RFID-based intelligent electronic lock, case and unlocking control system

Abstract

The application provides an RFID-based intelligent electronic lock, a locker and an unlocking control system, and relates to the field of intelligent electronic locks.The unlocking control system comprises an RFID positioning module, which is used to determine the position of the locker based on a plurality of calibration RFID tags arranged in the locker library, a plurality of RFID readers and an RFID tag arranged in the lock body; an unlocking control module, which is used to determine a plurality of target intelligent electronic locks; a state monitoring module, which is used to determine the tilt state of the lock body based on the tilt angle data collected by a plurality of tilt angle sensors of the target intelligent electronic lock; an abnormality judgment module, which is used to judge whether there is an abnormal intelligent electronic lock based on the position of the locker and the tilt state of the lock body, and generate a batch unlocking instruction if not; and a batch unlocking module, which is used to issue the batch unlocking instruction to instruct the plurality of target intelligent electronic locks to perform consensus verification, and then perform batch unlocking. The application has the advantages of realizing batch unlocking of the locker, and improving the unlocking efficiency and precision.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of intelligent electronic locks, in particular to an RFID-based intelligent electronic lock, a cash box and a lock opening control system. BACKGROUND

[0002] When valuable articles such as gold, jewelry, cash, etc. are transported, a cash box is usually used.

[0003] In the related art, a method of opening and closing a cash box based on encryption and decryption technology can be used to open multiple locks with one key, and record the time of opening and closing the lock, thereby solving the problem of user management of personnel, equipment, locks and keys. However, it is usually only used for management of specific cash boxes, and the opening efficiency is low. The vault needs to open hundreds of locks in a short time to handle the transfer of cash boxes from the jurisdictional network every day. The passive lock cannot be opened in batches, and the opening efficiency is low. The personnel need to continuously bend down to open the lock, which is labor-intensive. On the other hand, the passive lock includes a corresponding electronic key, and the key custody, use and handover system is complex. Physical keys need to be kept by multiple people, and the bank key management regulations must be strictly followed. The compliance inspection and management cost is high.

[0004] Therefore, it is necessary to provide an RFID-based intelligent electronic lock, a cash box and a lock opening control system to realize batch opening of the cash box, without manual storage of physical or electronic keys, and to improve the opening efficiency and accuracy. SUMMARY

[0005] The present application provides an RFID-based intelligent electronic lock, including a lock body and a lock beam. First and second slots are formed at both ends of the lock body. The first end of the lock beam is located in the first slot. When in the locked state, the second end of the lock beam is located in the second slot. When in the unlocked state, the second end of the lock beam is located outside the second slot. An RFID tag, a controller and a drive assembly are further provided in the lock body. The RFID tag is used to record cash box information and determine the position of the cash box. The controller is used to control the drive assembly to drive the second end of the lock beam to separate from the second slot based on a batch unlocking instruction. A state acquisition assembly and a wireless communication assembly electrically connected to the controller are further provided in the lock body. The state acquisition assembly includes a plurality of inclination sensors arranged at multiple positions of the lock body. The state acquisition assembly is used to upload the inclination angle data collected by the plurality of inclination sensors to the lock opening control system through the wireless communication assembly. The inclination angle data collected by the plurality of inclination sensors is used to instruct the lock opening control system to determine the inclination state of the lock body based on the vibration data collected by the plurality of vibration sensors, and to issue a batch unlocking instruction to the wireless communication assembly based on the cash box information, the position of the cash box and the inclination state of the lock body.

[0006] Further, the inclination sensors at the plurality of positions of the lock body include: disposing a plurality of test inclination sensors on the lock body of the test cashbox; determining a plurality of cashbox inclination test scenarios; obtaining inclination angle data collected by the plurality of test inclination sensors under each cashbox inclination test scenario; determining candidate test inclination sensors based on the inclination angle data collected by each test inclination sensor under each cashbox inclination test scenario; determining a plurality of target test inclination sensors by deduplicating the candidate test inclination sensors based on the inclination angle data collected by each candidate test inclination sensor under each cashbox inclination test scenario; and determining the inclination sensors at the plurality of positions of the lock body based on the setting positions of the plurality of target test inclination sensors.

[0007] Further, determining the candidate test inclination sensors based on the inclination angle data collected by each test inclination sensor under each cashbox inclination test scenario includes: for each test inclination sensor, calculating an angle sensing effectiveness coefficient of the test inclination sensor based on the inclination angle data collected by the test inclination sensor under each cashbox inclination test scenario; determining the candidate test inclination sensors based on the angle sensing effectiveness coefficient of each test inclination sensor; and determining a plurality of target test inclination sensors by deduplicating the candidate test inclination sensors based on the inclination angle data collected by each candidate test inclination sensor under each cashbox inclination test scenario, including: for any two candidate test inclination sensors, calculating an angle sensing similarity based on the inclination angle data collected by the two candidate test inclination sensors under each cashbox inclination test scenario; determining a plurality of sensor clusters based on the angle sensing similarity of any two candidate test inclination sensors through a clustering algorithm; generating a plurality of candidate setting schemes based on the plurality of candidate test inclination sensors and the plurality of sensor clusters; establishing a fitness function; for each setting scheme, calculating a fitness of the setting scheme based on the fitness function and the inclination angle data collected by the candidate test inclination sensors included in the setting scheme under each cashbox inclination test scenario; determining an optimal setting scheme based on the fitness of each setting scheme through genetic algorithm; and determining the plurality of target test inclination sensors based on the optimal setting scheme.

