Battery service time prediction method, system and equipment of intelligent lock and medium

Abstract

The invention relates to the technical field of battery management, and discloses a battery use time prediction method, system and device of an intelligent lock and a medium, the method comprises the following steps: obtaining an operation state of the intelligent lock and a battery state, the operation state being corresponding state data of a preset composition of the intelligent lock during operation; determining power consumption of the intelligent lock based on the state data; determining the remaining capacity of the intelligent lock based on the battery state; and predicting the battery use time of the smart lock based on the remaining capacity and the power consumption. According to the method, the current battery service time is predicted by calculating the total power consumption of the intelligent lock and the remaining power of the battery in consideration of the power consumption change of each component in the intelligent lock, so that the prediction precision of the battery service time can be improved, the use experience of a user can be improved, and the use requirement of the intelligent lock is met.

Description

Technical Field

[0001] The present invention relates to the field of battery management technology, and in particular to a method, system, device and medium for predicting battery usage time of a smart lock. Background Art

[0002] Smart locks are generally powered by their built-in batteries. In actual applications, in order to prevent low battery power from affecting the use of smart lock functions, accurately judging the battery life is one of the important capabilities of smart locks.

[0003] Currently, most smart locks have a battery power detection function. The relevant technology estimates the battery life by counting the current remaining power and the power consumption of the door lock. However, since the power consumption of each internal component of the smart lock is very different when it is in working state and in sleep state, the accuracy of estimating the remaining power by battery usage time in the original technology is poor, which seriously affects the user experience. Summary of the invention

[0004] In view of this, the present invention provides a method, system, device and medium for predicting the battery usage time of a smart lock, so as to solve the problem that the existing battery usage time prediction ignores the consumption changes of various internal components of the smart lock under different states, resulting in low accuracy and poor effect of battery usage time prediction, and it is difficult to meet the use requirements of the smart lock.

[0005] In a first aspect, the present invention provides a method for predicting battery life of a smart lock, the method comprising:

[0006] Obtain the operating status and battery status of the smart lock, where the operating status is the status data corresponding to the preset components of the smart lock during operation;

[0007] determining the power consumption of the smart lock based on the status data;

[0008] Determine the remaining power of the smart lock based on the battery status;

[0009] Predict the battery life of the smart lock based on remaining power and power consumption.

[0010] The present invention determines the power consumption and remaining power of the smart lock respectively through the operating status and battery status of the smart lock, and predicts the remaining battery life of the smart lock based on the power consumption and remaining power. It can fully consider the power consumption changes of each component inside the smart lock, help to improve the prediction accuracy of the battery life, which not only improves the user experience, but also meets the use requirements of the smart lock.

[0011] In an optional implementation, the power consumption includes a first power consumption and a second power consumption, wherein the first power consumption is the cumulative sum of the stable power consumption corresponding to the preset components of the smart lock when running, and the second power consumption is the cumulative sum of the dynamic power consumption corresponding to the preset components of the smart lock when running; determining the power consumption of the smart lock based on the state data includes:

[0012] Based on the component type of the preset components of the smart lock, determine the power consumption type of the corresponding components, wherein the preset components include but are not limited to the main control module, cat's eye module, biometric module, motor, human body sensing module, LED light, clock, sampling circuit and battery, and the power consumption type includes stable power consumption and dynamic power consumption;

[0013] For each of the preset components, obtain the stable power consumption and dynamic power consumption corresponding to the smart lock respectively;

[0014] The power consumption of the smart lock is determined based on all stable power consumption and dynamic power consumption.

[0015] The present invention obtains stable power consumption and dynamic power consumption respectively through the component types inside the smart lock, and determines the corresponding total power consumption of the smart lock based on the stable power consumption and dynamic power consumption. It can fully consider the power consumption changes of each component inside the smart lock and improve the prediction accuracy of battery life.

[0016] In an optional implementation, obtaining the dynamic power consumption corresponding to the smart lock includes:

[0017] When the preset components of the smart lock are running, obtaining multiple signal strengths of the smart lock;

[0018] Calculate the mean of all signal intensities to obtain the target signal strength;

[0019] Based on the target signal strength, the corresponding preset component power consumption is determined from the first preset relationship, and the preset component power consumption is determined as the dynamic power consumption corresponding to the smart lock, wherein the first preset relationship is a mapping relationship between different signal strengths and power consumption.

[0020] The present invention determines the preset component power consumption through the target signal strength of the smart lock and its corresponding first preset relationship, which can ensure the calculation accuracy of the power consumption and further help improve the prediction accuracy of subsequent battery usage time.

[0021] In an optional implementation, obtaining the dynamic power consumption corresponding to the smart lock includes:

[0022] In response to a preset unlocking operation of the smart lock by the user, the preset components of the smart lock are controlled to perform unlocking identification, and the first time of the smart lock is obtained through the clock;

[0023] When the smart lock outputs a door lock control instruction, the second time of the smart lock is obtained through the clock;

[0024] Determine the unlocking recognition duration of the smart lock based on the first time and the second time; and determine the preset component power consumption as the dynamic power consumption corresponding to the smart lock.

[0025] The present invention determines the preset component power consumption by the corresponding working time and preset unlocking power of the smart lock unlocking identification, and determines it as the dynamic power consumption of the smart lock, which helps to ensure the calculation accuracy of the dynamic power consumption and improve the prediction accuracy of the subsequent battery usage time.

