Internet-of-things-based intelligent control and power supply system and method for lockset of Internet of things

Abstract

The invention relates to the technical field of lock control, and discloses an internet-of-things lock intelligent control and power supply system and method based on the internet of things. Firstly, input information and preset user biological characteristics are subjected to multiple matching, then the abnormal state of the internet-of-things lock is judged, and internet-of-things lock control is achieved; secondly, acquiring an Internet of Things lockset parameter data set, performing data cleaning and data filling on the Internet of Things lockset parameter data set based on a dynamic sliding threshold value to obtain a processed Internet of Things lockset parameter data set, establishing a target function based on a user behavior self-adaption principle, and solving the target function by using an artemisinin optimization algorithm to obtain a target function; a global optimal solution is obtained; and finally, calculating the electric quantity of the internet-of-things lock according to the global optimal solution, and automatically switching to a standby power supply to realize intelligent power supply. By analyzing and processing the parameter data of the internet-of-things lock, the purposes of intelligent control and power supply are achieved, and the method is accurate and objective.

Description

Technical Field

[0001] The present invention relates to the technical field of lock control, and specifically to an intelligent control and power supply system and method for physical locks based on the Internet of Things. Background Art

[0002] Chinese Patent CN109920113B discloses a control method for an intelligent lock system and an intelligent lock system. The method specifically includes using a server to receive an unlocking instruction for unlocking an intelligent lock sent by an electronic device, where the unlocking instruction includes an unlocking account, and matching the unlocking account with the server. When the matching is successful, the server sends a verification instruction to the intelligent lock, and the verification instruction is the user's collected information, specifically the user's facial image. After receiving the verification instruction, the intelligent lock senses the distance between the user and the intelligent lock, and then based on the verification instruction and the distance between the user and the intelligent lock, determines whether the distance is within a preset distance range and whether the user's facial image matches the pre-stored standard facial image for recognition to obtain a final recognition result. When the recognition is successful, the server sends an unlocking command to the intelligent lock to unlock the intelligent lock. However, this invention simply relies on facial recognition to unlock the intelligent lock and does not consider the power supply system of the intelligent lock.

[0003] Traditional control methods for physical locks usually collect preset user passwords, fingerprints and other information, and then match them with the input information to achieve control, which may have problems such as abnormal remote control. At the same time, traditional control methods for physical locks do not use technologies such as the Internet of Things and do not consider the power supply system of physical locks, resulting in high power consumption and the inability to unlock normally when lacking power. Summary of the Invention

[0004] In view of the problems in the related art, the present invention provides an intelligent control and power supply system and method for physical locks based on the Internet of Things to overcome the above-mentioned technical problems existing in the prior related art.

[0005] To solve the above technical problems, the present invention is realized through the following technical solutions:

[0006] The present invention provides an intelligent control and power supply method for physical locks based on the Internet of Things, including the following steps:

[0007] S1. Obtain the input information of the physical lock, perform multiple matches between the input information and the preset user biometric characteristics to obtain a feature recognition result and achieve short-range control; then collect the parameters related to the power supply of the physical lock, determine the abnormal state of the physical lock, and transmit the abnormal state to the user terminal to achieve remote control;

[0008] S2. Obtain the parameter data set of the physical interlock based on the power supply - related parameters of the physical interlock, and perform data cleaning and data filling on the parameter data set of the physical interlock based on the dynamic sliding threshold to obtain the processed parameter data set of the physical interlock;

[0009] S3. Based on the principle of user - behavior adaptability, calculate the communication power, sensor power, and switching power of the physical interlock according to the processed parameter data set of the physical interlock, establish an objective function, and use the artemisinin optimization algorithm to solve the objective function to obtain the global optimal solution;

[0010] S4. Obtain the optimized parameters of the physical interlock according to the global optimal solution, calculate the power of the physical interlock, and set a power threshold. By comparing the power of the physical interlock and the power threshold, automatically switch to the backup power supply to achieve intelligent power supply.

[0011] This invention realizes the control of the physical interlock by performing multiple matches between the input information and the preset user biometric features, collecting the power supply - related parameters of the physical interlock, and discriminating the abnormal state of the physical interlock. The multiple - match method can ensure the security of the physical interlock, and discriminating the abnormal state can give early warnings for dangerous situations, improving the reliability of the physical interlock. Secondly, based on the dynamic sliding threshold, data cleaning and data filling are performed on the parameter data set of the physical interlock to obtain the processed parameter data set of the physical interlock. The sliding threshold can be obtained by calculating the variance transformation rate and the standard - deviation transformation rate, which can effectively distinguish normal and abnormal data. The method is simple and avoids complex calculations while ensuring the data quality. Then, based on the principle of user - behavior adaptability, an objective function is established according to the processed parameter data set of the physical interlock, and the artemisinin optimization algorithm is used to solve the objective function to obtain the global optimal solution. The principle of user - behavior adaptability conforms to the living habits of different users and has strong applicability. The artemisinin optimization algorithm has strong abilities to avoid local optima and perform local exploitation by simulating the process of artemisinin drugs treating malaria, converges quickly to help find the optimal solution quickly, solves the complex energy - consumption optimization problem in the multi - mode power - supply system, and saves electric energy to avoid waste. Finally, according to the global optimal solution, the optimized parameters of the physical interlock are obtained, the power of the physical interlock is calculated, and the backup power supply is automatically switched to achieve intelligent power supply, significantly improving the endurance and reliability of the lock in complex scenarios and helping to solve the problem of inability to unlock normally when there is a power shortage.