[0008] The application provides a lock opening control system for controlling a plurality of RFID-based intelligent electronic locks to be opened in batches, comprising: an RFID positioning module for determining the position of a cash box based on a plurality of calibration RFID tags arranged in a cash box library, a plurality of RFID readers and an RFID tag arranged in a lock body; an opening control module for receiving a batch opening request initiated by a user terminal and determining a plurality of target intelligent electronic locks based on the batch opening request initiated by the user terminal; a state monitoring module for determining the tilt state of the lock body of the target intelligent electronic lock based on the tilt angle data collected by a plurality of tilt angle sensors of the target intelligent electronic lock; an abnormality determination module for determining whether there is an abnormal intelligent electronic lock among the plurality of target intelligent electronic locks based on the position of the cash box and the tilt state of the lock body of the target intelligent electronic lock, sending a prompt information to the user terminal if it is determined that there is an abnormal intelligent electronic lock, and generating a batch opening instruction based on the plurality of target intelligent electronic locks if it is determined that there is no abnormal intelligent electronic lock; and a batch opening module for issuing the batch opening instruction to the wireless communication components of the plurality of target intelligent electronic locks, the batch opening instruction being used to instruct the plurality of target intelligent electronic locks to perform consensus verification and to be opened in batches after the consensus verification is passed.

[0009] Further, the RFID positioning module determines the position of the cash box based on a plurality of calibration RFID tags arranged in a cash box library, a plurality of RFID readers and an RFID tag arranged in a lock body, comprising: determining a plurality of target RFID readers from the plurality of RFID readers based on the strength of the signal of the RFID tag arranged in the lock body received by the plurality of RFID readers; determining a plurality of target calibration RFID tags from the plurality of calibration RFID tags based on the plurality of target RFID readers; and determining the position of the cash box based on the strength of the current signal of the plurality of target calibration RFID tags received by the plurality of target RFID readers and the strength of the signal of the RFID tag arranged in the lock body.

[0010] Further, the RFID positioning module determines the position of the cash box based on the strength of the current signal of the plurality of target calibration RFID tags received by the plurality of target RFID readers and the strength of the signal of the RFID tag arranged in the lock body, comprising: correcting the strength of the signal of the RFID tag arranged in the lock body received by the plurality of target RFID readers based on the strength of the current signal of the plurality of target calibration RFID tags received by the plurality of target RFID readers and the strength of the interference-free signal of the plurality of target calibration RFID tags received by the plurality of target RFID readers, to generate the corrected strength of the signal of the RFID tag arranged in the lock body received by the plurality of target RFID readers; and determining the position of the cash box based on the corrected strength of the signal of the RFID tag arranged in the lock body received by the plurality of target RFID readers.

[0011] Further, the state monitoring module determines the lock body tilt state of the target intelligent electronic lock based on the tilt angle data collected by the plurality of tilt angle sensors of the target intelligent electronic lock, comprising: establishing a multiple regression model, wherein the independent variables of the multiple regression model include the tilt angle data collected by the plurality of tilt angle sensors, and the dependent variable of the multiple regression model is the lock body tilt angle; for each time point, determining the lock body tilt angle at the time point based on the tilt angle data collected by the plurality of tilt angle sensors at the time point through the multiple regression model; and determining the lock body stability and the tilt angle of the target intelligent electronic lock based on the lock body tilt angles of a plurality of consecutive time points.

[0012] Further, the abnormality determination module determines whether there is an abnormal intelligent electronic lock among the plurality of target intelligent electronic locks based on the case position and the lock body tilt state of the target intelligent electronic lock, comprising: determining whether the target intelligent electronic lock is located in the unlocking area based on the case position; if the target intelligent electronic lock is not located in the unlocking area, determining that the target intelligent electronic lock is an abnormal intelligent electronic lock; if the target intelligent electronic lock is located in the unlocking area, determining the number of cases above the target intelligent electronic lock based on the case position; if the number of cases above the target intelligent electronic lock is greater than the number threshold, determining that the target intelligent electronic lock is an abnormal intelligent electronic lock; if the number of cases above the target intelligent electronic lock is less than or equal to the number threshold, determining whether the lock body stability of the target intelligent electronic lock is greater than the lock body stability threshold; if the lock body stability of the target intelligent electronic lock is less than the lock body stability threshold, determining that the target intelligent electronic lock is an abnormal intelligent electronic lock; if the lock body stability of the target intelligent electronic lock is greater than or equal to the lock body stability threshold, determining whether the tilt angle of the target intelligent electronic lock is greater than the tilt angle threshold; and if the tilt angle of the target intelligent electronic lock is greater than the tilt angle threshold, determining that the target intelligent electronic lock is an abnormal intelligent electronic lock.

[0013] Further, the batch unlocking instruction instructs the plurality of target intelligent electronic locks to perform consensus verification, comprising: performing unlocking time consensus verification based on the batch unlocking instruction by the plurality of target intelligent electronic locks; after the unlocking time consensus verification is passed, performing unlocking permission consensus verification based on the batch unlocking instruction; and after the unlocking permission consensus verification is passed, performing unlocking association consensus verification based on the batch unlocking instruction.

[0014] The application provides a case, which applies the above-mentioned unlocking control system.

[0015] Compared with the prior art, the intelligent electronic lock, the case and the unlocking control system based on RFID provided by the application have at least the following beneficial effects:

[0016] 1、RFID tags are used to record the information of the boxes and determine their positions, realizing integrated management of information. This makes the flow, monitoring and tracing of the boxes more convenient, allowing managers to grasp the status and position of the boxes in real time and improving the efficiency of logistics and warehouse management. The controller controls the driving assembly to drive the second end of the lock beam to separate from the second slot based on the batch unlocking instruction, realizing the remote batch unlocking function. In the case of needing to open multiple intelligent electronic locks at the same time, manual operation is not required, greatly improving the unlocking efficiency and being suitable for large-scale box management scenarios. The inclination sensor in the state acquisition assembly can collect the inclination angle data of the lock body in real time and upload it to the unlocking control system through the wireless communication assembly. This allows the unlocking control system to timely understand the inclination state of the lock body and provide data support for subsequent decision-making. The unlocking control system can issue batch unlocking instructions based on the box information, box position and lock body inclination state. This linkage control mechanism makes the unlocking operation of the intelligent electronic lock more intelligent and precise, allowing flexible adjustment according to actual conditions.