[0026] In an optional implementation, obtaining the dynamic power consumption corresponding to the smart lock includes:

[0027] When the preset composition of the smart lock is running, a sampling resistor and a plurality of sampling voltages of the preset composition are obtained through a sampling circuit;

[0028] For each sampling voltage, the corresponding sampling current is calculated according to the sampling resistance;

[0029] After screening the target current from all sampled currents, the preset component power consumption is calculated based on the target current, and the preset component power consumption is determined as the dynamic power consumption corresponding to the smart lock.

[0030] The present invention determines the corresponding current through the resistor of a preset composition and the sampled voltage during its operation, determines the power consumption of the preset composition based on the current, and determines it as the dynamic power consumption of the smart lock, which helps to ensure the calculation accuracy of the dynamic power consumption and improve the prediction accuracy of the subsequent battery usage time.

[0031] In an optional implementation, the battery status includes the factory power and the battery current, and determining the remaining power of the smart lock based on the battery status includes:

[0032] Determining the corresponding battery power consumption from a second preset relationship based on the battery current, where the second preset relationship is a mapping relationship between different battery currents and power consumption;

[0033] The factory power is subtracted from the battery power consumption to obtain the current power, and the current power is determined as the remaining power of the smart lock.

[0034] The present invention determines the remaining power of the smart lock through the factory power of the battery, the battery current, and the mapping relationship between different set battery currents and power consumption, which can ensure the calculation accuracy of the remaining power and thereby improve the subsequent accurate prediction of the battery usage time.

[0035] In an optional implementation, after predicting the battery life of the smart lock based on the remaining power and the power consumption, the battery life prediction method of the smart lock further includes:

[0036] Determine whether the battery usage time is less than a preset time threshold;

[0037] If yes, a charging reminder is given;

[0038] If not, return to the step of obtaining the operating status and battery status of the smart lock.

[0039] The present invention determines whether to provide a battery charging reminder based on the relationship between the battery usage time and a set time threshold, which can not only reduce battery wear and extend the battery life, but also ensure the normal operation of the smart lock.

[0040] In an optional implementation, after predicting the battery life of the smart lock based on the remaining power and the power consumption, the battery life prediction method of the smart lock further includes:

[0041] Acquire a first voltage of the battery through a preset acquisition device;

[0042] Calculating a second voltage of the battery based on the power consumption of the smart lock;

[0043] calculating an absolute difference based on the first voltage and the second voltage;

[0044] When the absolute difference is greater than the preset difference threshold, an early warning is performed.

[0045] The present invention obtains the actual voltage of the battery and the battery voltage obtained by reverse calculation based on the predicted battery usage time, and designs a judgment process of the absolute difference between the two and a set difference threshold. It can effectively monitor the abnormal power consumption of the smart lock, and perform early warning processing in time when the power consumption is abnormal, thereby greatly ensuring the normal operation of the smart lock.

[0046] In a second aspect, the present invention provides a battery life prediction system for a smart lock, the system comprising:

[0047] An acquisition module is used to obtain the operating status and battery status of the smart lock, where the operating status is the status data corresponding to the preset components of the smart lock during operation;

[0048] A first determination module, configured to determine the power consumption of the smart lock based on the status data;

[0049] A second determination module, used to determine the remaining power of the smart lock based on the battery status;

[0050] The prediction module is used to predict the battery life of the smart lock based on the remaining power and power consumption.

[0051] The battery usage time prediction system of the smart lock of the present invention fully considers the power consumption changes of each component inside the smart lock, which can greatly improve the prediction accuracy of the battery usage time, while improving the user experience and meeting the usage requirements of the smart lock.

[0052] In a third aspect, the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to execute a method for predicting battery life of a smart lock according to the first aspect or any corresponding embodiment thereof.

[0053] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute a method for predicting battery life of a smart lock according to the first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0055] Figure 1 is a flow chart of a method for predicting battery life of a smart lock according to an embodiment of the present invention;

[0056] Figure 2 is a flow chart of a method for predicting battery life of another smart lock according to an embodiment of the present invention;

[0057] Figure 3 It is a schematic diagram of the internal structure of the smart lock;

[0058] Figure 4 This is a flowchart of the calculation of the remaining battery days;

[0059] Figure 5 is a structural block diagram of a battery usage time prediction system for a smart lock according to an embodiment of the present invention;

[0060] Figure 6 It is a schematic diagram of the structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0061] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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 those skilled in the art without creative work are within the scope of protection of the present invention.

[0062] An embodiment of the present invention provides an embodiment of a method for predicting the battery life of a smart lock. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0063] In this embodiment, a method for predicting the battery life of a smart lock is provided. Figure 1 is a flow chart of a method for predicting battery life of a smart lock according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0064] Step S101, obtaining the operating status and battery status of the smart lock, where the operating status is the status data corresponding to the preset components of the smart lock during operation.

[0065] It should be noted that the specific contents of the preset components, operating status and battery status in this embodiment are not limited here, and can be adaptively adjusted based on actual needs. For example, the preset component is a cat's eye camera, and its corresponding operating status includes face recognition data, liveness detection data, monitoring data, etc.; the battery status includes battery type, power, temperature, current, voltage, etc., which are only for exemplary explanation.

[0066] Step S102, determining the power consumption of the smart lock based on the status data.

