Battery remote monitoring and early warning method and system based on Internet of Things

Abstract

The invention discloses a battery remote monitoring and early warning method and system based on the Internet of Things, and relates to the technical field of remote monitoring, and the method comprises the steps: 1, mainboard button battery state analysis, 2.1, power supply line damage monitoring, 2.2, battery box failure monitoring, and 3, button battery fault processing. The fault of the button cell is found in advance, whether the fault is the problem of the button cell is judged, so that the cause of the fault is further accurately determined, manual intervention is reduced through the voltage measuring instrument and the camera carried by the robot, deformation and liquid leakage of the cell box are analyzed, subsequent fault positioning is facilitated, and the working efficiency is improved. By quickly reducing the fault range of a power supply line, improving the maintenance efficiency and intelligently judging whether the battery box goes wrong or not, a maintainer can position conveniently, so that the operation efficiency of the mainboard is guaranteed, and the possibility of mainboard operation errors is reduced.

Description

Technical Field

[0001] The present invention relates to the field of remote monitoring technology, and in particular to a battery remote monitoring and early warning method and system based on the Internet of Things. Background Art

[0002] Motherboard button batteries are generally used to power BIOS chips, and traditional motherboard button battery detection methods rely on manual inspection, which makes it impossible to detect problems with motherboard button batteries in a timely manner, resulting in problems such as BIOS setting loss, system time errors, hardware configuration failure, etc., reducing the efficiency of motherboard use. Therefore, it is very necessary to monitor and warn of motherboard button batteries.

[0003] Prior art, such as the invention patent application with publication number CN116224094A, discloses a button battery power monitoring method, which includes: obtaining a battery remaining power calculation formula corresponding to the three discharge stages based on the discharge curve relationship; in actual battery power measurement, calling the corresponding calculation formula according to the specific situation to monitor the battery remaining power; and this invention uses a general sensor system circuit to measure the battery power, thereby improving the accuracy and effectiveness of battery remaining power monitoring without adding peripheral circuits. Prior art, such as the invention patent application with publication number CN112732523A, discloses an RTC battery life monitoring circuit and method for a server motherboard, which includes: obtaining the remaining usage time of the RTC battery, being able to monitor the remaining service life of the RTC battery, and ensuring the stable operation of the server motherboard.

[0004] It can be seen from the above scheme that the current battery remote monitoring and early warning method is not accurate in locating button battery faults. Button battery abnormalities may be caused by the battery itself, the power supply line or the battery box, but the existing technology is difficult to distinguish the specific causes, resulting in an inability to accurately repair, which in turn causes high repair costs. In addition, there is a lack of attention to monitoring whether the battery box has a fault. The deformation of the battery box will cause the button battery to be unable to contact the battery box normally, thereby causing the button battery power supply to fail, reducing the operating efficiency of the motherboard system, and increasing the possibility of motherboard operation errors. Summary of the Invention

[0005] The purpose of the present invention is to provide a battery remote monitoring and early warning method and system based on the Internet of Things, which solves the problems existing in the background technology.

[0006] In order to solve the above technical problems, the present invention adopts the following technical solutions: The first aspect of the present invention provides a battery remote monitoring and early warning method based on the Internet of Things, including: Step 1. Analysis of the status of the motherboard button battery: At the target monitoring time point, the motherboard is started up to determine whether the power supply status of the button battery belonging to the motherboard to the BIOS chip is normal. If abnormal, determine whether it is a problem with the button battery belonging to the motherboard itself. If not, execute steps 2.1 and 2.2.

[0007] Step 2.1. Power supply line damage monitoring: Monitor the power supply line of the button battery belonging to the motherboard for fault damage.

[0008] Step 2.2. Battery box failure monitoring: Monitor the battery box that holds the button battery on the motherboard for potential failures.

[0009] Step 3. Button battery troubleshooting: Determine the cause of the abnormal power supply of the button battery belonging to the motherboard and perform corresponding optimization and warning operations.

[0010] The second aspect of the present invention provides a remote monitoring and early warning system for executing the aforementioned remote monitoring and early warning method for batteries based on the Internet of Things, including: a motherboard button battery status analysis module, which is used to perform a startup experiment on the motherboard at a target monitoring time point to determine whether the power supply status of the button battery belonging to the motherboard to the BIOS chip is normal. If not, it is determined whether the problem is with the button battery belonging to the motherboard itself. If not, the power supply line damage monitoring module and the battery box failure monitoring module are executed.