[0017] 2、By setting multiple test inclination sensors on the lock body of the test box and obtaining the inclination angle data collected by them in different box inclination test scenarios, the angle sensing effectiveness coefficient of each test inclination sensor is calculated to determine the candidate test inclination sensor. This method can filter out sensors that accurately and reliably sense changes in inclination angle, improving the accuracy of state monitoring. Based on the inclination angle data collected by the candidate test inclination sensors in each box inclination test scenario, the angle sensing similarity is calculated, and multiple sensor clusters are determined through clustering algorithms. Then, according to the fitness function and the inclination angle data collected by the candidate test inclination sensors in each box inclination test scenario in the set scheme, the fitness of the set scheme is calculated, and the optimal set scheme is determined through genetic algorithms to determine multiple target test inclination sensors. This de-duplication optimization method can avoid redundant sensor settings, improve sensor utilization efficiency, and ensure the accuracy and reliability of monitoring data.

[0018] 3、By judging whether the target smart electronic lock is located in the unlocking area, the smart electronic lock in abnormal position can be effectively identified, preventing unlocking operation in non-designated area, ensuring the safety of important items such as cash boxes, and avoiding illegal personnel from stealing or damaging by using the lock in abnormal position. Determining the number of cash boxes above the target smart electronic lock and comparing it with the number threshold can timely find the unreasonable stacking of cash boxes. If there are too many cash boxes above, it may cause the lock body to bear too much pressure, affecting the normal use and safety of the lock, and timely determination of abnormality can avoid potential safety hazards. Judging whether the lock body stability of the target smart electronic lock is greater than the lock body stability threshold can detect whether the lock body is in a stable state. Unstable lock body may mean that the lock body is disturbed or damaged by external force, affecting its normal locking and unlocking functions, and unlocking in an unstable or inclined state may cause the items stored in the cash box to fall out of the cash box, resulting in loss of items. Therefore, through the test of the lock body stability and inclination angle of the target smart electronic lock, the unlocking operation in inappropriate scenarios can be effectively avoided.

[0019] 4、The unlocking time consensus verification ensures that the batch unlocking operation is performed within the preset safe time range. This can effectively prevent unauthorized unlocking attempts during non-working hours or sensitive time periods, such as at night or during holidays, avoiding security vulnerabilities due to time factors and reducing the risk of internal personnel violating regulations or external illegal intrusion. The unlocking permission consensus verification strictly verifies the user end initiating the batch unlocking request based on the unlocking permission information stored in each target smart electronic lock. Only users with corresponding permissions can perform unlocking operations, preventing unauthorized personnel from obtaining unlocking permissions, ensuring the safety of important items such as cash boxes, and preventing information leakage or asset loss. The unlocking association consensus verification analyzes the relationship between the unlocking records of multiple target smart electronic locks to determine whether there is a reasonable batch unlocking situation. This can prevent individual smart electronic locks from being illegally unlocked alone, ensuring that the unlocking operation complies with business logic and safety specifications, and avoiding security risks caused by abnormal association relationships. The three consensus verification mechanisms of unlocking time, unlocking permission, and unlocking association verify the batch unlocking instruction from different angles. This multi-verification method greatly improves the reliability and fault tolerance of the system, so that even if one verification link fails or is bypassed, the other verification links can still function, ensuring the safety of the unlocking operation. BRIEF DESCRIPTION OF DRAWINGS

[0020] The present specification will be further illustrated in the form of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting, and in these embodiments, the same reference numbers represent the same structures, wherein:

[0021] Figure 1is a structural schematic diagram of an RFID-based intelligent electronic lock according to some embodiments of the present specification;

[0022] Figure 2 is a flowchart of determining a plurality of target test-inclination sensors according to some embodiments of the present specification;

[0023] Figure 3 is a module schematic diagram of an unlocking control system according to some embodiments of the present specification.

[0024] In the figure, 110, lock body; 1101, first slot; 1102, second slot; 120, lock beam; 130, driving assembly. DETAILED DESCRIPTION

[0025] In order to more clearly illustrate the technical solutions of the embodiments of the present specification, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some examples or embodiments of the present specification, and for those skilled in the art, without paying creative labor, the present specification can also be applied to other similar scenarios according to these drawings. Unless it is obvious from the language environment or otherwise stated, the same reference numbers in the figures represent the same structure or operation.

[0026] Figure 1 is a structural schematic diagram of an RFID-based intelligent electronic lock according to some embodiments of the present specification, as Figure 1 shown, the RFID-based intelligent electronic lock includes a lock body and a lock beam, the lock body has a first slot and a second slot at both ends, the first end of the lock beam is located in the first slot, when in the locked state, the second end of the lock beam is located in the second slot, when in the unlocked state, the second end of the lock beam is located outside the second slot.

[0027] Specifically, the lock beam is in the shape of U.

[0028] The lock body is further provided with an RFID tag, a controller and a driving assembly, the RFID tag is used to record the information of the cabinet, the RFID tag is also used to determine the position of the cabinet, the controller is used to control the driving assembly to drive the second end of the lock beam to separate from the second slot based on the batch unlocking instruction.

[0029] Specifically, the controller 40 can be a single-chip microcomputer, a programmable logic controller (PLC), and can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component. The controller 40 can also be any conventional processor or the like.

[0030] As shown in Figure 1 The first slot is provided with a spring, and the first end of the lock beam is arranged on one end of the spring, and the other end of the spring is fixed in the first slot. The lock body is also provided with a latch, and the driving assembly is connected with the latch. The driving assembly is used to drive the latch according to the unlocking instruction sent by the controller, so that the latch is away from the first slot. When the latch is away from the groove, the lock beam moves away from the lock body under the elastic force of the lock beam spring, so that the second end of the lock beam is separated from the second slot, and the intelligent electronic lock is in an open state. The driving assembly can include but is not limited to a motor, a motor.

[0031] As preferred, the lock body can also be provided with a latch spring. One end of the latch spring is connected with the latch, and the other end of the latch spring is fixedly connected with the lock body. By arranging the latch spring, when the user presses the lock beam in the unlocking state and the lock beam moves towards the lock body, the latch can be inserted into the groove of the lock beam under the elastic force of the latch spring, so as to realize the locking of the intelligent electronic lock.

