A management method for whole-process internet of things informationization management and control of a smart locker

Abstract

The application provides a management method for whole-process Internet of Things informationization management and control of a smart locker, and belongs to the technical field of intelligent management and control, and comprises the following steps: a data transmission channel is automatically established with an Internet of Things management and control platform based on the current state and environmental parameters of the smart locker by using a multimode communication mode; an initial unique hardware identifier of the smart locker is bound with a national secret algorithm, and the collected data is encrypted based on a national secret chip; the encrypted whole-process management and control data, the dynamically updated hardware identifier information and the corresponding node permission information are associated, and are synchronously transmitted to an alliance block chain network for distributed verification; when each management and control node is connected with the smart locker through a terminal device via a communication device, the terminal identity information is decrypted by the national secret chip, verification is performed, the corresponding operation permission is triggered, and the whole-process management and control is completed. The safety and efficiency of the management and control of the locker are ensured, and the demand of modern informationization management and control is met.

Description

Technical Field

[0001] This invention relates to the field of intelligent control technology, and in particular to a management method for the full-process Internet of Things (IoT) information control of intelligent cash registers. Background Technology

[0002] In sectors such as finance and logistics, involving the transportation and storage of valuables, cash boxes, as core carriers, directly impact operational efficiency and asset security through their security and information technology levels. Currently, traditional cash box management models generally suffer from the following problems: First, communication methods are limited, often relying on fixed Wi-Fi or Bluetooth connections. In complex environments (such as underground parking garages or remote transportation routes), these connections are susceptible to electromagnetic interference, leading to data transmission interruptions or delays and failing to guarantee real-time synchronization of control commands and status information. Second, security measures are insufficient, often relying on simple password encryption or fixed hardware identifiers. Data is easily stolen and tampered with, and the long-term fixed hardware identifiers are easily cracked and copied, posing a risk of identity theft. Third, the management process lacks transparency and traceability. Information such as the cash box's opening and closing status, location trajectory, and item measurement relies heavily on manual recording or centralized platform storage, making it prone to information falsification and loss. These problems result in serious security risks and efficiency bottlenecks in traditional cash box management, making it difficult to meet the demands of modern, information-based management.

[0003] Therefore, this invention proposes a management method for the full-process IoT information control of smart cash registers. Summary of the Invention

[0004] This invention provides a management method for the full-process IoT information control of smart cash registers, in order to solve the aforementioned technical problems.

[0005] This invention provides a management method for end-to-end IoT-based information control of smart cash registers, comprising:

[0006] Step 1: Using a multi-mode communication mode, a data transmission channel is automatically established with the IoT management platform based on the current status and environmental parameters of the smart cash box. The multi-mode communication mode includes at least two of the following communication methods: WiFi, Bluetooth, StarFlash, and 5G.

[0007] Step 2: Bind the initial unique hardware identifier of the smart cash box to the national cryptographic algorithm. Based on the national cryptographic chip, encrypt the collected cash box opening and closing status, location trajectory, measurement parameters of items in the box, as well as the transmitted control commands and node identity information. When the smart cash box completes a preset number of operations, or when a physical disassembly attempt to target the smart cash box is detected, a new unique hardware identifier is automatically generated and updated.

[0008] Step 3: Associate the encrypted end-to-end control data, the dynamically updated hardware identification information, and the corresponding node permission information, and synchronize them to the consortium blockchain network in real time for distributed verification;

[0009] Step 4: When each control node connects to the smart cash box via a communication device through a terminal device, the terminal identity information is decrypted by a national cryptographic chip, and the permission association data and dynamically updated hardware identification information stored in the consortium blockchain network are retrieved to complete real-time verification. After the verification is successful, the corresponding operation permission is automatically triggered, and the operation completion log is immediately uploaded to the consortium blockchain network for update, thus completing the entire process control.

[0010] Preferably, a data transmission channel is automatically established between the smart cash register and the IoT management platform based on the current status and environmental parameters, including:

[0011] Identify the communication devices connected to the smart cash box and retrieve the historical work logs of each communication device;

[0012] The historical work log is analyzed by working time sequence and non-working time sequence to obtain the corresponding first matrix and second matrix, and the difference vector between the first feature vector of the first matrix and each historical row vector in the latest period of the first matrix is ​​obtained.