[0067] It should be noted that the power consumption in this embodiment represents the total power consumption of all components integrated inside the smart lock, including the stable power consumption consumed by the corresponding actions of the internal components that are difficult to be affected by the outside world (also called determinable power consumption), such as the power consumption of the smart lock body in a sleep state; and the dynamic power consumption consumed by the corresponding actions of the internal components that are easily affected by the outside world (also called uncertain power consumption), such as the power consumption consumed by the rotation of the motor and the power consumption consumed by the cat's eye to keep it alive. This is only for illustrative purposes.

[0068] Step S103, determining the remaining power of the smart lock based on the battery status.

[0069] It should be noted that the specific method of determining the remaining power of the smart lock based on the battery status in this embodiment is not limited here, and is adaptively adjusted based on actual needs. For example, if the battery status is voltage data, a voltage-remaining power fitting curve of the same type of battery can be obtained through offline testing, and the current voltage measured is substituted into the curve to obtain the corresponding remaining power, which is only an exemplary description.

[0070] Step S104, predicting the battery life of the smart lock based on the remaining power and power consumption.

[0071] In this embodiment, the method of predicting the battery life of the smart lock based on the remaining power and power consumption is not limited here, and is determined based on the adaptability of actual needs. For example, the battery life is determined based on the ratio of the remaining power and power consumption; or the remaining power-power consumption-usage time fitting curve of the same type of battery is obtained through offline testing, and the calculated remaining power and power consumption are substituted into the curve to obtain the battery life, which is only an exemplary description.

[0072] The battery usage time prediction method of the smart lock in the embodiment of the present invention determines the power consumption and remaining power of the smart lock respectively through the operating status and battery status of the smart lock, and predicts the remaining battery usage time of the smart lock based on the power consumption and remaining power. It can fully consider the changes in power consumption of each component inside the smart lock, help to improve the prediction accuracy of the battery usage time, not only improves the user experience, but also meets the use requirements of the smart lock.

[0073] In this embodiment, a method for predicting the battery life of a smart lock is provided. Figure 2 FIG. 1 is a flow chart of another method for predicting battery life of a smart lock according to an embodiment of the present invention. Figure 2 As shown, the process includes the following steps:

[0074] Step S201, obtain the operating status and battery status of the smart lock, where the operating status is the status data corresponding to the preset components of the smart lock during operation. Figure 1 Step S101 of the illustrated embodiment will not be described in detail here.

[0075] Step S202, determining the power consumption of the smart lock based on the status data.

[0076] In this embodiment, the power consumption includes a first power consumption and a second power consumption, wherein the first power consumption is the cumulative sum of the stable power consumption corresponding to the preset components of the smart lock during operation, and the second power consumption is the cumulative sum of the dynamic power consumption corresponding to the preset components of the smart lock during operation. It should be noted that the stable power consumption (also called determinable power consumption) is the power consumption generated when the components integrated inside the smart lock that are difficult to be affected by the outside world (such as LED lights, clocks, etc.) perform corresponding actions; the dynamic power consumption (also called undeterminable power consumption) is the power consumption generated when the components integrated inside the smart lock that are easily affected by the outside world (such as motors, face recognition modules, cat eyes, etc.) are in different operating states (such as sleep or work). Specifically, the above step S202 includes:

[0077] Step S2021, based on the component type of the preset components of the smart lock, determine the power consumption type of the corresponding component, wherein the preset components include but are not limited to a main control module, a cat's eye module, a biometric module, a motor, a human body sensing module, an LED light, a clock, a sampling circuit and a battery, and the power consumption type includes stable power consumption and dynamic power consumption.

[0078] It should be noted that the specific number of preset components in this embodiment is not limited here, and is adaptively adjusted based on the actual structure optimization of the smart lock. For example, after a new component is added to the smart lock, it can be added to the preset components, and the corresponding power consumption type can be determined according to its corresponding function and component type, and the power consumption can be adaptively calculated based on the power consumption type.

[0079] Step S2022: For each component in the preset components, obtain the stable power consumption and dynamic power consumption corresponding to the smart lock respectively.

[0080] It should be noted that in this embodiment, the uncertain power consumption is generated by the cat's eye module, biometric module and motor integrated inside the smart lock; the determined power consumption is generated by the internal components of the smart lock other than the above three components (namely the main control module, human body sensing module, LED light, clock, sampling circuit and battery), among which, the determined power consumption can be calculated according to the relevant formula after testing and recording with a current tester.

[0081] In this embodiment, the second power consumption includes the cat's eye power consumption of the cat's eye module. Specifically, the dynamic power consumption corresponding to the smart lock is obtained in the above step S2022, including:

[0082] Step A1, when the cat's eye module is running, obtain multiple signal strengths of the smart lock.

[0083] In this embodiment, the specific method of obtaining the signal strength is based on the adaptive setting of the communication type of the smart lock. For example, for a smart lock using Wi-Fi communication, the corresponding signal strength is determined by obtaining the current distance between the smart lock and the Wi-Fi signal source, which is only an exemplary description.

[0084] Step A2: Calculate the mean of all signal strengths to obtain the target signal strength.

[0085] Step A3, determine the corresponding cat's eye power consumption from the first preset relationship based on the target signal strength, and determine the cat's eye power consumption as the dynamic power consumption corresponding to the smart lock cat's eye module, wherein the first preset relationship is a mapping relationship between different signal strengths and power consumption.