[0032] The lock body is also provided with a state acquisition assembly and a wireless communication assembly electrically connected with the controller. The state acquisition assembly includes a plurality of inclination sensors arranged at different positions of the lock body. The state acquisition assembly is used to upload the inclination angle data collected by the plurality of inclination sensors to the unlocking control system through the wireless communication assembly. The inclination angle data collected by the plurality of inclination sensors is used to instruct the unlocking control system to determine the inclination state of the lock body according to the vibration data collected by the plurality of vibration sensors, and to issue a batch unlocking instruction to the wireless communication assembly according to the case information, the case position and the inclination state of the lock body.

[0033] The lock body is further provided with a power supply, which is electrically connected with the RFID tag, the controller, the driving assembly, the state acquisition assembly and the wireless communication assembly. The power supply is used to supply power to the RFID tag, the controller, the driving assembly, the state acquisition assembly and the wireless communication assembly. As a preferred, the power supply can be a lithium battery. Alternatively, a charging interface is further provided on the side of the lock body close to the lithium battery, and the charging interface is electrically connected with the lithium battery. Correspondingly, the charging interface can also not be provided, and only the lithium battery needs to be replaced when the lithium battery is out of power. As a preferred, the power supply can further include a wireless induction charging coil. The wireless induction charging coil can enable the power supply to have the function of wireless charging.

[0034] As a preferred, the inclination sensors at the plurality of positions of the lock body include:

[0035] A plurality of test inclination sensors are provided on the lock body of the test case, wherein the plurality of test inclination sensors are respectively arranged at a plurality of different positions of the lock body;

[0036] A plurality of case inclination test scenarios are determined, wherein the inclination angles of the cases in different case inclination test scenarios are different;

[0037] Obtain inclination angle data collected by the plurality of test inclination sensors in each case inclination test scenario;

[0038] Determine a candidate test inclination sensor based on the inclination angle data collected by each test inclination sensor in each case inclination test scenario;

[0039] Based on the inclination angle data collected by each candidate test inclination sensor in each case inclination test scenario, the candidate test inclination sensors are de-duplicated to determine a plurality of target test inclination sensors;

[0040] The inclination sensors at the plurality of positions of the lock body are based on the setting positions of the plurality of target test inclination sensors.

[0041] As a preferred, determining a candidate test inclination sensor based on the inclination angle data collected by each test inclination sensor in each case inclination test scenario includes:

[0042] For each test inclination sensor, calculate the angle sensing effectiveness coefficient of the test inclination sensor based on the inclination angle data collected by the test inclination sensor in each case inclination test scenario;

[0043] Determine a candidate test inclination sensor based on the angle sensing effectiveness coefficient of each test inclination sensor.

[0044] Specifically, the angle sensing effectiveness coefficient of the test tilt sensor can be calculated according to a difference between the tilt angle data collected by the test tilt sensor in each case box tilt test scene and the actual tilt angle of the case box.

[0045] For example, the angle sensing effectiveness coefficient of the test tilt sensor can be calculated according to the following formula:

[0046]

[0047] wherein, is the angle sensing effectiveness coefficient of the i th test tilt sensor, is the tilt angle collected by the i th test tilt sensor in the m th case box tilt test scene, is the actual tilt angle of the case box in the m th case box tilt test scene, is the total number of case box tilt test scenes.

[0048] The test tilt sensor with the sensing effectiveness coefficient greater than the sensing effectiveness coefficient threshold value can be taken as a candidate test tilt sensor.

[0049] Figure 2 is a flowchart for determining a plurality of target test tilt sensors according to some embodiments of the present specification, as shown in Figure 2 As preferred, the candidate test tilt sensors are de-duplicated based on the tilt angle data collected by each candidate test tilt sensor in each case box tilt test scene to determine the plurality of target test tilt sensors, as shown in

[0050] For any two candidate test tilt sensors, the angle sensing similarity is calculated according to the tilt angle data collected by the two candidate test tilt sensors in each case box tilt test scene;

[0051] A plurality of sensor clusters are determined based on the angle sensing similarity of any two candidate test tilt sensors through a clustering algorithm;

[0052] A plurality of candidate setting schemes are generated based on the plurality of candidate test tilt sensors and the plurality of sensor clusters, wherein different candidate setting schemes include at least partially different candidate test tilt sensors, and any two candidate test tilt sensors included in each candidate setting scheme do not belong to the same sensor cluster;

[0053] An adaptability function is established;

[0054] For each setting scheme, the adaptability of the setting scheme is calculated based on the adaptability function and the tilt angle data collected by the candidate test tilt sensors included in the setting scheme in each case box tilt test scene.

[0055] determine the optimal setting scheme based on the fitness of each setting scheme;

[0056] determine a plurality of target test tilt sensors based on the optimal setting scheme.

[0057] Specifically, the angle sensing similarity of the two candidate test tilt sensors can be calculated according to the difference between the tilt angle data collected by the two candidate test tilt sensors in each case box tilt test scene.

[0058] For example, the angle sensing similarity of the two candidate test tilt sensors can be calculated according to the following formula:

[0059]

[0060] wherein, is the angle sensing similarity of the i-th candidate test tilt sensor and the j-th candidate test tilt sensor, is the tilt angle collected by the j-th test tilt sensor in the m-th case box tilt test scene.

[0061] The fitness function plays a crucial role in the selection of sensor setting schemes, which is used to quantitatively evaluate the pros and cons of each candidate setting scheme. In the context of this scenario, the fitness function is mainly constructed based on the tilt angle data collected by the candidate test tilt sensors in various case box tilt test scenes, and its design goal is usually to enable the finally selected sensor setting scheme to meet certain performance requirements.

[0062] For example, the fitness function is:

[0063]

[0064] wherein, is the fitness of the k-th sensor setting scheme, is the total number of candidate test tilt sensors included in the k-th sensor setting scheme, and is a weight, greater than 0, .

