power supply provided by the present invention can work in public places such as high-speed railways and / or airports, so as to provide emergency lighting in case of power outages or fires, assist people to get out of danger, and protect people's personal safety.

[0023] 6. By setting up a communication link convergence module and a network communication module, the present invention can effectively protect the power supply safety of servers in critical scenarios such as data centers, prevent serious consequences such as data loss caused by power outages, effectively ensure data security, and through cross-departmental collaboration and information sharing, cooperate with the Internet of Things to break down the information barriers between departments, achieve real-time information sharing and collaborative operations, and improve the efficiency and effectiveness of emergency response.

[0024] 7. Through the analysis and mining of massive data, the present invention can provide scientific and reasonable decision-making basis for decision-makers, improve decision-making efficiency and accuracy, provide support for intelligent decision-making, and popularize emergency knowledge to the public through terminal devices, which can improve the public's safety awareness and self-help and mutual rescue capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 is the architecture diagram of the peripheral device and the main control device of the present invention; Figure 2 is the framework diagram of the main control device of the present invention; Figure 3 is the working flow chart of the communication link convergence module of the present invention; Figure 4 is the algorithm module diagram of the present invention; Figure 5 is the working flow chart of the algorithm module of the present invention; Figure 6 is the flow chart of the emergency power supply monitoring method of the present invention.

[0026] In the figure: 1. Emergency power supply perception module; 11. Lead-acid battery pack; 12. Uninterruptible power supply head; 2. Main control device; 21. Communication link convergence module; 22. Operating system; 23. Network communication module; 24. First user interface module; 25. Algorithm module; 26. Second user interface module; 27. Display module; 3. Detection module; 4. Alarm module. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0027] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0028] Embodiment: As Figure 1As shown in the figure, the present invention provides an emergency power supply monitoring system based on the Internet of Things. The system includes an emergency power supply sensing module 1, a main control device 2, a detection module 3, and an alarm module 4. By the detection module 3, parameters such as the host voltage, current, frequency, backup power duration, and the voltage, internal resistance, and pole temperature of each battery can be monitored in real time. It can monitor the usage status of each battery in the emergency power supply in real time, and can provide early warnings and the real-time working status of the emergency power supply on the premise that an abnormal situation occurs in the backup power supply. The emergency power supply sensing module 1 is used to seamlessly switch between the mains power and the backup power supply to ensure uninterrupted power supply to the connected load and avoid affecting the system power supply when the mains power fails; the emergency power supply sensing module 1 is electrically connected to three pins of the main control device 2, and the main control device 2 is used to classify and manage communication data and converge communication links; the fourth pin of the main control device 2 is connected to the detection module 3, and the detection module 3 is used to detect the voltage, current, and frequency parameters of the lead-acid battery pack; the fifth pin of the main control device 2 is connected to the alarm module 4, and the alarm module 4 is used to send an alarm signal to the main control device 2 when the detection module 3 detects abnormal data. Through the Internet of Things technology, remote monitoring and data collection can be realized, and when an abnormal situation is detected, the early warning mechanism can be automatically triggered to notify relevant personnel to take countermeasures. By optimizing the emergency power supply configuration, losses caused by power outages or battery failures can be reduced, and the power supply reliability can be improved.

[0029] Preferably, the emergency power supply sensing module 1 includes a lead-acid battery pack 11 and an uninterruptible power supply head 12. The capacity of the lead-acid battery pack 11 determines the power supply duration of the emergency power supply sensing module 1. The lead-acid battery pack 11 is serially connected to the first pin and the second pin of the main control device 2, and the uninterruptible power supply head 12 is electrically connected to the third pin of the main control device 2.

[0030] Preferably, the lead-acid battery pack 11 includes a plurality of emergency power supplies and a plurality of sensing units. The plurality of emergency power supplies are serially connected in sequence and form a closed-loop ring link with the convergence point of the main control device 2. Each emergency power supply includes a battery and a sensing unit, and each sensing unit is connected to the positive and negative poles of the corresponding emergency power supply. The sensing unit is used to monitor the operating status of the battery connected thereto in real time.

[0031] Preferably, the operating status of the battery includes battery voltage, pole temperature, and battery internal resistance.

[0032] Preferably, a plurality of communication interfaces are provided between the uninterruptible power supply head 12 and the main control device 2, and the plurality of communication interfaces are used to integrate different uninterruptible power supply heads 12 on the main control device 2.

[0033] As Figure 2As shown, the main control device 2 includes a communication link convergence module 21, an operating system 22, a network communication module 23, a first user interface module 24, an algorithm module 25, a second user interface module 26, and a display module 27; The communication link convergence module 21 is called by the main control device 2 to classify and manage the monitoring signals and point-to-point data communication between the battery and the uninterruptible power supply head 12.

[0034] As Figure 3 shown, the working process steps of the communication link convergence module 21 are as follows: S1: The communication link convergence module listens to the physical hardware interface; S2: Identifies the types of access devices through a specific mode; S3: Calls the built-in system module to parse the algorithm and perform point-to-point parsing with the device; S4: Attaches the measured point data to the memory and opens a register storage area.