[0086] In the embodiment of the present invention, the cat's eye power consumption consumed by the cat's eye module is determined by the target signal strength of the smart lock and its corresponding first preset relationship, which can ensure the calculation accuracy of the cat's eye power consumption and further help improve the prediction accuracy of subsequent battery usage time.

[0087] In this embodiment, the second power consumption also includes the recognition power consumption of the biometric recognition module, which is used for the opening and closing control recognition of the smart lock, and generates the door lock control instruction based on the recognition result. It should be noted that the unlocking method included in the biometric recognition module is not limited here, and is adaptively adjusted based on actual needs. For example, the biometric recognition module includes fingerprint, password, face, iris, voice and other unlocking recognition methods, which are only used as an exemplary explanation. Specifically, the dynamic power consumption corresponding to the smart lock obtained in the above step S2022 includes:

[0088] Step B1, in response to the user's preset unlocking operation on the smart lock, controls the biometric module to work, and obtains the first time of the smart lock through the clock.

[0089] In this embodiment, the specific content of the preset unlocking operation is not limited here, and is adaptively adjusted based on the unlocking recognition method actually equipped with the smart lock. For example, if the biometric recognition module is a fingerprint unlocking recognition method, the corresponding preset unlocking operation is that the user places a set finger on the recognition area of ​​the smart lock to generate a corresponding recognition function trigger signal to control the operation of the biometric recognition module.

[0090] Step B2, when it is detected that the biometric module generates a door lock control instruction, the second time of the smart lock is obtained through the clock.

[0091] In this embodiment, the door lock control instruction includes an unlocking instruction and a locking instruction, which is determined according to the recognition result of the biometric recognition module. For example, when the biometric recognition module fails to recognize the user's fingerprint, it indicates that the user's legal identity verification has failed, and a locking instruction is generated accordingly to keep the door lock body of the smart lock closed.

[0092] Step B3, determining the unlocking recognition time of the smart lock based on the first time and the second time.

[0093] In this embodiment, the unlocking recognition time represents the total time taken by the biometric recognition module to verify the legitimate identity of the user, and its specific value is determined based on the working time of the biometric recognition module, that is, recognition time = second time - first time.

[0094] Step B4, calculating the recognition power consumption based on the unlocking recognition time and the preset unlocking power consumption, and determining the recognition power consumption as the dynamic power consumption corresponding to the biometric recognition module of the smart lock.

[0095] It should be noted that if the smart lock also includes the cat's eye power consumption of the cat's eye module, the identification power consumption and the cat's eye power consumption are summed to obtain the first cumulative power consumption, and the first cumulative power consumption is determined as the second power consumption of the smart lock.

[0096] In this embodiment, the specific content of the preset unlocking power is not limited here, and is adaptively adjusted based on the unlocking identification method and the corresponding power consumption test results of the actual smart lock. For example, the biometric recognition module is a fingerprint unlocking recognition method, and the corresponding preset unlocking power is obtained by testing the fingerprint unlocking recognition process offline multiple times and counting the power consumption corresponding to each recognition process, which is only for exemplary explanation.

[0097] In the embodiment of the present invention, the recognition power consumption of the biometric module is determined by the working time corresponding to the smart lock biometric recognition and the preset unlocking power, and it is added to the cat's eye power consumption to obtain the second power consumption of the smart lock, which helps to ensure the calculation accuracy of the second power consumption and improve the prediction accuracy of subsequent battery usage time.

[0098] In this embodiment, the second power consumption also includes the motor power consumption of the motor. It should be noted that the motor in the smart lock is mainly used to control the rotation of the lock body to realize the opening / closing operation of the smart lock. Specifically, the dynamic power consumption corresponding to the smart lock in the above step S2022 includes:

[0099] Step C1, when the motor is running, obtaining a sampling resistance and a plurality of sampling voltages of the motor through a sampling circuit.

[0100] In this embodiment, the specific value of the sampling resistor is determined based on the adaptability of the actual motor type.

[0101] Step C2: for each sampled voltage, the corresponding sampled current is calculated according to the sampled resistor.

[0102] Step C3, after selecting the target current from all sampled currents, the motor power consumption is calculated based on the target current, and the motor power consumption is determined as the dynamic power consumption corresponding to the smart lock motor.

[0103] It should be noted that if the smart lock also includes the cat's eye power consumption of the cat's eye module and the recognition power consumption of the biometric recognition module, the motor power consumption and the first cumulative power consumption (that is, the sum of the recognition power consumption and the cat's eye power consumption) are summed to obtain the second cumulative power consumption, and the second cumulative power consumption is determined as the second power consumption of the smart lock.

[0104] In this embodiment, the specific method for determining the target current is not limited here, and is adaptively adjusted based on actual needs. For example, all sampled currents are averaged to obtain the target current; or all sampled currents are filtered and then averaged to obtain the target current, which is only an example.

[0105] In an embodiment of the present invention, the corresponding current is determined by the resistance of the motor and the sampled voltage during its operation, and the motor power consumption consumed by the motor module is determined based on the current. The power consumption is added to the cat's eye power consumption and the identification power consumption to obtain the second power consumption of the smart lock, which helps to ensure the calculation accuracy of the second power consumption and improve the prediction accuracy of subsequent battery usage time.

[0106] Step S2023, determine the power consumption of the smart lock based on all stable power consumption and dynamic power consumption.

[0107] In this embodiment, the power consumption of the smart lock is obtained by summing up the stable power consumption and dynamic power consumption obtained by solving each preset component of the smart lock.