[0013] The second eigenvector of the second matrix is ​​determined and compared with the standard eigenvector of the communication device when it is in a non-working state to obtain the static principal element. The change attenuation of the static principal element in the third matrix obtained by extracting the second matrix according to the latest period is analyzed.

[0014] Compare all static principal elements with the elements of each difference vector, and combine the element combination of the difference principal elements of the corresponding difference vector with the change attenuation of all static principal elements to obtain the dynamic attenuation group, and adjust the corresponding sub-attenuation terms to construct the communication loss function.

[0015] Based on the communication loss function and the determination result of the real-time collected environmental electromagnetic interference intensity, the communication connection confidence based on the current state of the smart cash box is determined, the final communication mode is locked, and a data transmission channel is established.

[0016] Preferably, determining the communication connection confidence based on the current state of the smart cash register includes:

[0017] The interference influence coefficient is obtained by matching the electromagnetic interference intensity It of the environment in which the smart cash box is located with a preset intensity level-influence correspondence table. ;

[0018] For the communication loss function Perform time-weighted correction to obtain the corrected loss function. ,in, The current moment; The time-series sampling interval is n; n is the length of the historical sampling window. Let be the weight of the i-th historical sampling point, and ;

[0019] Calculate communication connection confidence ,in, The coupling factor is based on the current state;

[0020] Confidence of the communication connection The final communication mode is determined by comparing it with a threshold range.

[0021] Preferably, the collected cash box opening and closing status, location trajectory, internal item measurement parameters, and transmitted control commands and node identity information are encrypted based on the national cryptographic chip, including:

[0022] Each acquisition parameter involved in each acquisition moment is encoded and randomly combined to obtain the first code;

[0023] Extract the start and end positions of each operation item from the entire process. Using the end position of the first operation item as the starting point and the initial start position of the latest executed operation item as the ending point, obtain the first two adjacent moments of each trigger position. At the same time, obtain the second two adjacent moments where there is a mode switch, and determine the operation item change status of each second two adjacent moments for encoding to obtain the second code.

[0024] Based on the data changes at the first two adjacent time points, analyze the multidimensional satisfaction factors of the change conditions based on the corresponding adjacent operation items, and perform separate extended analysis on the same-dimensional satisfaction factors at all the first two adjacent time points and comprehensive extended analysis on the multidimensional satisfaction factors at all the first two adjacent time points to obtain the compensation function.

[0025] Based on the compensation function, the first code, and the second code, the influencing factors at the corresponding acquisition time are obtained;

[0026] Based on the national cryptographic chip, the collected data is encrypted according to the national cryptographic algorithm and in combination with influencing factors.

[0027] Preferably, a compensation function is obtained by performing individual extended analysis on all same-dimensional satisfaction factors at the first two adjacent time points and comprehensive extended analysis on multi-dimensional satisfaction factors at all first two adjacent time points, including:

[0028] Based on the full-process control attributes of smart cash boxes, the core dimensions corresponding to the same-dimensional satisfaction factors are divided into time-series-location trajectory dimension, time-series-single measurement dimension, and multi-parameter correlation dimension.

[0029] Obtain the same-dimensional extension coefficient of a single dimension at the corresponding time, obtain the comprehensive correlation degree of multiple dimensions at the corresponding time, and obtain the expansion coefficient along the time axis at the corresponding time to obtain the compensation function at the corresponding time.

[0030] Preferably, based on the compensation function, the first code, and the second code, the influencing factors corresponding to the acquisition time are obtained, including:

[0031] Extract the acquisition time interval corresponding to the first code and the operation item triggering time interval corresponding to the second code, and verify the time sequence coverage relationship between the acquisition time and the operation item to determine the time sequence matching degree between the two.

[0032] The initial weights of the compensation function at the corresponding time point are adjusted based on the time-series matching degree.

[0033] Obtain the associated weights of the scene at the corresponding time for the compensation function, the first code, and the second code from the scene-weight lookup table, and combine them with the adjusted initial weights to obtain the updated weights for the compensation function, the first code, and the second code, respectively.