[0012] Preferably, the S1 includes the following steps:

[0013] S11. During the process of a user unlocking a physical interlock, obtain the input information of the physical interlock, where the input information of the physical interlock includes the input password of the physical interlock, the input fingerprint of the physical interlock, and the input face of the physical interlock; set the preset user biometric characteristics, where the preset user biometric characteristics include the preset user password, the preset user fingerprint, and the preset user face. For the first time, match the input information of the physical interlock with the preset user biometric characteristics. When the match is successful, unlock the physical interlock; when the match is unsuccessful, set the input times threshold. When the number of times of the input information of the physical interlock is less than the input times threshold, unlock the physical interlock; otherwise, at this time, the physical interlock enters the intrusion state, and multiple matches are made between the input password of the physical interlock, the input fingerprint of the physical interlock, and the input face of the physical interlock in the input information of the physical interlock and the preset user biometric characteristics in turn until the input information of the physical interlock and the preset user biometric characteristics are matched to obtain the feature recognition result and achieve short-range control;

[0014] S12. Collect the power supply related parameters of the physical interlock, where the power supply related parameters of the physical interlock include the communication wake-up period, the sensor sampling frequency, and the power supply switching voltage. During the process of a user unlocking the physical interlock, set the threshold of the power supply related parameters of the physical interlock. When the power supply related parameters of the physical interlock are less than the threshold of the power supply related parameters of the physical interlock, at this time, the physical interlock is in the normal state; otherwise, the physical interlock is in the abnormal state, and the internal Internet of Things communication module of the physical interlock transmits the abnormal state to the user terminal, and the user terminal queries the state of the physical interlock to achieve remote control.

[0015] This invention discriminates the abnormal state of the physical interlock by performing multiple matches between the input information and the preset user biometric characteristics and collecting the power supply related parameters of the physical interlock. Performing multiple matches can ensure the security of the physical interlock, discriminate the abnormal state to give early warnings for dangerous situations, improve the reliability of the physical interlock, and achieve the control of the physical interlock.

[0016] Preferably, the S2 includes the following steps:

[0017] S21. According to the power supply related parameters of the physical interlock, collect the data of the power supply related parameters of the physical interlock to form the physical interlock parameter data set A = {A1, A2, A3}, where A1 represents the communication wake-up period data set, A2 represents the sensor sampling frequency data set, and A3 represents the power supply switching voltage data set; perform data cleaning on the physical interlock parameter data set based on the dynamic sliding threshold to obtain the cleaned physical interlock parameter data set. The specific steps are as follows:

[0018] S211. Select the communication wake-up period data set A1 = {b1, b2, b3,..., b m} in the physical interlock parameter data set, where b mDenote the data of the m-th communication wake-up cycle, set the rated cycle, use the rated cycle to divide the communication wake-up cycle data set to obtain several communication wake-up cycle data subsets, and sort the several communication wake-up cycle data subsets in descending order to obtain the sorted communication wake-up cycle data set;

[0019] S212. Set a sliding window, where the size of the sliding window is equal to the number of communication wake-up cycle data in the communication wake-up cycle data subset. Place the sliding window on the first communication wake-up cycle data subset in the communication wake-up cycle data set, and calculate the variance and standard deviation of the communication wake-up cycle data in the sliding window to obtain the first variance and the first standard deviation; then move the sliding window and place it on the second communication wake-up cycle data subset in the communication wake-up cycle data set, calculate to obtain the second variance and the second standard deviation, and calculate the variance transformation rate of the first variance and the second variance and the standard deviation transformation rate of the first standard deviation and the second standard deviation; move the sliding window in turn until the communication wake-up cycle data set is traversed to obtain the variance transformation rate set A4 = {a1, a2, a3,..., a n} and the standard deviation transformation rate set A5 = {a1′, a′2, a3′,..., a′ n}, where a n represents the n-th variance transformation rate, and a′ n represents the n-th standard deviation transformation rate;

[0020] S213. Calculate the difference between adjacent standard deviation transformation rates in the standard deviation transformation rate set, set a sliding threshold. When the difference between adjacent standard deviation transformation rates is less than the sliding threshold, the communication wake-up cycle data corresponding to the adjacent standard deviation transformation rates at this time is normal data, otherwise the communication wake-up cycle data corresponding to the adjacent standard deviation transformation rates is abnormal data. Delete the abnormal data until the standard deviation transformation rate set is traversed to obtain the cleaned communication wake-up cycle data set; perform data cleaning on the sensor sampling frequency data set and the power supply switching voltage data set in turn to obtain the cleaned physical interlock device parameter data set;

[0021] S22. For the missing data in the cleaned physical interlock device parameter data set, set a data flag bit. When the data flag bit is equal to 0, it represents missing data, and when the data flag bit is equal to 1, it represents normal data; use a sliding window to divide the cleaned physical interlock device parameter data set, calculate the mean value of the physical interlock device parameter data in the sliding window, increase or decrease the mean value of the physical interlock device parameter data within the sliding threshold range to form a parameter data filling value, and then assign it to the position where the data flag bit is equal to 0 and modify the data flag bit to 1 until all data flag bits in the cleaned physical interlock device parameter data set are equal to 1 to obtain the processed physical interlock device parameter data set.