[0108] In the embodiment of the present invention, the stable power consumption and dynamic power consumption are respectively obtained through the component types inside the smart lock, and the total power consumption corresponding to the smart lock is determined based on the stable power consumption and the dynamic power consumption. This can fully consider the changes in power consumption of each component inside the smart lock and improve the prediction accuracy of the battery life.

[0109] Step S203, determining the remaining power of the smart lock based on the battery status.

[0110] In this embodiment, the battery status includes the factory power and battery current. It should be noted that the factory power is determined based on the adaptability of the actual battery type. For example, the factory power of a certain model of smart lock is 5000mAh. Specifically, the above step S203 includes:

[0111] Step S2031, determining the corresponding battery power consumption from a second preset relationship based on the battery current, where the second preset relationship is a mapping relationship between different battery currents and power consumption.

[0112] Step S2032, subtract the factory power from the battery power consumption to obtain the current power, and determine the current power as the remaining power of the smart lock.

[0113] In the embodiment of the present invention, the remaining power of the smart lock is determined by the factory power of the battery, the battery current, and the mapping relationship between different set battery currents and power consumption, which can ensure the calculation accuracy of the remaining power and thereby improve the subsequent accurate prediction of the battery usage time.

[0114] Step S204: predict the battery life of the smart lock based on the remaining power and power consumption. Figure 1 Step S101 of the illustrated embodiment will not be described in detail here.

[0115] In practical applications, if the battery is at low power, charging it can better maintain the health and stability of the battery. Therefore, after predicting the battery life of the smart lock based on the remaining power and power consumption, the battery life prediction method of the smart lock of this embodiment also includes:

[0116] Step E1, determining whether the battery usage time is less than a preset time threshold.

[0117] In this embodiment, the specific value of the preset time threshold is adaptively set based on actual needs. It should be noted that in this embodiment, by determining the relationship between the battery usage time and the set time threshold, it is actually to determine whether the battery power is at a low level (i.e., the power threshold for battery charging), and the corresponding charging reminder determination condition can be adjusted according to the actual application scenario.

[0118] Step E2: If yes, then a charging reminder is given.

[0119] Step E3: if not, return to the step of obtaining the operating status and battery status of the smart lock.

[0120] In the embodiment of the present invention, whether to provide a battery charging reminder is determined by the relationship between the battery usage time and the set time threshold, which can not only reduce the loss of the battery and thus extend the battery life, but also ensure the normal operation of the smart lock.

[0121] In actual applications, in order to ensure the health of the battery and further extend the battery life, it is also necessary to perform real-time abnormal monitoring of the battery power consumption. Therefore, after predicting the battery life of the smart lock based on the remaining power and power consumption, the smart lock battery life prediction method of this embodiment also includes:

[0122] Step F1, obtaining a first voltage of a battery through a preset acquisition device.

[0123] In this embodiment, the specific type of the preset acquisition device is set based on the adaptability of conventional voltage acquisition devices in the art.

[0124] Step F2, calculating the second voltage of the battery based on the power consumption of the smart lock.

[0125] Step F3, calculating an absolute difference based on the first voltage and the second voltage.

[0126] Step F4: when the absolute difference is greater than a preset difference threshold, a warning process is performed.

[0127] In this embodiment, the specific value of the preset difference threshold is not limited here and is adaptively adjusted based on actual needs.

[0128] In a specific embodiment, the total power consumption of the device is obtained based on the calculation of the power consumption of each component inside the smart lock, and the current theoretical voltage of the battery is deduced based on it. If the difference between the theoretical voltage and the actual voltage collected is gradually increasing, it can be determined that there is an abnormality in the power consumption. The abnormal information is pushed to the user through a mobile phone APP that communicates with the smart lock, or the user is informed in time by text message / local voice broadcast that there is an abnormality and maintenance is required.

[0129] In the embodiment of the present invention, by obtaining the actual voltage of the battery and the battery voltage obtained by reverse calculation based on the predicted battery usage time, and designing a judgment process between the absolute difference between the two and the set difference threshold, it is possible to effectively monitor the abnormal power consumption of the smart lock, and perform early warning processing in time when the power consumption is abnormal, thereby greatly ensuring the normal operation of the smart lock.

[0130] In a specific embodiment, for the smart lock currently used by the user, the working content of the smart lock is divided into: actions that are difficult to be affected by the outside world and whose power consumption can be determined (such as the power consumption of the lock body in sleep mode and the power consumption of the fingerprint head in operation), and actions that are affected by the outside world and whose power consumption cannot be determined (such as the power consumption of the motor rotation and the power consumption of the cat's eye to keep alive). For the specific internal structure of the smart lock, please refer to Figure 3 .Depend on Figure 3 It can be seen that the total power consumption of the smart lock includes determinable power consumption and undeterminable power consumption, among which the specific composition of each type of power consumption includes:

[0131] 1. MCU (Microcontroller Unit), that is, the main control module or main control chip, is used to integrate and calculate the power consumption of each module and calculate the total power consumption.

[0132] 2. Cat's eye module: that is, a camera used to observe the situation outside the door.

[0133] 3. Biometric module: used to verify identity, including face, fingerprint, iris and other unlocking recognition methods.

[0134] 4. Proximity sensing module: used to determine the proximity of human body and give a signal to MCU.

[0135] 5. Touch chip: used to detect human touch operation and send a signal to MCU after touching. It should be noted that the touch chip and proximity sensing module constitute the human body sensing module, which is used to detect and identify the presence of human body.