[0011] The power supply line damage monitoring module is used to monitor the power supply line of the button battery belonging to the mainboard for fault damage.

[0012] The battery box failure monitoring module is used to monitor the failure hazards of the battery box where the button battery belonging to the mainboard is placed.

[0013] The button battery fault processing module is used to determine the cause of power supply abnormality of the button battery belonging to the motherboard and perform corresponding optimization and early warning operations.

[0014] The beneficial effects of the present invention are as follows: (1) Step 1 of the present invention analyzes the status of the button battery on the mainboard. By performing startup experiments regularly, the failure of the button battery can be discovered in advance, thereby avoiding data loss caused by sudden failures and determining whether the problem lies with the button battery itself, thereby further accurately determining the cause of the failure.

[0015] (2) In step 2.1 of the present invention, power supply line damage monitoring and step 2.2 of the present invention, the voltage of the power supply line and the image of the battery box are remotely collected through the voltmeter and camera carried by the robot, thereby reducing manual intervention and analyzing the deformation and leakage of the battery box, thereby facilitating the subsequent location of the fault.

[0016] (3) Step 3 of the present invention is to handle button battery faults. This improves maintenance efficiency by quickly narrowing the scope of power supply line faults. The robot is equipped with a liquid suction device to directly handle leakage problems. It can intelligently determine whether there is a problem with the placement of the battery box, making it easier for maintenance personnel to locate the battery. This ensures the operating efficiency of the mainboard and reduces the possibility of mainboard operation errors. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0018] Figure 1 Schematic diagram of the method of the present invention.

[0019] Figure 2 Schematic diagram of the system module of the present invention. DETAILED DESCRIPTION

[0020] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0021] Reference Figure 1 As shown, the present invention provides a battery remote monitoring and early warning method based on the Internet of Things, including: Step 1. Motherboard button battery status analysis: At the target monitoring time point, the motherboard is powered on to determine whether the power supply status of the motherboard button battery to the BIOS chip is normal. If abnormal, determine whether the problem is with the motherboard button battery itself. If not, execute steps 2.1 and 2.2.

[0022] In a specific embodiment of the present invention, the motherboard is started up with a test to determine whether the power supply status of the button battery of the motherboard to the BIOS chip is normal. The specific determination method is: obtaining the power-off duration of the motherboard from a local database.

[0023] When the motherboard is running, the intelligent robot is dispatched to continuously monitor the output voltage of the button battery of the motherboard. Then the motherboard is powered off. After the power off time, the motherboard is restarted to obtain the output voltage of the button battery of the motherboard at each experimental monitoring time point during this monitoring process. , where x represents the number of each experimental monitoring time point, , y is a positive integer greater than 2, and obtains the BIOS setting data of the motherboard during the restart process.

[0024] Obtain the voltage fluctuation coefficient threshold, the button battery's normal output voltage A, and the last setting data of the motherboard's BIOS from the local database to calculate the voltage fluctuation coefficient of the button battery on the motherboard. .

[0025] If the voltage fluctuation coefficient of the button battery belonging to the motherboard is greater than the voltage fluctuation coefficient threshold, it is judged that the power supply status of the button battery belonging to the motherboard to the BIOS chip is abnormal. Otherwise, the BIOS setting data of the motherboard during the restart process is compared with the final setting data. If they are inconsistent, it is judged that the power supply status of the button battery belonging to the motherboard to the BIOS chip is abnormal.

[0026] It should be noted that the local database is used to store the duration of power outage of the motherboard, the voltage fluctuation coefficient threshold, the normal output voltage of the button battery, the last setting data of the BIOS belonging to the motherboard, the detection range of the placed battery box, the abnormal threat coefficient threshold, the initial grayscale value of each pixel point of the appearance image of the battery box where the button battery belonging to the motherboard is placed, and the distance value between the placed battery box at each monitoring point in each direction.

[0027] In a specific embodiment, the output voltage of the button battery belonging to the mainboard at each experimental monitoring time point during the monitoring process is obtained by using the voltage probe of the intelligent robot to obtain the output voltage of the button battery belonging to the mainboard at each experimental monitoring time point during the monitoring process.

[0028] In a specific embodiment, the method for obtaining the setting data of the BIOS of the motherboard during the restart process is as follows: obtaining the setting data of the BIOS of the motherboard during the restart process through the internal system of the motherboard.