[0022] The invention effectively distinguishes normal and abnormal data by performing data cleaning and data filling on the parameter data set of the physical interlock device based on a dynamic sliding threshold, calculating the variance transformation rate and the standard deviation transformation rate to obtain the sliding threshold. The method is simple and avoids complicated calculations, while ensuring the quality of the data, and obtaining a processed parameter data set of the physical interlock device.

[0023] Preferably, S3 includes the following steps:

[0024] S31. The processed parameter data set of the physical interlock device includes a processed communication wake-up cycle data set, a processed sensor sampling frequency data set, and a processed power supply switching voltage data set. Based on the principle of user behavior adaptation, according to the processed communication wake-up cycle data set, calculate the communication power of the physical interlock device, according to the processed sensor sampling frequency data set, calculate the sensor power of the physical interlock device, according to the processed power supply switching voltage data set, calculate the switching power of the physical interlock device, and then calculate the total power of the physical interlock device. Take the minimum value of the total power of the physical interlock device as the objective function, and the calculation formula is as follows:

[0025] minF = α1P1 + α2P2 + α3P3;

[0026] Where, minF represents the objective function, α1, α2, and α3 represent dynamic weights, P1 represents the communication power of the physical interlock device, P2 represents the sensor power of the physical interlock device, and P3 represents the switching power of the physical interlock device;

[0027] S32. Take the objective function as the fitness function, and use the artemisinin optimization algorithm to solve the objective function to obtain the global optimal solution. The specific steps are as follows:

[0028] S321. Consider the process of solving the objective function as the search space. Inject artemisinin drugs into the search space. There are artemisinin particles. Randomly generate an artemisinin population. The dimension of the artemisinin population is j. The artemisinin particles in the artemisinin population represent an optimization variable. The optimization variables include the communication wake-up cycle, the sensor sampling frequency, and the power supply switching voltage. The artemisinin population enters the full elimination stage. Set the current iteration number as c and the maximum iteration number as C. Then the artemisinin drug concentration The position of the i-th artemisinin particle in the artemisinin population at the c-th iteration is x i (c), and the best position of the artemisinin particle in the artemisinin population at the c-th iteration is d1 represents a random number between the interval [0, 1]. Simulate the diffusion process of the artemisinin drug as follows:

[0029] When d1 < 0.5, the position x of the i-th artemisinin particle in the artemisinin population at the (c + 1)-th iteration i (c + 1) = xi (c) + x i (c)·β·(-1) c ;

[0030] When d1 > 0.5, at the (c + 1)-th iteration, the position x of the i-th artemisinin particle in the artemisinin population i (c + 1) = x i (c) + x′(c)·β·(-1) c ;

[0031] The artemisinin drug concentration decays with time t during the diffusion process. A probability coefficient is used to simulate the reaction time of different situations of artemisinin drugs. The probability coefficient Set d2 to represent a random number between the interval [0, 1]. When d2 < χ, repeat the simulation of the diffusion process of artemisinin drugs to cure malaria. Otherwise, the artemisinin population enters the local clearance stage;

[0032] S322. In the local clearance stage of the artemisinin population, count the current fitness function values of the artemisinin population to obtain the current best fitness function value and the current worst fitness function value, and perform normalization processing on the current fitness function values to obtain the normalized fitness function values where f i represents the fitness function value corresponding to the i-th artemisinin particle in the artemisinin population, f min represents the current worst fitness function value, and f max represents the current best fitness function value; Randomly select artemisinin particles i′, i″, and i″′ in the artemisinin population, and they follow a uniform distribution in the interval [1, j]. The positions of the artemisinin particles are denoted as x i′ (c), x i″ (c), and x i″′ (c). The coefficient k represents a random number between the interval [0.1, 0.6]. Set d3 to represent a random number between the interval [0, 1]. When , at this time, update the position of the artemisinin particle, x i (c + 1) = x i′ (c) + k·(x i″ (c) - x i″′ (c)), otherwise do not update the position of the artemisinin particle;

[0033] S323. The artemisinin population enters the consolidation stage. The positions of artemisinin particles in the artemisinin population are counted, and the corresponding fitness function values are calculated. Let d4 denote a random number between the interval [0, 1]. When d4 < 0.05, the position of the i-th artemisinin particle in the artemisinin population at the c-th iteration is used as the position of the i-th artemisinin particle in the artemisinin population at the (c + 1)-th iteration. When d4 < 0.2, the best position of the artemisinin particles in the artemisinin population at the c-th iteration is used as the position of the i-th artemisinin particle in the artemisinin population at the (c + 1)-th iteration. Otherwise, the positions of the artemisinin particles are not updated. After the artemisinin population completes all stages, a new generation of artemisinin population is generated for continuous iteration until the current iteration number reaches the maximum iteration number, at which point the iteration stops, and the final artemisinin population is obtained. The artemisinin particle corresponding to the best fitness function value is found in the final artemisinin population to obtain the global optimal solution.

[0034] The invention obtains the global optimal solution by establishing an objective function and using the artemisinin optimization algorithm to solve the objective function. It uses the principle of user behavior adaptation to conform to the living habits of different users, with strong applicability. The artemisinin optimization algorithm has strong abilities to avoid local optima and perform local exploitation by simulating the process of artemisinin drugs treating malaria. Its fast convergence helps to quickly find the optimal solution, solve the complex energy consumption optimization problem in the multi-mode power supply system, and save electric energy to avoid waste.