[0035] The communication link convergence module 21 can continuously listen to the physical hardware interface of the main control device 2, and perceive whether there is a sensing module, a detection module 3, or other communication devices on the physical interface through a listening frequency of milliseconds. If the access of a communication device is recognized in a certain scanning cycle, the built-in coding algorithm of the main control device 2 is called to identify the type of the device accessing the main control device 2, and the matching parsing algorithm is called to perform point-to-point data parsing on the device. Then, the data measurement points of different devices are attached to the built-in memory, and a data register storage area is opened to complete the data convergence work. After the data register storage area stores the data, the algorithm module 25 needs to configure the data in the data register storage area to achieve data storage and optimization; As Figure 4As shown, the algorithm module 25 includes a numerical verification algorithm, a numerical traceability algorithm, a permission algorithm, a numerical storage algorithm, an AI trend algorithm, and a numerical alarm algorithm. The algorithm module 25 can adjust the output power of the main control device 2 according to the real-time load demand, maximize the energy utilization efficiency, and realize the intelligent management of battery energy. By designing an emergency power supply system adapted to different environmental conditions, the emergency power supply can work in harsh environments such as high temperature, low temperature, and humidity, so as to cope with a wider range of disaster situations and improve the adaptability to the environment. The algorithm module 25 is used to configure and optimize data and evaluate in real time whether there is swelling and leakage in the backup battery of the emergency power supply. By detecting the abnormal phenomena of the emergency power supply in time, it is possible to avoid the occurrence of battery fire faults. The algorithm module 25 can verify whether the data of the communication link convergence module 21 is accurate through the numerical verification algorithm. If illegal data appears, the illegal error data can be discarded and the correct data can be retained through the numerical verification algorithm; the numerical storage algorithm can set the rules for data storage, such as timed storage / overlimit storage / difference storage of data, etc. For example, when the sulfur dioxide content value is input, the default algorithm is to store a data in the memory every 30 minutes. When there is a large change in the data within 30 minutes, the data is directly stored in the memory. When there is a large change in the data within 30 minutes, the data is directly stored in the memory. The traceability algorithm is used to query the historical records, operation records, and login log information in the memory under specified conditions, such as querying by time period, by device type, data measurement point, etc.; The permission algorithm is used to distinguish the permissions of accessing users. Users with different levels of permissions have different operation permissions, such as the permission division of the monitoring interface, the query function division of historical data, and the permission distinction of control operations, etc.; Such as Figure 5 As shown, the algorithm module follows the following process: S1: Data sampling: Sample the data of battery voltage, battery internal resistance, and terminal post temperature in the memory, and combine historical data as supporting data; S2: Feature extraction: Extract the resistance change value and the number of sensors with resistance changes from historical data; Extract temperature feature vectors from the denoised image, including the highest temperature, the lowest temperature, and the temperature in the leakage area; S3: Model training: Construct a training sample set, take each discharge cycle as a sample, and extract the corresponding time series as features; Train a support vector regression (SVR) model, and multiple SVRs form an SVR set; Use the ensemble learning algorithm to fuse multiple trained SVR models to obtain an integrated SVR model; Train a model based on the variable probability genetic algorithm - Gaussian process (VPGA-GPR), optimize the objective function, and minimize the root mean square value of the actual output and the predicted output of the validation set; S4: Model prediction: Use the integrated SVR model to predict the state of health (SOH) of the lead-acid battery after each discharge cycle. Use the VPGA-GPR model to predict the independent test set, compare the predicted value with the true value, and test the effectiveness of the model; S5: Result analysis and marking: Calculate the operating conditions of each battery according to the logistic regression function and the linear regression function, and predict the approximate time of its abnormality on the chart.

[0036] Preferably, the alarm module 4 is used to alarm the illegal error data identified by the algorithm module 25. The operating system 22 is used to set logical comparators for the user to select and configure and set the upper limit value, upper upper limit value, lower limit value and lower lower limit value of the alarm to meet the configuration requirements.

[0037] Preferably, the network communication module 23 is used to provide an Ethernet interface integrated on the main control device 2. The network communication module 23 transmits data, so that the third-party platform can obtain the monitoring data of the device measuring points in the main control device (2) through the Ethernet interface and the corresponding communication protocol; The display module 27 is used to display the monitoring data; The first user interface module 24 and the second user interface module 26 are used for information interaction in system configuration, such as setting the alarm threshold of a certain data, the device IP address, and the time.

[0038] Such as Figure 6 As shown, the present invention also provides an emergency power supply monitoring method based on the Internet of Things, which is applied to the emergency power supply monitoring system based on the Internet of Things as described above. The method includes: S1: Collect the operation data of the emergency power supply perception module; S2: The data analysis module analyzes the collected operation data in real time and determines whether it is abnormal data; S3: When it is determined to be abnormal data, the emergency power supply monitoring system starts the warning program; S4: Send a warning message through the mobile Internet. Preferably, the ways of sending warning messages through the mobile Internet include sending messages by mobile phone text messages and pushing messages by APP.