[0034] The parameter features of the first code, the operation item state features of the second code, and the correction features of the compensation function are mapped hierarchically. The basic feature layer is constructed with the element with the highest update weight as the core, and the remaining elements are embedded into the associated nodes of the basic feature layer according to their update weights to generate a preliminary set of influence factors.

[0035] Preferably, real-time synchronization to the consortium blockchain network for distributed verification includes:

[0036] The consortium blockchain network nodes are divided into a core verification layer, a secondary verification layer, and an audit verification layer. Differentiated verification permissions and data visibility ranges are preset for each layer of nodes.

[0037] The core verification layer performs basic verifications on data encryption integrity, dynamic hardware identifier validity, and node identity and authorization legality, and generates basic verification credentials that are synchronized to the corresponding secondary verification layer group.

[0038] The secondary verification layer is based on the basic verification credentials and cross-verifies the consistency of the data with the historical chain data and the rationality of the operation sequence. The group leader node summarizes the verification results within the group to form a secondary verification report.

[0039] The audit verification layer conducts sampling reviews of the verification process for high-security-level data, while low / medium-security-level data is only reviewed when an anomaly warning is triggered.

[0040] Preferably, a new unique hardware identifier is automatically generated for updating, including:

[0041] After the update is triggered, the original root key and historical update log of the current hardware identifier are automatically retrieved based on the national cryptographic chip. A temporary encryption seed is generated based on the original root key, and hash fragments of the last n0 on-chain data are extracted as auxiliary factors. The security enhancement function is determined by combining the temporary encryption seed and auxiliary factors. This is then combined with the current state parameters of the cash box and an intermediate identifier generated using the national cryptographic algorithm. This intermediate identifier is then encrypted again using a unique verification code pre-allocated by the core verification layer node to form a new unique hardware identifier. This new identifier includes a historical identifier traceability field and an update trigger reason flag. The security enhancement function is as follows:

[0042] Where N0 is the number of auxiliary factors; The security increment coefficient between the s0th auxiliary factor and the temporary encryption seed; The mutual exclusion angle between the s0th auxiliary factor and the temporary encryption seed The value; This is a secure increment function based on the temporary encryption seed and all auxiliary factors.

[0043] Compared with the prior art, the beneficial effects of this application are as follows:

[0044] By employing dual-mode communication with adaptive switching, the system resolves communication instability issues in complex environments, ensuring real-time data transmission. It also enhances security by using national cryptographic chip encryption and dynamic hardware identification to prevent data leakage and identity theft. Furthermore, it achieves transparent and traceable management data through distributed verification via a consortium blockchain, preventing single-point tampering. Real-time node verification ensures operational compliance, forming a closed-loop management system that effectively addresses the pain points of traditional cash box management, such as communication interruptions, data insecurity, opaque processes, and chaotic permissions, significantly improving the informatization and security of cash box management.

[0045] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0046] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0047] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0048] Figure 1 This is a flowchart illustrating a management method for end-to-end IoT information control of smart cash registers, as described in an embodiment of the present invention. Detailed Implementation

[0049] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0050] This invention provides a management method for end-to-end IoT-based information control of smart cash registers, such as... Figure 1 As shown, it includes:

[0051] Step 1: Using a multi-mode communication mode, a data transmission channel is automatically established with the IoT management platform based on the current status and environmental parameters of the smart cash box. The multi-mode communication mode includes at least two of the following communication methods: WiFi, Bluetooth, StarFlash, and 5G.

[0052] Step 2: Bind the initial unique hardware identifier of the smart cash box to the national cryptographic algorithm. Based on the national cryptographic chip, encrypt the collected cash box opening and closing status, location trajectory, measurement parameters of items in the box, as well as the transmitted control commands and node identity information. When the smart cash box completes a preset number of operations, or when a physical disassembly attempt to target the smart cash box is detected, a new unique hardware identifier is automatically generated and updated.