[0035] Preferably, the S4 includes the following steps:

[0036] S41. According to the global optimal solution, obtain the optimized communication wake-up period, the optimized sensor sampling frequency, and the optimized power supply switching voltage, which form the optimized parameters of the physical interlock device. According to the optimized parameters of the physical interlock device, obtain the minimum total power of the physical interlock device.

[0037] S42. According to the minimum total power of the physical interlock device, calculate the power of the physical interlock device, and set a power threshold. By comparing the power of the physical interlock device with the power threshold, automatically switch to the backup power supply. The specific steps are as follows:

[0038] S421. The physical interlock device operates according to the minimum total power of the physical interlock device, obtains the rated power of the physical interlock device, and then calculates the power consumption and the remaining power of the physical interlock device.

[0039] S422. Set the power threshold. When the remaining power of the physical interlock device is less than the power threshold, it enters the power warning state and switches to the backup power supply. Otherwise, it does not switch to the backup power supply, and the power warning state is transmitted to the user terminal through the internal Internet of Things communication module of the physical interlock device to achieve intelligent power supply.

[0040] The invention obtains optimized physical interlocking device parameters based on the global optimal solution, calculates the power of the physical interlocking device, and automatically switches to the backup power supply to achieve intelligent power supply, significantly improving the endurance and reliability of the lock in complex scenarios and helping to solve the problem that the lock cannot be normally unlocked when there is a power shortage.

[0041] This embodiment also discloses a system for intelligent control and power supply of a physical interlocking device based on the Internet of Things, specifically including: a physical interlocking device control module, a parameter data cleaning module, a physical interlocking device power optimization module, and a physical interlocking device power supply switching module;

[0042] The physical interlocking device control module is used to perform multiple matches on the user's biometric characteristics and determine the abnormal state of the physical interlocking device, and control the physical interlocking device;

[0043] The parameter data cleaning module is used to perform data cleaning and data filling on the physical interlocking device parameter data set based on a dynamic sliding threshold;

[0044] The physical interlocking device power optimization module is used to establish an objective function based on the power of the physical interlocking device and use the artemisinin optimization algorithm to solve for the global optimal solution;

[0045] The physical interlocking device power supply switching module is used to compare the power of the physical interlocking device with the power threshold and automatically switch the backup power supply.

[0046] The present invention has the following beneficial effects:

[0047] 1. The invention ensures the security of the physical interlocking device by performing multiple matches on the input information and the preset user biometric characteristics, determines the abnormal state of the physical interlocking device, facilitates early warning of dangerous situations, improves the reliability of the physical interlocking device, and realizes the control of the physical interlocking device.

[0048] 2. The invention performs data cleaning and data filling on the physical interlocking device parameter data set based on a dynamic sliding threshold, calculates the variance transformation rate and the standard deviation transformation rate to obtain the sliding threshold, can effectively distinguish normal and abnormal data, the method is simple and avoids complicated calculations, and at the same time ensures the quality of the data.

[0049] 3. The invention establishes an objective function, uses the artemisinin optimization algorithm to solve the objective function to obtain the global optimal solution. The artemisinin optimization algorithm has strong abilities to escape local optima and perform local exploitation by simulating the process of artemisinin drugs treating malaria, converges quickly to help find the optimal solution quickly, solves the complex energy consumption optimization problem in a multi-mode power supply system, and saves electric energy to avoid waste.

[0050] 4. The invention obtains optimized physical interlocking device parameters based on the global optimal solution, automatically switches to the backup power supply to achieve intelligent power supply, significantly improves the endurance and reliability of the lock in complex scenarios, and helps to solve the problem that the lock cannot be normally unlocked when there is a power shortage.

[0051] Of course, it is not necessary for any product implementing the present invention to achieve all the above-mentioned advantages simultaneously. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the technical solutions of the embodiments of the invention, the following will briefly introduce the drawings required for describing the embodiments. Obviously, the drawings in the following description are only some embodiments of the invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0053] Figure 1 FIG. is a schematic flow diagram of the intelligent control and power supply of an object interlocking device based on the Internet of Things provided by the present invention in the intelligent control and power supply of the object interlocking device. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0054] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0055] In the description of the present invention, it should be understood that the terms "opening", "upper", "lower", "top", "middle", "inner", etc. indicating orientation or positional relationships are only for the convenience of describing the invention and simplifying the description, rather than indicating or implying that the components or elements referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as a limitation to the invention.

[0056] Embodiment 1

[0057] Please refer to Figure 1 , this embodiment discloses an intelligent control and power supply method for an object interlocking device based on the Internet of Things, which specifically includes the following content:

[0058] S1. Obtain the input information of the object interlocking device, perform multiple matches on the input information and the preset user biometric features to obtain a feature recognition result, and achieve short-range control; then collect the power supply-related parameters of the object interlocking device, determine the abnormal state of the object interlocking device, and transmit the abnormal state to the user terminal to achieve remote control.