[0029] In a specific embodiment of the present invention, the determination of whether the problem lies with the button battery of the motherboard itself is determined by setting the BIOS data of the motherboard to the last setting data, powering off the motherboard, replacing the button battery of the motherboard with a new one, and performing a restart test again. If it is still determined that the power supply status of the button battery of the motherboard to the BIOS chip is abnormal, then it is determined that the problem is not with the button battery of the motherboard itself.

[0030] Step 1 of the present invention is to analyze the status of the button battery on the mainboard. By performing startup experiments regularly, the failure of the button battery can be discovered in advance to avoid data loss caused by sudden failures, and to determine whether the problem is with the button battery itself, so as to further accurately determine the cause of the failure.

[0031] Step 2.1. Power supply line damage monitoring: Monitor the power supply line of the button battery belonging to the motherboard for fault damage.

[0032] In a specific embodiment of the present invention, the fault hazard monitoring of the power supply circuit of the button battery belonging to the mainboard is performed, and its specific monitoring method is: performing a startup experiment, and performing voltage testing on the starting point and ending point of the power supply circuit of the button battery belonging to the mainboard through the voltmeter of the intelligent robot, thereby obtaining the starting point voltage and ending point voltage of the power supply circuit of the button battery belonging to the mainboard.

[0033] In a specific embodiment, the starting point voltage and the ending point voltage of the power supply circuit of the button battery belonging to the mainboard are obtained by the voltage probe of the intelligent robot to obtain the starting point voltage and the ending point voltage of the power supply circuit of the button battery belonging to the mainboard.

[0034] Step 2.2. Battery box failure monitoring: Monitor the battery box that holds the button battery on the motherboard for potential failures.

[0035] In a specific embodiment of the present invention, the battery box for placing button batteries belonging to the mainboard is monitored for fault hazards, and the specific monitoring method is: obtaining the detection range of the battery box from a local database.

[0036] Through the camera of the intelligent robot, the contact images of the button battery belonging to the motherboard and the battery box in various directions are obtained. Then the button battery belonging to the motherboard is removed, the appearance image of the battery box where the button battery belonging to the motherboard is placed is obtained, and the leakage information within the detection range of the battery box where the button battery belonging to the motherboard is placed is obtained.

[0037] In a specific embodiment, the leakage information of the button battery belonging to the mainboard within the detection range of the battery box where the button battery is placed is obtained by a leakage detection probe to obtain the leakage information of the button battery belonging to the mainboard within the detection range of the battery box where the button battery is placed, wherein the leakage information is used to determine whether there is leakage.

[0038] It should be noted that the detection range includes: the inside of the battery box and the range within a certain distance (such as 1 cm) from the edge of the battery box.

[0039] In step 2.1 of the present invention, power supply line damage monitoring and step 2.2 of the battery box failure monitoring are carried out by using the voltmeter and camera carried by the robot to remotely collect the power supply line voltage and battery box image, reducing manual intervention, and analyzing the battery box deformation and leakage, thereby facilitating the subsequent fault location.

[0040] Step 3. Button battery troubleshooting: Determine the cause of the abnormal power supply of the button battery belonging to the motherboard and perform corresponding optimization and warning operations.

[0041] In a specific embodiment of the present invention, the method for determining the cause of the abnormal power supply of the button battery belonging to the mainboard is as follows: if the starting point voltage and the ending point voltage of the power supply circuit of the button battery belonging to the mainboard are inconsistent, then it is determined that the cause of the abnormal power supply of the button battery belonging to the mainboard is an abnormal power supply circuit.

[0042] Based on the appearance image of the battery box where the button battery of the motherboard is placed and the contact images with the battery box in various directions, the mutation threat coefficient of the battery box where the button battery of the motherboard is placed is analyzed.

[0043] A mutation threat coefficient threshold is obtained from a local database. If the mutation threat coefficient of the battery box containing the button battery on the motherboard is greater than the mutation threat coefficient threshold, it is determined that the power supply abnormality of the button battery on the motherboard is caused by deformation of the battery box.

[0044] If leakage occurs within the detection range of the battery box where the button battery belonging to the mainboard is placed, it is determined that the power supply abnormality of the button battery belonging to the mainboard is caused by abnormal leakage.