[0065] Genetic algorithm is an optimization algorithm that simulates natural selection and genetic mechanisms, which searches for the optimal solution of a problem by simulating selection, crossover and mutation operations in the biological evolution process. By genetically determining the fitness of each setting scheme, the optimal setting scheme can be determined, which can include the following processes:

[0066] Initialization of population: First, a certain number of candidate setting schemes are randomly generated to form the initial population. Each setting scheme can be represented as a chromosome, which contains multiple genes, each representing a candidate test with an angle sensor.

[0067] Evaluation of fitness: The fitness value of each setting scheme is calculated using a fitness function. The higher the fitness value, the better the setting scheme.

[0068] Selection operation: According to the fitness value, a part of the excellent setting schemes in the population are selected as parents for generating the next generation. Selection methods such as roulette selection, tournament selection, etc. can be used.

[0069] Cross operation: The selected parents are crossed to generate new child setting schemes. Cross operation can simulate the gene recombination process in biological genetics, by exchanging some genes in the parent scheme to produce new gene combinations.

[0070] Mutation operation: The child setting schemes are mutated to introduce new gene mutations and increase the diversity of the population. Mutation operation can simulate the gene mutation process in biological genetics, by randomly changing some gene values in the child scheme to produce new schemes.

[0071] Iterative optimization: The newly generated child setting schemes are added to the population, and the evaluation of fitness, selection, cross and mutation operations are repeated until the termination condition is met (such as reaching the maximum number of iterations, convergence of fitness value, etc.).

[0072] Determination of optimal scheme: During the iterative optimization process, the optimal fitness value and corresponding setting scheme are recorded. Finally, when the termination condition is met, the optimal setting scheme is output as the final result.

[0073] It can be understood that the lock body, as the core security component of the case, its inclination state may be affected by multiple factors. A single sensor is difficult to cover all potential risk points, and a multi-position sensor layout can achieve more comprehensive inclination monitoring. The optimized sensor layout can more accurately identify the inclination state of the case. The elimination of redundant sensors can reduce system complexity and reduce the cost of later maintenance and calibration.

[0074] Figure 3 is a schematic diagram of the unlocking control system according to some embodiments of the present specification, as shown in Figure 3 The unlocking control system can be used to control a plurality of RFID-based intelligent electronic locks described above to batch unlock, and the unlocking control system can include an RFID positioning module, an unlocking control module, a state monitoring module, an abnormality determination module, and a batch unlocking module.

[0075] The RFID positioning module is configured to determine the position of the cashbox based on a plurality of calibration RFID tags arranged in the cashbox library, a plurality of RFID readers and an RFID tag arranged in the lock body.

[0076] Preferably, the RFID positioning module is configured to determine the position of the cashbox based on a plurality of calibration RFID tags arranged in the cashbox library, a plurality of RFID readers and an RFID tag arranged in the lock body, including:

[0077] The plurality of target RFID readers are determined from the plurality of RFID readers based on the strength of the signal of the RFID tag arranged in the lock body received by the plurality of RFID readers. For example, the plurality of RFID readers can be ranked in descending order of the strength of the signal of the RFID tag arranged in the lock body received by the plurality of RFID readers, and the plurality of target RFID readers are determined from the plurality of RFID readers according to the ranking result. For example, the top three RFID readers in the ranking can be taken as the target RFID readers.

[0078] The plurality of target calibration RFID tags are determined from the plurality of calibration RFID tags based on the plurality of target RFID readers. Specifically, for each calibration RFID tag, the strength of the interference-free signal of the target calibration RFID tag received by each target RFID reader is averaged to obtain the strength average of the calibration RFID tag. The plurality of calibration RFID tags are ranked in descending order of the strength average, and the plurality of target calibration RFID tags are determined from the plurality of calibration RFID tags according to the ranking result. For example, the top three calibration RFID tags in the ranking can be taken as the target calibration RFID tags.

[0079] The position of the cashbox is determined based on the strength of the current signal of the plurality of target calibration RFID tags received by the plurality of target RFID readers and the strength of the signal of the RFID tag arranged in the lock body.

[0080] Preferably, the position of the cashbox is determined based on the strength of the current signal of the plurality of target calibration RFID tags received by the plurality of target RFID readers and the strength of the signal of the RFID tag arranged in the lock body, including:

[0081] The strength of the signal of the RFID tag arranged in the lock body received by the target RFID reader is corrected based on the strength of the current signal of the target calibration RFID tag received by the target RFID reader and the strength of the interference-free signal of the target calibration RFID tag received by the target RFID reader, and the corrected strength of the signal of the RFID tag arranged in the lock body received by the target RFID reader is generated, wherein the interference-free signal of the target calibration RFID tag received by the target RFID reader refers to the signal emitted by the target calibration RFID tag received by the target RFID reader when the article box library does not store any articles.

[0082] The article box position is determined based on the corrected strength of the signal of the RFID tag arranged in the lock body received by the target RFID reader.

[0083] Specifically, the strength correction model can be established and trained, wherein the strength correction model can be a convolutional neural network model, and the strength correction model is used to correct the strength of the signal of the RFID tag arranged in the lock body received by the target RFID reader based on the strength of the current signal of the target calibration RFID tag received by the target RFID reader and the strength of the interference-free signal of the target calibration RFID tag received by the target RFID reader, and output the corrected strength of the signal of the RFID tag arranged in the lock body received by the target RFID reader. The article box position is determined based on the corrected strength of the signal of the RFID tag arranged in the lock body received by the target RFID reader by using a positioning algorithm (such as a triangular positioning method, a fingerprint positioning method, etc.).

[0084] The lock opening control module is used to receive a batch lock opening request initiated by a user terminal, and determine a plurality of target intelligent electronic locks based on the batch lock opening request initiated by the user terminal.

[0085] Specifically, the batch lock opening request can include various information, such as user identity information, unique identification of the target intelligent electronic lock, and request time, etc.