[0059] The said S1 includes the following steps:

[0060] S11. During the process of the user unlocking the physical interlocking device, obtain the input information of the physical interlocking device, where the input information of the physical interlocking device includes the input password of the physical interlocking device, the input fingerprint of the physical interlocking device, and the input face of the physical interlocking device; set the preset user biometric features, where the preset user biometric features include the preset user password, the preset user fingerprint, and the preset user face. For the first time, match the input information of the physical interlocking device with the preset user biometric features. When the match is successful, unlock the physical interlocking device; when the match is unsuccessful, set the input times threshold. When the number of times of the input information of the physical interlocking device is less than the input times threshold, unlock the physical interlocking device. Otherwise, at this time, the physical interlocking device enters the intrusion state, and perform multiple matches on the input password of the physical interlocking device, the input fingerprint of the physical interlocking device, and the input face of the physical interlocking device in the input information of the physical interlocking device and the preset user biometric features in turn until the input information of the physical interlocking device matches the preset user biometric features to obtain the feature recognition result and achieve short-range control;

[0061] S12. Collect the power supply related parameters of the physical interlocking device, where the power supply related parameters of the physical interlocking device include the communication wake-up period, the sensor sampling frequency, and the power supply switching voltage. During the process of the user unlocking the physical interlocking device, set the threshold of the power supply related parameters of the physical interlocking device. When the power supply related parameters of the physical interlocking device are less than the threshold of the power supply related parameters of the physical interlocking device, at this time, the physical interlocking device is in the normal state; otherwise, the physical interlocking device is in the abnormal state. The internal Internet of Things communication module of the physical interlocking device transmits the abnormal state to the user terminal, and the user terminal queries the state of the physical interlocking device to achieve remote control;

[0062] S2. According to the power supply related parameters of the physical interlocking device, obtain the parameter data set of the physical interlocking device, and perform data cleaning and data filling on the parameter data set of the physical interlocking device based on the dynamic sliding threshold to obtain the processed parameter data set of the physical interlocking device;

[0063] The S2 includes the following steps:

[0064] S21. According to the power supply related parameters of the physical interlocking device, collect the power supply related parameter data to form the parameter data set A of the physical interlocking device = {A1, A2, A3}, where A1 represents the communication wake-up period data set, A2 represents the sensor sampling frequency data set, and A3 represents the power supply switching voltage data set; perform data cleaning on the parameter data set of the physical interlocking device based on the dynamic sliding threshold to obtain the cleaned parameter data set of the physical interlocking device. The specific steps are as follows:

[0065] S211. Select the communication wake-up period data set A1 = {b1, b2, b3,..., b m} in the parameter data set of the physical interlocking device, where b mRepresents the data of the m-th communication wake-up cycle. Set the rated cycle, use the rated cycle to divide the communication wake-up cycle data set, obtain several communication wake-up cycle data subsets, and sort the several communication wake-up cycle data subsets in descending order to obtain the sorted communication wake-up cycle data set;

[0066] S212. Set a sliding window. The size of the sliding window is equal to the number of communication wake-up cycle data in the communication wake-up cycle data subset. Place the sliding window on the first communication wake-up cycle data subset in the communication wake-up cycle data set, calculate the variance and standard deviation of the communication wake-up cycle data in the sliding window to obtain the first variance and the first standard deviation; then move the sliding window and place it on the second communication wake-up cycle data subset in the communication wake-up cycle data set, calculate to obtain the second variance and the second standard deviation, and calculate the variance transformation rate of the first variance and the second variance and the standard deviation transformation rate of the first standard deviation and the second standard deviation; move the sliding window in turn until the communication wake-up cycle data set is traversed to obtain the variance transformation rate set A4 = {a1, a2, a3,..., a n} and the standard deviation transformation rate set A5 = {a1′, a′2, a3′,..., a′ n}, where a n represents the n-th variance transformation rate, and a′ n represents the n-th standard deviation transformation rate;

[0067] S213. Calculate the difference between adjacent standard deviation transformation rates in the standard deviation transformation rate set. Set a sliding threshold. When the difference between adjacent standard deviation transformation rates is less than the sliding threshold, the communication wake-up cycle data corresponding to the adjacent standard deviation transformation rate at this time is normal data, otherwise the communication wake-up cycle data corresponding to the adjacent standard deviation transformation rate is abnormal data. Delete the abnormal data until the standard deviation transformation rate set is traversed to obtain the cleaned communication wake-up cycle data set; perform data cleaning on the sensor sampling frequency data set and the power supply switching voltage data set in turn to obtain the cleaned physical interlock tool parameter data set;

[0068] S22. For the missing data in the cleaned physical interlock tool parameter data set, set a data flag bit. When the data flag bit is equal to 0, it represents missing data, and when the data flag bit is equal to 1, it represents normal data; use a sliding window to divide the cleaned physical interlock tool parameter data set, calculate the mean value of the physical interlock tool parameter data in the sliding window, increase or decrease the mean value of the physical interlock tool parameter data within the sliding threshold range to form a parameter data filling value, and then assign it to the place where the data flag bit is equal to 0 and modify the data flag bit to 1 until all data flag bits in the cleaned physical interlock tool parameter data set are equal to 1 to obtain the processed physical interlock tool parameter data set;

[0069] S3. Based on the principle of user behavior adaptation, calculate the communication power, sensor power, and switching power of the physical interlock device according to the processed physical interlock device parameter data set, establish an objective function, and use the artemisinin optimization algorithm to solve the objective function to obtain the global optimal solution;

[0070] The S3 includes the following steps:

[0071] S31. The processed physical interlock device parameter data set includes a processed communication wake-up cycle data set, a processed sensor sampling frequency data set, and a processed power supply switching voltage data set. Based on the principle of user behavior adaptation, calculate the communication power of the physical interlock device according to the processed communication wake-up cycle data set, calculate the sensor power of the physical interlock device according to the processed sensor sampling frequency data set, calculate the switching power of the physical interlock device according to the processed power supply switching voltage data set, then calculate the total power of the physical interlock device, and take the minimum value of the total power of the physical interlock device as the objective function. The calculation formula is as follows:

[0072] minF = α1P1 + α2P2 + α3P3;

[0073] where, minF represents the objective function, α1, α2, and α3 represent dynamic weights, P1 represents the communication power of the physical interlock device, P2 represents the sensor power of the physical interlock device, and P3 represents the switching power of the physical interlock device;

[0074] S32. Take the objective function as the fitness function, and use the artemisinin optimization algorithm to solve the objective function to obtain the global optimal solution. The specific steps are as follows:

[0075] S321. Consider the process of solving the objective function as a search space. Inject artemisinin drugs into the search space. There are artemisinin particles. Randomly generate an artemisinin population. The dimension of the artemisinin population is j. The artemisinin particles in the artemisinin population represent an optimization variable. The optimization variables include the communication wake-up cycle, sensor sampling frequency, and power supply switching voltage. The artemisinin population enters the full elimination stage. Set the current iteration number as c and the maximum iteration number as C. Then the artemisinin drug concentration The position of the i-th artemisinin particle in the artemisinin population at the c-th iteration is x i (c), and the best position of the artemisinin particle in the artemisinin population at the c-th iteration is d1 represents a random number between the interval [0, 1]. Simulate the diffusion process of the artemisinin drug as follows:

[0076] When d1 < 0.5, the position x of the i-th artemisinin particle in the artemisinin population at the (c + 1)-th iteration i (c + 1) = x i(c) + x i (c)·β·(-1) c ;

[0077] When d1 > 0.5, at the (c + 1)-th iteration, the position x of the i-th artemisinin particle in the artemisinin population i (c + 1) = x i (c) + x′(c)·β·(-1) c ;

[0078] The artemisinin drug concentration decays with time t during the diffusion process. The probability coefficient is used to simulate the reaction time of different situations of artemisinin drugs. The probability coefficient Set d2 to represent a random number between the interval [0, 1]. When d2 < χ, repeat the simulation of the diffusion process of artemisinin drugs to cure malaria. Otherwise, the artemisinin population enters the local clearance stage;

[0079] S322. In the local clearance stage of the artemisinin population, count the current fitness function values of the artemisinin population to obtain the current best fitness function value and the current worst fitness function value, and perform normalization processing on the current fitness function value to obtain the normalized fitness function value where f i represents the fitness function value corresponding to the i-th artemisinin particle in the artemisinin population, f min represents the current worst fitness function value, f max represents the current best fitness function value; Randomly select artemisinin particles i′, i″, and i″′ in the artemisinin population, and they follow a uniform distribution in the interval [1, j]. The artemisinin particle positions are respectively denoted as x i′ (c), x i″ (c) and x i″′ (c). The coefficient k represents a random number between the interval [0.1, 0.6]. Set d3 to represent a random number between the interval [0, 1]. When , at this time, update the artemisinin particle position, x i (c + 1) = x i′ (c) + k·(x i″ (c) - x i″′ (c)), otherwise do not update the artemisinin particle position;

[0080] S323. The artemisinin population enters the consolidation stage. The positions of artemisinin particles in the artemisinin population are counted, and the corresponding fitness function values are calculated. Let d4 represent a random number between the interval [0, 1]. When d4 < 0.05, the position of the i-th artemisinin particle in the artemisinin population at the c-th iteration is used as the position of the i-th artemisinin particle in the artemisinin population at the (c + 1)-th iteration. When d4 < 0.2, the best position of the artemisinin particles in the artemisinin population at the c-th iteration is used as the position of the i-th artemisinin particle in the artemisinin population at the (c + 1)-th iteration. Otherwise, the positions of the artemisinin particles are not updated. After the artemisinin population completes all stages, a new generation of artemisinin population is generated for continuous iteration until the current iteration number reaches the maximum iteration number, at which point the iteration stops, and the final artemisinin population is obtained. The artemisinin particle corresponding to the best fitness function value is found in the final artemisinin population to obtain the global optimal solution.

[0081] S4. Based on the global optimal solution, the optimized parameters of the physical interlock device are obtained, the power of the physical interlock device is calculated, and a power threshold is set. By comparing the power of the physical interlock device with the power threshold, the standby power supply is automatically switched to achieve intelligent power supply.

[0082] S4 includes the following steps:

[0083] S41. Based on the global optimal solution, the optimized communication wake-up period, the optimized sensor sampling frequency, and the optimized power supply switching voltage are obtained, which together form the optimized parameters of the physical interlock device. The minimum total power of the physical interlock device is obtained according to the optimized parameters of the physical interlock device.

[0084] S42. Based on the minimum total power of the physical interlock device, the power of the physical interlock device is calculated, and a power threshold is set. By comparing the power of the physical interlock device with the power threshold, the standby power supply is automatically switched. The specific steps are as follows:

[0085] S421. The physical interlock device operates according to the minimum total power of the physical interlock device, obtains the rated power of the physical interlock device, and then calculates the power consumption and the remaining power of the physical interlock device.

[0086] S422. A power threshold is set. When the remaining power of the physical interlock device is less than the power threshold, it enters the power warning state and switches to the standby power supply. Otherwise, it does not switch to the standby power supply, and the power warning state is transmitted to the user terminal through the internal IoT communication module of the physical interlock device to achieve intelligent power supply.