[0045] In a specific embodiment of the present invention, the abnormal threat coefficient of the battery box where the button battery of the motherboard is placed is analyzed by the following specific analysis method: based on the contact image of the button battery of the motherboard and the battery box in each direction, the distance value between the button battery of the motherboard and the battery box in each direction at each monitoring point is obtained by image recognition technology. , where n represents the number of each direction, , m is a positive integer greater than 2, i represents the number of each monitoring point, , j is a positive integer greater than 2.

[0046] Extract the grayscale value of each pixel of the appearance image of the battery box where the button battery belongs to the motherboard and the battery box where the button battery belongs to the motherboard , where p represents the number of each pixel, , q is a positive integer greater than 2.

[0047] Get the initial grayscale value of each pixel of the appearance image of the battery box where the button battery belongs to the motherboard from the local database And the distance between the battery box and each monitoring point in each direction Calculate the mutation threat coefficient of the battery box where the button battery on the motherboard is placed , where j is the number of monitoring points and m is the number of directions.

[0048] In a specific embodiment, the distance values between the button batteries belonging to the mainboard and the placed battery box at each monitoring point in each direction are obtained by the specific method: the existing technology of distance recognition through images is relatively mature, and the distance values between the button batteries belonging to the mainboard and the placed battery box at each monitoring point in each direction can be obtained through the contact images of the button batteries belonging to the mainboard and the placed battery box in each direction.

[0049] It should be noted that before installing the button battery and the battery box on the mainboard, the monitoring points of the button battery and the battery box need to be marked respectively, and the number of monitoring points of the button battery and the battery box is the same, and there is a one-to-one correspondence.

[0050] In a specific embodiment of the present invention, the corresponding optimization warning operation is performed, and its specific operation method is: if the power supply abnormality of the button battery belonging to the mainboard is caused by the abnormal power supply line, then the fault range of the power supply line of the button battery belonging to the mainboard is analyzed and sent to the person in charge of maintenance.

[0051] If the abnormal power supply of the button battery belonging to the mainboard is caused by the deformation of the battery box, an early warning will be issued to the person in charge of maintenance to remind him to replace the battery box.

[0052] If the abnormal power supply of the button battery belonging to the motherboard is caused by leakage, use the intelligent robot's leakage suction device to clean up the leakage.

[0053] In a specific embodiment of the present invention, the fault range of the power supply circuit of the button battery belonging to the mainboard is analyzed, and the specific analysis method is: perform a startup experiment, obtain the starting point voltage and the mid-point voltage of the power supply circuit of the button battery belonging to the mainboard; if the starting point voltage and the mid-point voltage of the power supply circuit of the button battery belonging to the mainboard are inconsistent, then continue to perform the startup experiment, obtain the starting point voltage and the voltage at one-quarter distance point of the power supply circuit of the button battery belonging to the mainboard; otherwise, obtain the ending point voltage and the voltage at three-quarter distance point of the power supply circuit of the button battery belonging to the mainboard, and so on, and continuously use the dichotomy method to determine the fault range of the power supply circuit of the button battery belonging to the mainboard.

[0054] It should be noted that the quarter distance point is a point on the power supply line that is one quarter of the length of the entire power supply line from the starting point, and the three quarters distance point is a point on the power supply line that is three quarters of the length of the entire power supply line from the starting point.

[0055] Step 3 of the present invention is to handle button battery faults, which improves maintenance efficiency by quickly narrowing the scope of power supply line faults. The robot is equipped with a liquid suction device to directly handle leakage problems, and intelligently judge whether there is a problem with the placement of the battery box, which is convenient for maintenance personnel to locate, thereby ensuring the operating efficiency of the motherboard and reducing the possibility of motherboard operation errors.

[0056] Reference Figure 2 As shown, the second aspect of the present invention provides a remote monitoring and early warning system for executing the battery remote monitoring and early warning method based on the Internet of Things, including: a mainboard button battery status analysis module, a power supply line damage monitoring module, a battery box failure monitoring module, a button battery fault processing module and a local database.

[0057] It should be noted that the mainboard button battery status analysis module is connected to the power supply line damage monitoring module and the battery box failure monitoring module, the button battery fault processing module is connected to the power supply line damage monitoring module and the battery box failure monitoring module, and the local database is connected to the mainboard button battery status analysis module, the battery box failure monitoring module, and the button battery fault processing module.