[0136] 6. Light (i.e. LED light): works in synergy with touch chip.

[0137] 7. Motor: used to rotate the lock body to open or close the door.

[0138] 8. Sampling circuit: convert the current used by the motor into voltage and sample it for the MCU.

[0139] 9. Lithium battery: supplies power to the entire circuit.

[0140] 10. RTC (Real Time Clock): used to calculate the usage time of functions.

[0141] In a specific embodiment, based on the above-mentioned smart lock and the set power consumption type, a battery remaining days calculation scheme is proposed. Figure 4 The figure is a flowchart of the calculation of the remaining battery days. Figure 4 It can be seen that the process includes:

[0142] 1. Internal test power consumption.

[0143] In this embodiment, the internal test power consumption is to calculate the determinable power consumption of the smart lock offline. Specifically, the current tester is used to record the power consumption after the test, and the determinable power consumption is obtained based on the record.

[0144] 2. User use.

[0145] In this embodiment, this step is used to obtain different operation records of the user for subsequent power consumption calculation.

[0146] 3. Calculate the changing power consumption.

[0147] In this embodiment, this step is to calculate the uncertain power consumption, which includes three types, and the corresponding calculation method is used to obtain the power consumption. For example, for the power consumption of the motor, the change of the sampled voltage of the motor itself can be used to estimate the current consumed by the door opening action, and the actual scene records are accumulated by the user opening and closing the door repeatedly, and the highest and lowest values ​​are excluded. The processing algorithm processes the records and then calculates the actual power consumption of the user opening the door based on it. Specifically, the calculation steps of the motor power consumption are as follows:

[0148] (1) Based on the sampling resistor of the motor chip, the current used by the motor in real time is calculated through the ADC (Analog-to-digital converter).

[0149] (2) Calculate the power consumption of this door opening through relevant algorithms. Specifically, first calculate the current data through real-time sampling of voltage and sampling resistance; then calculate the energy consumed by the motor based on the sampling changes, that is, the sampling rate and sampling data. For example, if the sampling rate is 1k (i.e. 1000 times per second), and the sampling data is 1, 2, 3, 4, 5, etc., then the total amount corresponding to 1000mA is 0.139mAh.

[0150] (3) After the number of times the user uses the door increases, the highest and lowest values ​​can be excluded to calculate the relatively real power consumption. Specifically, after multiple samplings, the maximum and minimum power consumption values ​​of each door opening are excluded, and the average is calculated to obtain the final power consumption. For example, if a user opens the door 10 times a day, the corresponding power consumption values ​​for the 10 times are 7.5, 8, 8, 8, 8, 8, 8, 8, 8, and 8.3, respectively. The corresponding average is 8. It should be noted that in the relevant software of the smart lock, it can be set to remove 10% of the upper and lower limits of the data, and only retain the middle 80% of the data as valid data to calculate the average value.

[0151] In a specific embodiment, for the cat eye standby current, the cat eye obtains the signal strength to roughly infer the cat eye's sleep power consumption. Specifically, the cat eye sleep power consumption calculation steps are as follows:

[0152] (1) Obtain signal strength through cat's eye.

[0153] (2) By obtaining the signal strength value multiple times and performing calculations, the dormant power consumption of the cat's eye is obtained.

[0154] In a specific embodiment, for face recognition power consumption, since the main source of face recognition power consumption is the power consumption of the infrared fill light, the flashing duration can be obtained through the internal RTC timing of the smart lock, thereby calculating the recognition power consumption.

[0155] Specifically, the calculation steps of face recognition power consumption are as follows:

[0156] (1) Face recognition starts working and RTC starts timing.

[0157] (2) When face verification fails or succeeds, RTC stops timing and the calculation time is obtained.

[0158] (3) By calculating the time and face recognition current, the corresponding power consumption, i.e., face recognition power consumption, is obtained.

[0159] In this embodiment, the average power consumption of the user's face recognition is tested by the power consumption tester. It should be noted that the face recognition time of different users is different, so the user's door opening time can be obtained according to the RTC acquisition time, and the average current of the recognition flow obtained by the test can be multiplied to calculate the power consumption used for this door opening. For example, if the user opens the door for 1S, the corresponding power consumption value is 1; if the door is opened for 5S, the corresponding power consumption value is 5.

[0160] 4. Establish the average power consumption of users.

[0161] In this embodiment, as the number of actual uses by the user increases, the calculation result of the uncertain power consumption becomes more accurate and in line with the actual situation of the user. The final result of the power consumption can be characterized by calculating the average working condition of the user. Specifically, the power consumption of the lock itself is continuously tested (i.e., the internal test power consumption), and its own battery model is established (characterizing the determinable power consumption); the power consumption of each operation can be calculated by combining the usage of each module in the smart lock; for some uncertain power consumption, calculations can be performed based on the actual usage scenarios of the user to obtain the power consumption that meets the user's usage scenarios.

[0162] 5. Calculate the remaining battery life.

[0163] In this embodiment, the remaining battery time that the user can use and the recommended charging time can be accurately calculated based on the capacity of the inserted battery (such as a certain type of lithium battery with a capacity of 7800mAh) minus the user's daily power consumption (i.e., the user's average power consumption). Specifically, the remaining power and the battery sampling voltage can be compared regularly to verify the accuracy of the power consumption calculation; at the same time, if there is unreasonable power consumption behavior, the user will be notified in time for maintenance.