[0087] Embodiment 2

[0088] This embodiment also discloses a system for the intelligent control and power supply method of a physical interlock device based on the Internet of Things, which specifically includes: a physical interlock device control module, a parameter data cleaning module, a physical interlock device power optimization module, and a physical interlock device power supply switching module;

[0089] The physical interlock control module is used to perform multiple matches on the user's biometric characteristics, determine the abnormal state of the physical interlock, and control the physical interlock;

[0090] The parameter data cleaning module is used to clean and fill the physical interlock parameter data set based on a dynamic sliding threshold;

[0091] The physical interlock power optimization module is used to establish an objective function according to the physical interlock power, and use the artemisinin optimization algorithm to solve for the global optimal solution;

[0092] The physical interlock power supply switching module is used to compare the power of the physical interlock with the power threshold and automatically switch the backup power supply.

[0093] In the description of this specification, the description with reference to terms such as "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0094] The preferred embodiments of the invention disclosed above are only used to help explain the invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific embodiments described. Obviously, many modifications and variations can be made according to the content of this specification. These embodiments are selected and specifically described in this specification in order to better explain the principle and practical application of the invention, so that those skilled in the art in the relevant technical field can understand and utilize the invention well.

Claims

1. An intelligent control and power supply method for physical interlocking devices based on the Internet of Things, characterized in that It includes the following steps: S1. Obtain the input information of the physical interlock device. By performing multiple matches between the input information and the preset user biometric characteristics, obtain the feature recognition result to achieve short-range control. Then collect the parameters related to the power supply of the physical interlock device, determine the abnormal state of the physical interlock device, and transmit the abnormal state to the user terminal to achieve remote control; S2. According to the parameters related to the power supply of the physical interlock device, obtain the parameter data set of the physical interlock device. Based on the dynamic sliding threshold, perform data cleaning and data filling on the parameter data set of the physical interlock device to obtain the processed parameter data set of the physical interlock device; S3. Based on the principle of user behavior adaptability, calculate the communication power, sensor power, and switching power of the physical interlock device according to the processed parameter data set of the physical interlock device, establish an objective function, solve the objective function, and obtain the global optimal solution; S4. Obtain the optimized parameters of the physical interlock device according to the global optimal solution, calculate the power of the physical interlock device, and set the power threshold. By comparing the power of the physical interlock device and the power threshold, automatically switch to the backup power supply to achieve intelligent power supply.

2. The intelligent control and power supply method for an Internet of Things-based physical interlock according to claim 1, wherein The S1 includes the following steps: S11. Obtain the input information of the physical interlock device, set the preset user biometric characteristics, and match the input information of the physical interlock device with the preset user biometric characteristics. When the match is unsuccessful, perform multiple matches, otherwise unlock the physical interlock device to obtain the feature recognition result to achieve short-range control; S12. Collect the parameters related to the power supply of the physical interlock device, set the threshold of the parameters related to the power supply of the physical interlock device, compare the parameters related to the power supply of the physical interlock device with the threshold of the parameters related to the power supply of the physical interlock device, determine whether the physical interlock device is in an abnormal state, transmit the abnormal state to the user terminal, and the user terminal queries the state of the physical interlock device to achieve remote control.

3. The intelligent control and power supply method for an Internet of Things-based physical interlock according to claim 2, characterized in that, The S2 includes the following steps: S21. According to the parameters related to the power supply of the physical interlock device, collect the parameter data related to the power supply of the physical interlock device to form the parameter data set of the physical interlock device; set a sliding window, and based on the dynamic sliding threshold, perform data cleaning on the parameter data set of the physical interlock device to obtain the cleaned parameter data set of the physical interlock device; S22. For the missing data in the cleaned parameter data set of the physical interlock device, set a data flag bit, calculate the mean value of the parameter data in the sliding window to form a parameter data filling value, and assign it to the data flag bit to obtain the processed parameter data set of the physical interlock device.

4. A method for intelligent control and power supply of an Internet of Things-based physical interlock, according to claim 3, characterized in that The S21 includes the following steps: S211. Select the communication wake-up period data set in the parameter data set of the physical interlock device and divide it to obtain several communication wake-up period data subsets. Sort the several communication wake-up period data subsets in descending order to obtain the sorted communication wake-up period data set; S212. Set a sliding window, and the sliding window continuously moves in the sorted communication wake-up period data set. Calculate the variance change rate and standard deviation change rate between the sliding windows to obtain the variance change rate set and the standard deviation change rate set; S213. Calculate the difference between adjacent standard deviation transformation rates in the set of standard deviation transformation rates, set a sliding threshold, compare the difference between adjacent standard deviation transformation rates with the sliding threshold, determine whether the communication wake-up cycle data corresponding to the adjacent standard deviation transformation rates is abnormal data, and delete the abnormal data to obtain a cleaned set of communication wake-up cycle data; After cleaning the data in the set of physical interlock tool parameter data in sequence, a cleaned set of physical interlock tool parameter data is formed.

5. The intelligent control and power supply method for an Internet of Things-based physical interlock according to claim 4, characterized in that, The said S3 includes the following steps: S31. Based on the principle of user behavior adaptation, according to the processed set of physical interlock tool parameter data, calculate the communication power of the physical interlock tool, the sensor power of the physical interlock tool, and the switching power of the physical interlock tool to obtain the total power of the physical interlock tool. Take the minimum value of the total power of the physical interlock tool as the objective function, and the calculation formula is as follows: minF = α1P1 + α2P2 + α3P3; Among them, minF represents the objective function, α1, α2, and α3 represent dynamic weights, P1 represents the communication power of the physical interlock tool, P2 represents the sensor power of the physical interlock tool, and P3 represents the switching power of the physical interlock tool; S32. Use the objective function as the fitness function and use the artemisinin optimization algorithm to solve the objective function to obtain the global optimal solution.