[0058] The motherboard button battery status analysis module is used to perform a startup experiment on the motherboard at the target monitoring time point to determine whether the power supply status of the button battery belonging to the motherboard to the BIOS chip is normal. If not, it is determined whether the problem is with the button battery belonging to the motherboard itself. If not, the power supply line damage monitoring module and the battery box failure monitoring module are executed.

[0059] The power supply line damage monitoring module is used to monitor the power supply line of the button battery belonging to the mainboard for fault damage.

[0060] The battery box failure monitoring module is used to monitor the failure hazards of the battery box where the button batteries belonging to the mainboard are placed.

[0061] The button battery fault processing module is used to determine the cause of the power supply abnormality of the button battery belonging to the mainboard and perform corresponding optimization and early warning operations.

[0062] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they should all fall within the scope of protection of the present invention.

Claims

1. A battery remote monitoring and early warning method based on the Internet of Things, characterized in that: include: Step 1. Motherboard coin cell battery status analysis: At the target monitoring time, power on the motherboard to determine whether the motherboard coin cell battery is properly supplying power to the BIOS chip. If not, determine whether the problem lies with the motherboard coin cell battery itself. If not, proceed to steps 2.1 and 2.

2. Step 2.

1. Power supply line damage monitoring: Monitor the power supply line of the button battery on the motherboard for fault damage; Step 2.

2. Battery box failure monitoring: Monitor the battery box that holds the button battery on the motherboard for potential damage. Step 3. Button battery troubleshooting: Determine the cause of the abnormal power supply of the button battery belonging to the motherboard and perform corresponding optimization and warning operations.

2. The method for remote battery monitoring and early warning based on the Internet of Things according to claim 1, characterized in that: The motherboard startup test is performed to determine whether the power supply status of the motherboard's button battery to the BIOS chip is normal. The specific judgment method is as follows: Get the mainboard power outage duration from the local database; When the motherboard is running, the intelligent robot is dispatched to continuously monitor the output voltage of the button battery of the motherboard. Then the motherboard is powered off. After the power off time, the motherboard is restarted to obtain the output voltage of the button battery of the motherboard at each experimental monitoring time point during this monitoring process. , where x represents the number of each experimental monitoring time point, , y is a positive integer greater than 2, and obtains the BIOS setting data of the motherboard during the restart process; Obtain the voltage fluctuation coefficient threshold, the normal output voltage A of the button battery, and the last setting data of the motherboard's BIOS from the local database to calculate the voltage fluctuation coefficient of the button battery on the motherboard. ; If the voltage fluctuation coefficient of the button battery belonging to the motherboard is greater than the voltage fluctuation coefficient threshold, it is judged that the power supply status of the button battery belonging to the motherboard to the BIOS chip is abnormal. Otherwise, the BIOS setting data of the motherboard during the restart process is compared with the final setting data. If they are inconsistent, it is judged that the power supply status of the button battery belonging to the motherboard to the BIOS chip is abnormal.

3. The method for remote battery monitoring and early warning based on the Internet of Things according to claim 2, characterized in that: The specific method for determining whether the problem lies with the button battery of the motherboard is as follows: Set the motherboard's BIOS data to the latest settings, power off the motherboard, replace the motherboard's button battery with a new one, and restart the computer. If the power supply status of the motherboard's button battery to the BIOS chip is still abnormal, it is determined that the problem is not with the motherboard's button battery itself.

4. The method for remote battery monitoring and early warning based on the Internet of Things according to claim 1, characterized in that: The specific monitoring method for the fault hazard monitoring of the power supply circuit of the button battery of the mainboard is as follows: Conduct a startup experiment and use the intelligent robot's voltmeter to test the starting and ending points of the power supply circuit of the button battery belonging to the motherboard, so as to obtain the starting point voltage and ending point voltage of the power supply circuit of the button battery belonging to the motherboard.

5. The method for remote battery monitoring and early warning based on the Internet of Things according to claim 4, characterized in that: The specific monitoring method for monitoring the failure hazard of the battery box where the button battery of the mainboard is placed is as follows: Obtain the detection range of the placed battery box from the local database; Through the camera of the intelligent robot, the contact images of the button battery belonging to the motherboard and the battery box in various directions are obtained. Then the button battery belonging to the motherboard is removed, the appearance image of the battery box where the button battery belonging to the motherboard is placed is obtained, and the leakage information within the detection range of the battery box where the button battery belonging to the motherboard is placed is obtained.