[0086] For example, the user terminal initiates a batch lock opening request through an API interface or a management platform, and the data format is usually JSON, which includes the following key fields:

[0087] lock_ids: The unique identification list of the target lock (such as lock ID, MAC address, etc.).

[0088] user_token: User identity authentication token, which ensures the legality of the request.

[0089] timestamp: Request timestamp, which is used to prevent replay attacks.

[0090] The unlocking control module can determine a plurality of target smart electronic locks according to the following process:

[0091] Verify user permissions: query the database according to the user_token to confirm whether the user terminal has the right to operate the specified lock.

[0092] Filter invalid locks: check whether the unique identifier of each target smart electronic lock in the lock_ids exists in the system database, and verify its state (such as whether it is online, whether it is disabled).

[0093] Generate a list of target locks: return the unique identifier set of the target smart electronic locks that meet the conditions as the target of the subsequent unlocking instruction.

[0094] The state monitoring module is configured to determine the lock body tilt state of the target smart electronic lock based on the tilt angle data collected by the plurality of tilt angle sensors of the target smart electronic lock.

[0095] Preferably, the state monitoring module determines the lock body tilt state of the target smart electronic lock based on the tilt angle data collected by the plurality of tilt angle sensors of the target smart electronic lock, including:

[0096] Establish a multiple regression model, wherein the independent variables of the multiple regression model include the tilt angle data collected by the plurality of tilt angle sensors, and the dependent variable of the multiple regression model is the lock body tilt angle;

[0097] For each time point, the lock body tilt angle at the time point is determined by the multiple regression model based on the tilt angle data collected by the plurality of tilt angle sensors at the time point;

[0098] Based on the lock body tilt angles of a plurality of consecutive time points, the lock body stability and tilt angle of the target smart electronic lock are determined.

[0099] Specifically, the lock body stability of the target smart electronic lock can be calculated according to the following formula:

[0100]

[0101] wherein, is the lock body stability of the i-th target smart electronic lock, is the tilt angle of the i-th target smart electronic lock at the t-th time point, is the total number of sampled time points.

[0102] The anomaly determination module is configured to determine whether there is an abnormal smart electronic lock among the plurality of target smart electronic locks based on the position of the cash box and the lock body tilt state of the target smart electronic lock, and if it is determined that there is an abnormal smart electronic lock, send a prompt message to the user terminal, and if it is determined that there is no abnormal smart electronic lock, generate a batch unlocking instruction based on the plurality of target smart electronic locks.

[0103] As preferred, the abnormality determination module determines whether the target smart electronic lock is an abnormal smart electronic lock based on the case position and the lock body tilt state of the target smart electronic lock, comprising:

[0104] determining whether the target smart electronic lock is located in the unlocking area based on the case position;

[0105] if the target smart electronic lock is not located in the unlocking area, determining that the target smart electronic lock is an abnormal smart electronic lock;

[0106] if the target smart electronic lock is located in the unlocking area, determining the number of cases above the target smart electronic lock based on the case position, wherein the number of cases above the target smart electronic lock can be the number of cases located directly above the target smart electronic lock;

[0107] if the number of cases above the target smart electronic lock is greater than the number threshold, determining that the target smart electronic lock is an abnormal smart electronic lock;

[0108] if the number of cases above the target smart electronic lock is less than or equal to the number threshold, determining whether the lock body stability of the target smart electronic lock is greater than the lock body stability threshold;

[0109] if the lock body stability of the target smart electronic lock is less than the lock body stability threshold, determining that the target smart electronic lock is an abnormal smart electronic lock;

[0110] if the lock body stability of the target smart electronic lock is greater than or equal to the lock body stability threshold, determining whether the tilt angle of the target smart electronic lock is greater than the tilt angle threshold;

[0111] if the tilt angle of the target smart electronic lock is greater than the tilt angle threshold, determining that the target smart electronic lock is an abnormal smart electronic lock.

[0112] It can be understood that by determining whether the target smart electronic lock is located in the unlocking area, the smart electronic lock in the abnormal position can be effectively identified, preventing unlocking operations in non-designated areas, ensuring the safety of important items such as cases, and avoiding illegal personnel from stealing or damaging using the lock in the abnormal position. Determining the number of cases above the target smart electronic lock and comparing it with the number threshold can timely discover unreasonable case stacking. If the number of cases above is too large, it may cause the lock body to bear excessive pressure, affecting the normal use and safety of the lock, and timely determination of abnormality can avoid potential safety hazards. Determining whether the lock body stability of the target smart electronic lock is greater than the lock body stability threshold can detect whether the lock body is in a stable state. Unstable lock body may mean that the lock body is disturbed or damaged by external force, affecting its normal locking and unlocking functions, and unlocking in an unstable or tilted state may cause the stored items in the case to be separated from the case, resulting in loss of items.

[0113] The batch unlocking module is configured to issue a batch unlocking instruction to a wireless communication component of a plurality of target smart electronic locks, and the batch unlocking instruction is configured to instruct the plurality of target smart electronic locks to perform consensus verification and to perform batch unlocking after the consensus verification is passed.

[0114] Preferably, the batch unlocking instruction instructs the plurality of target smart electronic locks to perform consensus verification, which includes:

[0115] The plurality of target smart electronic locks perform unlocking time consensus verification based on the batch unlocking instruction. Specifically, after receiving the batch unlocking instruction, the target smart electronic lock can determine whether the unlocking time of the batch unlocking instruction is within the allowed unlocking time range stored in the target smart electronic lock, and feed back the unlocking time verification result. If all target smart electronic locks determine that the unlocking time is within the allowed unlocking time range, it is determined that the unlocking time consensus verification is passed.

[0116] After the unlocking time consensus verification is passed, the unlocking permission consensus verification is performed based on the batch unlocking instruction. Specifically, the target smart electronic lock can determine whether the user terminal initiating the batch unlocking request has the unlocking permission of the target smart electronic lock according to the unlocking permission information stored in the target smart electronic lock, and feed back the unlocking permission verification result. If all target smart electronic locks determine that the user terminal has the unlocking permission of the target smart electronic lock, it is determined that the unlocking permission consensus verification is passed.