[0164] In a specific embodiment, by calculating that the average power consumption of the user's smart lock is 50mAh, and the user's battery capacity is 2000mAh, the actual remaining days of the battery that can be used are 40 days; and when the battery power is 1000mAh (i.e. 20% power), the user needs to be reminded to charge. Specifically, the remaining battery days calculation scheme of this embodiment can directly determine the remaining time of the user's use of the smart lock, and can also determine its own power consumption problem; at the same time, the lithium battery usage is regularly calibrated according to the results of the internal power consumption test to complete the battery calibration.

[0165] In summary, the battery usage time prediction method of the smart lock of the present invention takes into account the changes in power consumption of each component inside the smart lock, which not only improves the prediction accuracy of the battery usage time, but also improves the user experience and meets the usage requirements of the smart lock.

[0166] In this embodiment, a battery life prediction system for a smart lock is also provided, which is used to implement the above embodiments and preferred implementations, and will not be repeated here. As used below, the term "module" refers to a combination of software and / or hardware that can implement a predetermined function. Although the system described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0167] The present invention provides a battery life prediction system for a smart lock. Figure 5 As shown, the system includes:

[0168] The acquisition module 501 is used to obtain the operating status and battery status of the smart lock. The operating status is the status data corresponding to the preset components of the smart lock during operation.

[0169] The first determination module 502 is used to determine the power consumption of the smart lock based on the status data.

[0170] The second determination module 503 is used to determine the remaining power of the smart lock based on the battery status.

[0171] The prediction module 504 is used to predict the battery life of the smart lock based on the remaining power and power consumption.

[0172] In some optional embodiments, the first determination module 502 includes: a first calculation submodule, a second calculation submodule and a third calculation submodule; wherein the first calculation submodule is used to determine the power consumption type of the corresponding component based on the component type of the preset component of the smart lock, wherein the preset component includes but is not limited to a main control module, a cat's eye module, a biometric module, a motor, a human body sensing module, an LED light, a clock, a sampling circuit and a battery, and the power consumption type includes stable power consumption and dynamic power consumption; the second calculation submodule is used to obtain the stable power consumption and dynamic power consumption corresponding to the smart lock for each component in the preset component; the third calculation submodule is used to determine the power consumption of the smart lock based on all stable power consumption and dynamic power consumption.

[0173] In some optional embodiments, the first calculation submodule includes: a first calculation unit, a second calculation unit and a third calculation unit; wherein the first calculation unit is used to obtain multiple signal strengths of the smart lock when the preset components of the smart lock are running; perform mean calculation on all signal strengths to obtain the target signal strength; determine the corresponding preset component power consumption from the first preset relationship based on the target signal strength, and determine the preset component power consumption as the dynamic power consumption corresponding to the smart lock, wherein the first preset relationship is a mapping relationship between different signal strengths and power consumption; the second calculation unit is used to respond to the user's preset unlocking operation on the smart lock, control the preset components of the smart lock to perform unlocking identification, and obtain the smart lock through the clock. a first time; when it is detected that the smart lock outputs a door lock control instruction, the second time of the smart lock is obtained through the clock; the unlocking recognition time of the smart lock is determined based on the first time and the second time; the preset component power consumption is calculated based on the unlocking recognition time and the preset unlocking power, and the preset component power consumption is determined as the dynamic power consumption corresponding to the smart lock; a third calculation unit is used to obtain the sampling resistance and multiple sampling voltages of the preset component through the sampling circuit when the preset component of the smart lock is running; for each sampling voltage, the corresponding sampling current is calculated according to the sampling resistance; after screening the target current from all the sampling currents, the preset component power consumption is calculated based on the target current, and the preset component power consumption is determined as the dynamic power consumption corresponding to the smart lock.

[0174] In some optional embodiments, the second determination module 503 includes: a first determination submodule and a second determination submodule; wherein the first determination submodule is used to determine the corresponding battery power consumption from a second preset relationship based on the battery current, and the second preset relationship is a mapping relationship between different battery currents and power consumption; the second determination submodule is used to subtract the factory power consumption from the battery power consumption to obtain the current power, and determine the current power as the remaining power of the smart lock.

[0175] In some optional embodiments, the system also includes: a reminder module and an early warning module; wherein the reminder module is used to determine whether the battery usage time is less than a preset time threshold; if so, a charging reminder is issued; if not, returning to the step of obtaining the operating status and battery status of the smart lock; the early warning module is used to obtain the first voltage of the battery through a preset acquisition device; calculate the second voltage of the battery based on the power consumption of the smart lock; calculate the absolute difference based on the first voltage and the second voltage; when the absolute difference is greater than the preset difference threshold, an early warning process is performed.

[0176] The further functional description of each of the above modules is the same as that of the above corresponding embodiments and will not be repeated here.

[0177] The battery life prediction system of the smart lock in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0178] The battery usage time prediction system of the smart lock in the embodiment of the present invention takes into account the changes in power consumption of each internal component of the smart lock in different states, and predicts the current battery usage time by calculating the total power consumption of the smart lock and the remaining battery power. This can improve the accuracy and efficiency of battery usage time prediction, further enhance the user experience, and meet the usage requirements of the smart lock.

[0179] The present invention also provides a computer device, see Figure 6 , Figure 6 is a schematic diagram of the structure of the above-mentioned computer device provided in an optional embodiment of the present invention, such as Figure 6 As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 6 A processor 10 is taken as an example.