6. The method for remote battery monitoring and early warning based on the Internet of Things according to claim 5, characterized in that: The specific method for determining the cause of abnormal power supply of the button battery of the motherboard is as follows: If the starting point voltage and the ending point voltage of the power supply circuit of the button battery of the motherboard are inconsistent, it is determined that the power supply abnormality of the button battery of the motherboard is caused by an abnormal power supply circuit; Analyze the mutation threat factor of the button battery compartment on the motherboard based on the appearance image of the compartment and the contact images of the compartment in various directions. Obtain a mutation threat coefficient threshold from a local database. If the mutation threat coefficient of the battery compartment containing the motherboard's button battery is greater than the mutation threat coefficient threshold, determine that the power supply anomaly of the motherboard's button battery is caused by deformation of the battery compartment. If leakage occurs within the detection range of the battery box where the button battery belonging to the mainboard is placed, it is determined that the power supply abnormality of the button battery belonging to the mainboard is caused by leakage abnormality.

7. The method for remote battery monitoring and early warning based on the Internet of Things according to claim 6, characterized in that: The specific analysis method for analyzing the abnormal threat coefficient of the battery box where the button battery belonging to the motherboard is placed is as follows: Based on the contact images of the button battery of the motherboard and the battery box in each direction, and through image recognition technology, the distance value between the button battery of the motherboard and the battery box at each monitoring point in each direction is obtained. , where n represents the number of each direction, , m is a positive integer greater than 2, i represents the number of each monitoring point, , j is a positive integer greater than 2; Extract the grayscale value of each pixel of the appearance image of the battery box where the button battery belongs to the motherboard and the battery box where the button battery belongs to the motherboard , where p represents the number of each pixel, , q is a positive integer greater than 2; Get the initial grayscale value of each pixel of the appearance image of the battery box where the button battery belongs to the motherboard from the local database And the distance between the battery box and each monitoring point in each direction Calculate the mutation threat coefficient of the battery box where the button battery on the motherboard is placed , where j is the number of monitoring points and m is the number of directions.

8. The method for remote battery monitoring and early warning based on the Internet of Things according to claim 6, characterized in that: The specific operation method for performing the corresponding optimization warning operation is as follows: If the power supply abnormality of the button battery of the motherboard is caused by an abnormal power supply line, analyze the fault scope of the power supply line of the button battery of the motherboard and send it to the person in charge of maintenance; If the abnormal power supply of the button battery of the motherboard is caused by the deformation of the battery box, an early warning will be issued to the maintenance person in charge to remind him to replace the battery box; If the abnormal power supply of the button battery belonging to the motherboard is caused by leakage, use the intelligent robot's leakage suction device to clean up the leakage.

9. The method for remote battery monitoring and early warning based on the Internet of Things according to claim 8, characterized in that: The specific analysis method for analyzing the fault range of the power supply circuit of the button battery belonging to the motherboard is as follows: Perform a startup experiment to obtain the starting point voltage and the midpoint voltage of the power supply circuit of the button battery belonging to the mainboard. If the starting point voltage and the midpoint voltage of the power supply circuit of the button battery belonging to the mainboard are inconsistent, continue to perform the startup experiment to obtain the starting point voltage and the voltage at one-quarter distance point of the power supply circuit of the button battery belonging to the mainboard. Otherwise, obtain the ending point voltage and the voltage at three-quarter distance point of the power supply circuit of the button battery belonging to the mainboard, and so on, and continuously use the dichotomy method to determine the fault range of the power supply circuit of the button battery belonging to the mainboard.

10. A remote monitoring and early warning system for executing the battery remote monitoring and early warning method based on the Internet of Things according to any one of claims 1 to 9, characterized in that: include: The motherboard button battery status analysis module is used to perform a motherboard startup test at the target monitoring time point to determine whether the motherboard button battery's power supply to the BIOS chip is normal. If not, it determines whether the problem is with the motherboard button battery itself. If not, it executes the power supply line damage monitoring module and the battery box failure monitoring module; The power supply line damage monitoring module is used to monitor the power supply line of the button battery of the mainboard for fault damage; The battery box failure monitoring module is used to monitor the failure hazards of the battery box where the button battery of the mainboard is placed; The button battery fault processing module is used to determine the cause of power supply abnormality of the button battery belonging to the motherboard and perform corresponding optimization and early warning operations.

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