[0039] Preferably, the abnormal data includes voltage dip data, frequency deviation data, and data with the battery internal resistance increasing beyond the maximum threshold. Through the analysis and mining of a large amount of data, it can provide scientific and reasonable decision-making basis for decision-makers, improve decision-making efficiency and accuracy, provide support for intelligent decision-making, and popularize emergency knowledge to the public through terminal devices, which can improve the public's safety awareness and self-help and mutual rescue capabilities.

[0040] The above are only the preferred specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, making equivalent substitutions or changes, shall be covered by the protection scope of the present invention.

Claims

1. An emergency power supply monitoring system based on the Internet of Things, characterized in that: The system comprises: Emergency power supply sensing module: The emergency power supply sensing module is used to seamlessly switch between the mains power supply and the backup power supply to ensure uninterrupted power supply to the connected loads; A main control device, wherein the emergency power sensing module is electrically connected to three pins of the main control device, and the main control device is used to classify and manage communication data and aggregate communication links; A detection module, wherein the fourth pin of the main control device is connected to the detection module, and the detection module is used to detect voltage, current and frequency parameters of the lead-acid battery pack; An alarm module, the fifth pin of the main control device is connected to the alarm module, and the alarm module is used to send an alarm signal to the main control device when the detection module detects abnormal data.

2. The emergency power supply monitoring system based on the Internet of Things according to claim 1 is characterized in that: The emergency power supply sensing module includes a lead-acid battery pack and an uninterruptible power supply head. The capacity of the lead-acid battery pack determines the power supply duration of the emergency power supply sensing module. The lead-acid battery pack is connected in series to the first pin and the second pin of the main control device, and the uninterruptible power supply head is electrically connected to the third pin of the main control device.

3. The emergency power supply monitoring system based on the Internet of Things according to claim 2 is characterized in that: The lead-acid battery pack includes multiple emergency power supplies and multiple sensing units. The multiple emergency power supplies are connected in series in sequence and form a closed-loop ring link with the convergence point of the main control device. Each emergency power supply includes a battery and a sensing unit. Each sensing unit is connected to the positive and negative electrodes of the corresponding emergency power supply. The sensing unit is used to monitor the operating status of the battery connected thereto in real time.

4. The emergency power supply monitoring system based on the Internet of Things according to claim 1 is characterized in that: The operating state of the battery includes battery voltage, electrode temperature and battery internal resistance.

5. The emergency power supply monitoring system based on the Internet of Things according to claim 1 is characterized in that: A plurality of communication interfaces are arranged between the uninterruptible power supply head and the main control device, and the plurality of communication interfaces are used to integrate different uninterruptible power supply heads on the main control device.

6. The emergency power supply monitoring system based on the Internet of Things according to claim 5 is characterized in that: The main control device includes a communication link convergence module, an operating system, a network communication module, a first user interface module, an algorithm module, a second user interface module and a display module; The communication link convergence module is called by the main control device to classify and manage the monitoring signals and point-to-point data communications between the battery and the uninterruptible power supply head; The algorithm module includes a numerical verification algorithm, a numerical traceability algorithm, a permission algorithm, a numerical storage algorithm, an AI trend algorithm, and a numerical alarm algorithm. The algorithm module is used to configure and optimize data and to evaluate in real time whether the backup battery of the emergency power supply has bulging and leakage. The traceability algorithm is used to query the historical records, operation records, and login log information of the storage device under specified conditions. The permission algorithm is used to distinguish the permissions of access users.

7. The emergency power supply monitoring system based on the Internet of Things according to claim 6 is characterized in that: The alarm module is used to alarm the illegal error data identified by the algorithm module, and the operating system is used to set the logical comparison symbol for the user to select and configure and set the upper limit value, upper upper limit value, lower limit value and lower lower limit value of the alarm.

8. The emergency power supply monitoring system based on the Internet of Things according to claim 7 is characterized in that: The network communication module is used to provide a set of Ethernet interfaces integrated on the main control device; The display module is used to display monitoring data; The first user interface module and the second user interface module are used for information interaction in system configuration.

9. An emergency power supply monitoring method based on the Internet of Things, characterized in that: Applied to the Internet of Things-based emergency power supply monitoring system according to any one of claims 1 to 8, the method comprises: Collect the operation data of the emergency power supply sensing module; The data analysis module analyzes the collected operating data in real time and determines whether it is abnormal data; When abnormal data is judged, the emergency power supply monitoring system starts the early warning program; Send early warning information via mobile Internet.

10. The method for monitoring emergency power supply based on the Internet of Things according to claim 9, characterized in that: The abnormal data includes voltage drop data, frequency deviation data, and data indicating that the battery internal resistance increases beyond a maximum threshold.

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