[0180] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0181] The memory 20 stores instructions executable by at least one processor 10, so that at least one processor 10 executes the method shown in the above embodiment.

[0182] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0183] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0184] The computer device also includes a communication interface 30, which is used for the main control chip to communicate with other devices or a communication network.

[0185] A computer-readable storage medium is also provided in an embodiment of the present invention. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium and downloaded through a network, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor main control chip or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor or hardware, the method shown in the above embodiment is implemented.

[0186] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A method for predicting battery life of a smart lock, characterized in that: The method comprises: Obtaining the operating status and battery status of the smart lock, wherein the operating status is status data corresponding to the preset components of the smart lock during operation; determining the power consumption of the smart lock based on the status data; Determine the remaining power of the smart lock based on the battery status; The battery usage time of the smart lock is predicted based on the remaining power and the power consumption.

2. The method for predicting battery life of a smart lock according to claim 1, characterized in that: The power consumption includes a first power consumption and a second power consumption, wherein the first power consumption is the cumulative sum of stable power consumption corresponding to the preset components of the smart lock when running, and the second power consumption is the cumulative sum of dynamic power consumption corresponding to the preset components of the smart lock when running; determining the power consumption of the smart lock based on the state data includes: Based on the component type of the preset components of the smart lock, determine the power consumption type of the corresponding components, wherein the preset components include but are not limited to the main control module, the cat's eye module, the biometric module, the motor, the human body sensing module, the LED light, the clock, the sampling circuit and the battery, and the power consumption type includes stable power consumption and dynamic power consumption; For each of the preset components, respectively obtain the stable power consumption and dynamic power consumption corresponding to the smart lock; The power consumption of the smart lock is determined based on all stable power consumption and dynamic power consumption.

3. The method for predicting battery life of a smart lock according to claim 2, characterized in that: Obtaining the dynamic power consumption corresponding to the smart lock includes: When the preset components of the smart lock are running, obtaining multiple signal strengths of the smart lock; Calculate the mean of all signal intensities to obtain the target signal strength; Based on the target signal strength, the corresponding preset component power consumption is determined from the first preset relationship, and the preset component power consumption is determined as the dynamic power consumption corresponding to the smart lock, wherein the first preset relationship is a mapping relationship between different signal strengths and power consumption.

4. The method for predicting battery life of a smart lock according to claim 2, characterized in that: Obtaining the dynamic power consumption corresponding to the smart lock includes: In response to a preset unlocking operation of the smart lock by the user, controlling the preset components of the smart lock to perform unlocking identification, and obtaining the first time of the smart lock through the clock; When it is detected that the smart lock outputs a door lock control instruction, obtaining a second time of the smart lock through a clock; Determine the unlocking identification duration of the smart lock based on the first time and the second time; The preset component power consumption is calculated based on the unlocking identification time and the preset unlocking power, and the preset component power consumption is determined as the dynamic power consumption corresponding to the smart lock.

5. The method for predicting battery life of a smart lock according to claim 2, characterized in that: Obtaining the dynamic power consumption corresponding to the smart lock includes: When the preset composition of the smart lock is running, a sampling resistor and a plurality of sampling voltages of the preset composition are obtained through a sampling circuit; For each sampled voltage, a corresponding sampled current is calculated according to the sampled resistor; After screening the target current from all sampled currents, the preset component power consumption is calculated based on the target current, and the preset component power consumption is determined as the dynamic power consumption corresponding to the smart lock.

6. The method for predicting battery life of a smart lock according to claim 1, characterized in that: The battery status includes the factory power and the battery current, and determining the remaining power of the smart lock based on the battery status includes: Determining the corresponding battery power consumption from a second preset relationship based on the battery current, where the second preset relationship is a mapping relationship between different battery currents and power consumption; The factory power consumption is subtracted from the battery power consumption to obtain the current power consumption, and the current power consumption is determined as the remaining power of the smart lock.

7. The method for predicting battery life of a smart lock according to any one of claims 1 to 6, characterized in that: After predicting the battery usage time of the smart lock based on the remaining power and the power consumption, the method further includes: Determine whether the battery usage time is less than a preset time threshold; If yes, a charging reminder is given; If not, return to the step of obtaining the operating status and battery status of the smart lock.

8. The method for predicting battery life of a smart lock according to any one of claims 1 to 6, characterized in that: After predicting the battery usage time of the smart lock based on the remaining power and the power consumption, the method further includes: Acquire a first voltage of the battery through a preset acquisition device; Calculating a second voltage of the battery based on the power consumption of the smart lock; calculating an absolute difference based on the first voltage and the second voltage; When the absolute difference is greater than a preset difference threshold, an early warning process is performed.

9. A battery life prediction system for a smart lock, characterized in that: The system comprises: An acquisition module, used to acquire the operating status and battery status of the smart lock, wherein the operating status is the status data corresponding to the preset components of the smart lock when running; A first determination module, configured to determine the power consumption of the smart lock based on the status data; A second determination module, configured to determine the remaining power of the smart lock based on the battery status; A prediction module is used to predict the battery usage time of the smart lock based on the remaining power and the power consumption.

10. A computer device, characterized in that: The device includes: a memory and a processor, the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the battery usage time prediction method for the smart lock described in any one of claims 1 to 8 by executing the computer instructions.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the battery usage time prediction method for a smart lock according to any one of claims 1 to 8.

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