[0117] After the unlocking permission consensus verification is passed, the unlocking association consensus verification is performed based on the batch unlocking instruction. Specifically, based on the plurality of target smart electronic locks, a to-be-verified relationship corresponding to each target smart electronic lock is generated. For example, the plurality of target smart electronic locks include target smart electronic lock A, target smart electronic lock B, and target smart electronic lock C. The to-be-verified relationship corresponding to the target smart electronic lock A includes the target smart electronic lock A and the target smart electronic lock B, and the target smart electronic lock A and the target smart electronic lock C. The to-be-verified relationship corresponding to the target smart electronic lock B includes the target smart electronic lock B and the target smart electronic lock A, and the target smart electronic lock B and the target smart electronic lock C. For each target smart electronic lock, it is determined whether each to-be-verified relationship is verified based on the pre-stored unlocking record of the current period of the target smart electronic lock. When there are at least one same-batch unlocking record of the two target smart electronic locks corresponding to the to-be-verified relationship in the unlocking record, the to-be-verified relationship is verified. When the proportion of the to-be-verified relationships verified by each target smart electronic lock is greater than a preset proportion (for example, 50%), the unlocking association consensus verification is passed.

[0118] It can be understood that the unlocking time consensus verification ensures that the batch unlocking operation is performed within the preset safe time range. This can effectively prevent unauthorized unlocking attempts during non-working hours or sensitive time periods, such as special periods such as night or holidays, avoid security vulnerabilities due to time factors, and reduce the risk of internal personnel violation or external illegal intrusion. The unlocking permission consensus verification strictly verifies the user terminal initiating the batch unlocking request according to the unlocking permission information stored in each target smart electronic lock. Only users with corresponding permissions can perform unlocking operations to prevent unauthorized personnel from obtaining unlocking permissions, protect the safety of important items such as cash boxes, and prevent information leakage or asset loss. The unlocking association consensus verification analyzes the unlocking record relationship between multiple target smart electronic locks to determine whether there is a reasonable batch unlocking situation. This can prevent a single smart electronic lock from being illegally unlocked alone, ensure that the unlocking operation conforms to the business logic and safety specifications, and avoid security risks caused by abnormal association relationships. The three consensus verification mechanisms of unlocking time, unlocking permission, and unlocking association verify the batch unlocking instruction from different angles. This multi-verification method greatly improves the reliability and fault tolerance of the system, so that even if a verification link fails or is bypassed, other verification links can still function to ensure the safety of the unlocking operation.

[0119] The present application provides a cash box, which is installed with the above-mentioned RFID-based smart electronic lock and applies the above-mentioned unlocking control system, which will not be described here.

[0120] Finally, it should be understood that the embodiments described in the specification are only used to illustrate the principles of the embodiments of the specification. Other variations can also belong to the scope of the specification. Therefore, as an example rather than a limitation, alternative configurations of the embodiments of the specification can be considered consistent with the teachings of the specification. Accordingly, the embodiments of the specification are not limited to the embodiments explicitly introduced and described in the specification.

Claims

1. An RFID-based smart electronic lock characterized by, The lock body comprises a lock body and a lock beam, first and second insertion slots are formed at both ends of the lock body, the first end of the lock beam is located in the first insertion slot, the second end of the lock beam is located in the second insertion slot in the locked state, and the second end of the lock beam is located outside the second insertion slot in the unlocked state; The lock body further comprises an RFID tag, a controller and a driving assembly, the RFID tag is used to record the information of the cash box, the RFID tag is also used to determine the position of the cash box, and the controller is used to control the driving assembly to drive the second end of the lock beam to separate from the second insertion slot based on the batch unlocking instruction; The lock body further comprises a state acquisition assembly and a wireless communication assembly electrically connected with the controller, the state acquisition assembly comprises a plurality of inclination sensors arranged at a plurality of positions of the lock body, and the following processes are based on the following processes: Obtain the inclination angle data collected by a plurality of test inclination sensors in each cash box inclination test scene, and determine candidate test inclination sensors; For any two candidate test inclination sensors, calculate the angle sensing similarity according to the inclination angle data collected by the two candidate test inclination sensors in each cash box inclination test scene; Determine a plurality of sensor clusters based on the angle sensing similarity of any two candidate test inclination sensors through a clustering algorithm; Based on the plurality of candidate test inclination sensors and the plurality of sensor clusters, a plurality of candidate setting schemes are generated, wherein the candidate test inclination sensors included in different candidate setting schemes are at least partially different, and any two candidate test inclination sensors included in each candidate setting scheme do not belong to the same sensor cluster; Establish a fitness function; For each setting scheme, calculate the fitness of the setting scheme based on the fitness function and the inclination angle data collected by the candidate test inclination sensors included in the setting scheme in each cash box inclination test scene; Determine the optimal setting scheme based on the fitness of each setting scheme through genetic algorithm; Based on the optimal setting scheme, a plurality of target test inclination sensors are determined; The state acquisition assembly is used to upload the inclination angle data collected by the plurality of inclination sensors to the unlocking control system through the wireless communication assembly, and the inclination angle data collected by the plurality of inclination sensors is used to instruct the unlocking control system to determine the inclination state of the lock body according to the vibration data collected by the plurality of vibration sensors, and to issue a batch unlocking instruction to the wireless communication assembly according to the cash box information, the cash box position and the inclination state of the lock body.

2. The RFID-based intelligent electronic lock according to claim 1, characterized in that, The inclination sensors at a plurality of positions of the lock body comprise: A plurality of test inclination sensors are arranged on the lock body of the test cash box; A plurality of cash box inclination test scenes are determined; Obtain the inclination angle data collected by a plurality of test inclination sensors in each cash box inclination test scene; Determine candidate test inclination sensors based on the inclination angle data collected by each test inclination sensor in each cash box inclination test scene; Based on the inclination angle data collected by each candidate test inclination sensor in each cash box inclination test scene, the candidate test inclination sensors are de-duplicated to determine a plurality of target test inclination sensors; Based on the setting positions of the plurality of target test inclination sensors, the inclination sensors at a plurality of positions of the lock body.