6. The intelligent control and power supply method for an Internet of Things-based physical interlock according to claim 5, characterized in that, The said S32 includes the following steps: S321. Consider the process of solving the objective function as a search space. Inject artemisinin drugs into the search space, where there are artemisinin particles. Randomly generate an artemisinin population. The dimension of the artemisinin population is j. An artemisinin particle in the artemisinin population represents an optimization variable, and the optimization variables include the communication wake-up period, the sensor sampling frequency, and the power supply switching voltage. The artemisinin population enters the overall elimination stage. Set the current iteration number as c and the maximum iteration number as C. Then the artemisinin drug concentration The position of the i-th artemisinin particle in the artemisinin population at the c-th iteration is x i (c). The best position of the artemisinin particle in the artemisinin population at the c-th iteration is d1 represents a random number between the interval [0, 1]. The diffusion process of artemisinin drugs is simulated as follows: When d1 < 0.5, the position x of the i-th artemisinin particle in the artemisinin population at the (c + 1)-th iteration i (c + 1) = x i (c) + x i (c)·β·(-1) c ; When d1 > 0.5, the position x of the i-th artemisinin particle in the artemisinin population at the (c + 1)-th iteration i (c + 1) = x i (c) + x′(c)·β·(-1) c ; The artemisinin drug concentration decays with time t during the diffusion process, and the probability coefficient is used to simulate the reaction time of artemisinin drugs in different situations. The probability coefficient Set d2 to represent a random number between the interval [0, 1]. When d2 < χ, repeatedly simulate the diffusion process of artemisinin drugs to cure malaria; otherwise, the artemisinin population enters the local clearance stage. S322. During the local elimination stage of the artemisinin population, the current fitness function value of the artemisinin population is statistically analyzed to obtain the current best fitness function value and the current worst fitness function value, and the current fitness function value is normalized to obtain the normalized fitness function value. Randomly select artemisinin particles i′, i″, and i″′ from the artemisinin population, and they follow a uniform distribution in the interval [1, j]. The positions of the artemisinin particles are denoted as x i′ (c), x i″ (c), and x i″′ (c). The coefficient k represents a random number in the interval [0.1, 0.6]. Set d3 to represent a random number in the interval [0, 1]. When , at this time, the position of the artemisinin particle is updated, x i (c + 1) = x i′ (c)+k·(x i″ (c)-x i″′ (c)), otherwise the position of the artemisinin particle is not updated. S323. The artemisinin population enters the consolidation stage. Statistically analyze the positions of artemisinin particles in the artemisinin population and calculate the corresponding fitness function values. Set d4 to represent a random number in the interval [0, 1]. When d4 < 0.05, use the position of the i-th artemisinin particle in the artemisinin population at the c-th iteration as the position of the i-th artemisinin particle in the artemisinin population at the (c + 1)-th iteration. When d4 < 0.2, use the best position of the artemisinin particles in the artemisinin population at the c-th iteration as the position of the i-th artemisinin particle in the artemisinin population at the (c + 1)-th iteration. Otherwise, do not update the positions of the artemisinin particles. After the artemisinin population completes all stages, generate the next generation of artemisinin population for continuous iteration until the current iteration number reaches the maximum iteration number, then stop the iteration to obtain the final artemisinin population, and find the artemisinin particle corresponding to the best fitness function value in the final artemisinin population to obtain the global optimal solution.

7. A method for intelligent control and power supply of an Internet of Things-based physical lock, according to claim 6, characterized in that, The said S4 includes the following steps: S41. According to the global optimal solution, obtain the optimized physical interlock tool parameters, and obtain the minimum value of the total power of the physical interlock tool according to the optimized physical interlock tool parameters; S42. According to the minimum value of the total power of the physical interlock tool, calculate the power of the physical interlock tool, and set a power threshold. By comparing the power of the physical interlock tool with the power threshold, automatically switch to the backup power supply.

8. A method for intelligent control and power supply of an Internet of Things-based physical interlock, according to claim 7, characterized in that The said S42 includes the following steps: S421. The physical interlock tool operates according to the minimum value of the total power of the physical interlock tool, obtains the rated power of the physical interlock tool, and then calculates the power consumption of the physical interlock tool and the remaining power of the physical interlock tool; S422. Set a power threshold. When the remaining power of the physical interlock tool is less than the power threshold, enter the power warning state at this time and switch to the backup power supply. Otherwise, do not switch to the backup power supply, and transmit the power warning state to the user terminal to achieve intelligent power supply.

9. A system for implementing the method for intelligent control and power supply of an Internet of Things-based physical interlock as described in any one of claims 1-8, characterized in that, Specifically include: Biological interlock control module, parameter data cleaning module, biological interlock power optimization module and biological interlock power supply switching module; The biological interlock control module is used to perform multiple matches on the user's biological characteristics, determine the abnormal state of the biological interlock, and control the biological interlock; The parameter data cleaning module is used to perform data cleaning and data filling on the biological interlock parameter data set based on a dynamic sliding threshold; The biological interlock power optimization module is used to establish an objective function according to the biological interlock power, and use the artemisinin optimization algorithm to solve for the global optimal solution; The biological interlock power supply switching module is used to compare the power of the biological interlock with the power threshold and automatically switch the backup power supply.

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