3. The RFID-based intelligent electronic lock of claim 2, wherein, Determine the candidate test tilt sensor based on the tilt angle data collected by each test tilt sensor under each case box tilt test scene, comprising: For each test tilt sensor, calculate the angle sensing effectiveness coefficient of the test tilt sensor based on the tilt angle data collected by the test tilt sensor under each case box tilt test scene; Determine the candidate test tilt sensor based on the angle sensing effectiveness coefficient of each test tilt sensor.

4. A system for controlling the opening of a lock, characterized in that For controlling a plurality of RFID-based intelligent electronic locks as claimed in any one of claims 1-3 to perform batch unlocking, comprising: An RFID positioning module for determining the case box position based on a plurality of calibration RFID tags arranged in the case box library, a plurality of RFID readers and an RFID tag arranged in the lock body; An unlocking control module for receiving a batch unlocking request initiated by the user end and determining a plurality of target intelligent electronic locks based on the batch unlocking request initiated by the user end; A state monitoring module for determining the lock body tilt state of the target intelligent electronic lock based on the tilt angle data collected by the plurality of tilt sensors of the target intelligent electronic lock; An abnormality determination module for determining whether there is an abnormal intelligent electronic lock among the plurality of target intelligent electronic locks based on the case box position and the lock body tilt state of the target intelligent electronic lock, and if it is determined that there is an abnormal intelligent electronic lock, sending a prompt information to the user end, and if it is determined that there is no abnormal intelligent electronic lock, generating a batch unlocking instruction based on the plurality of target intelligent electronic locks; A batch unlocking module for issuing the batch unlocking instruction to the wireless communication component of the plurality of target intelligent electronic locks, and the batch unlocking instruction is used to instruct the plurality of target intelligent electronic locks to perform consensus verification and batch unlocking after the consensus verification is passed.

5. The unlocking control system according to claim 4, characterized by The RFID positioning module determines the case box position based on a plurality of calibration RFID tags arranged in the case box library, a plurality of RFID readers and an RFID tag arranged in the lock body, comprising: Determine a plurality of target RFID readers from the plurality of RFID readers based on the strength of the signal of the RFID tag arranged in the lock body received by the plurality of RFID readers; Determine a plurality of target calibration RFID tags from the plurality of calibration RFID tags based on the plurality of target RFID readers; Determine the case box position based on the strength of the current signal of the plurality of target calibration RFID tags received by the plurality of target RFID readers and the strength of the signal of the RFID tag arranged in the lock body.

6. The unlocking control system according to claim 5, characterized by Determine the case box position based on the strength of the current signal of the plurality of target calibration RFID tags received by the plurality of target RFID readers and the strength of the signal of the RFID tag arranged in the lock body, comprising: Based on the strength of the current signal of the plurality of target calibration RFID tags received by the plurality of target RFID readers and the strength of the interference-free signal of the plurality of target calibration RFID tags received by the plurality of target RFID readers, correct the strength of the signal of the RFID tag arranged in the lock body received by the plurality of target RFID readers to generate the corrected strength of the signal of the RFID tag arranged in the lock body received by the plurality of target RFID readers; The case position is determined based on the corrected intensities of the signals of the RFID tags arranged in the lock bodies received by the plurality of target RFID readers.

7. The unlocking control system according to claim 4, characterized by The state monitoring module determines the tilt state of the lock body of the target smart electronic lock based on the tilt angle data collected by the plurality of tilt angle sensors of the target smart electronic lock, including: A multiple regression model is established, wherein the independent variables of the multiple regression model include the tilt angle data collected by the plurality of tilt angle sensors, and the dependent variable of the multiple regression model is the tilt angle of the lock body; For each time point, the tilt angle of the lock body at the time point is determined by the multiple regression model based on the tilt angle data collected by the plurality of tilt angle sensors at the time point; Based on the tilt angles of the lock body at a plurality of consecutive time points, the stability and the tilt angle of the lock body of the target smart electronic lock are determined.

8. The unlocking control system according to claim 4, characterized by The anomaly determination module determines whether there is an abnormal smart electronic lock among the plurality of target smart electronic locks based on the case position and the tilt state of the lock body of the target smart electronic lock, including: Based on the case position, it is determined whether the target smart electronic lock is located in the unlocking area; If the target smart electronic lock is not located in the unlocking area, the target smart electronic lock is determined to be an abnormal smart electronic lock; If the target smart electronic lock is located in the unlocking area, the number of cases above the target smart electronic lock is determined based on the case position; If the number of cases above the target smart electronic lock is greater than the number threshold, the target smart electronic lock is determined to be an abnormal smart electronic lock; If the number of cases above the target smart electronic lock is less than or equal to the number threshold, it is determined whether the stability of the lock body of the target smart electronic lock is greater than the lock body stability threshold; If the stability of the lock body of the target smart electronic lock is less than the lock body stability threshold, the target smart electronic lock is determined to be an abnormal smart electronic lock; If the stability of the lock body of the target smart electronic lock is greater than or equal to the lock body stability threshold, it is determined whether the tilt angle of the target smart electronic lock is greater than the tilt angle threshold; If the tilt angle of the target smart electronic lock is greater than the tilt angle threshold, the target smart electronic lock is determined to be an abnormal smart electronic lock.

9. The unlocking control system according to any one of claims 4 to 8, characterized by, The batch unlocking instruction instructs a plurality of target smart electronic locks to perform consensus verification, including: The plurality of target smart electronic locks perform unlocking time consensus verification based on the batch unlocking instruction; After the unlocking time consensus verification is passed, the unlocking permission consensus verification is performed based on the batch unlocking instruction; After the unlocking permission consensus verification is passed, the unlocking association consensus verification is performed based on the batch unlocking instruction.

10. A case characterized by, The unlocking control system of any one of claims 4-9 is applied.

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