[0053] Step 3: Associate the encrypted end-to-end control data, the dynamically updated hardware identification information, and the corresponding node permission information, and synchronize them to the consortium blockchain network in real time for distributed verification;

[0054] Step 4: When each control node connects to the smart cash box via a communication device through a terminal device, the terminal identity information is decrypted by a national cryptographic chip, and the permission association data and dynamically updated hardware identification information stored in the consortium blockchain network are retrieved to complete real-time verification. After the verification is successful, the corresponding operation permission is automatically triggered, and the operation completion log is immediately uploaded to the consortium blockchain network for update, thus completing the entire process control.

[0055] In this embodiment, the multi-mode communication mode refers to the smart cash box being equipped with any two of the following communication methods: WiFi, Bluetooth, StarFlash, and 5G. The main control unit monitors the current status of the cash box (such as static storage, mobile transportation, and static standby) and environmental parameters (such as electromagnetic interference intensity) in real time, and automatically adjusts the two communication methods to achieve adaptive data transmission with the IoT management platform.

[0056] The initial unique hardware identifier refers to the physical identity identifier that is embedded in the built-in encryption chip when the smart smart box leaves the factory. It is a unique serial number that cannot be tampered with (such as a chip UID with a length of 16 bytes) and is used to uniquely distinguish different smart boxes.

[0057] National cryptographic algorithms refer to encryption algorithms that conform to industry standards. This scheme uses the SM4 symmetric encryption algorithm and the SM2 asymmetric encryption algorithm.

[0058] National cryptographic chips refer to hardware encryption chips that integrate national cryptographic algorithms, possessing secure key storage and hardware-level encryption computing capabilities.

[0059] The opening and closing status of the smart cash box refers to the opening and closing state of the door. This is collected in real time by sensors to determine whether the cash box is in a safe and closed state. The common states are open and closed.

[0060] Location trajectory refers to the real-time location and historical movement path of the smart cash box throughout the entire process. It is formed by collecting latitude and longitude coordinates through the positioning module to create a continuous location record.

[0061] The measurement parameters of the items inside the smart cash box refer to the quantitative data of the items carried inside, such as the amount of cash and the weight of precious metals. These data are collected through built-in weight sensors and counting modules and are the core data for item management.

[0062] Control commands refer to the operation instructions issued by the IoT control platform or control node to the smart cash box, such as opening authorization, location reporting frequency adjustment, and locking of the cash box, which are used to control the behavior of the cash box.

[0063] Node identity information refers to the identity identifiers of entities participating in cash box management (such as bank staff, logistics escorts, and warehouse managers), such as employee IDs and unique terminal device codes, which are used for authorization verification.

[0064] Preset operation refers to a threshold number of operations configured in the IoT management platform to trigger hardware identifier updates (e.g., 50 opening-closing cycles, 10 transport handover operations). When the cash box accumulates this number of operations, an identifier update is triggered. Physical disassembly attempt refers to unauthorized disassembly of the smart cash box body or built-in modules (e.g., encryption chip, positioning module). This is detected in real time by vibration sensors, pressure sensors, and anti-tamper contacts. For example, if the initial hardware identifier is HC32L136-00123456789ABCDEF, and the national cryptographic chip collects data at 2024-05-20 10:00, the opening / closing status is closed, the location is 30.1234°N, 120.5678°E, the measurement is 1 million yuan, the instruction is none, and the identity is OP456 performing SM. 4. Encryption: The ciphertext is 8A3B7D9E2F4C1A6B0D8E3F5A2C4D6E8F. When the cash box has completed 50 opening and closing operations (preset number), the main control unit sends an update command to the national cryptographic chip. The national cryptographic chip automatically generates a new hardware identifier HC32L136-00987654321FEDCBA and synchronizes it to the IoT management platform and blockchain network. If the vibration sensor detects 8g acceleration (illegal disassembly), the identifier update is immediately triggered, and the disassembly trigger field is marked in the new identifier.

[0065] A consortium blockchain network refers to a private blockchain network jointly constructed by relevant entities involved in the management of cash boxes (such as financial institutions, logistics companies, and regulatory authorities). Each entity connects as a node, and only authorized nodes can participate in data verification and notarization. The data is immutable and traceable. For example, the data packet uploaded to the chain contains the ciphertext: 8A3B7D9E2F4C1A6B0D8E3F5A2C4D6E8F, hardware identifier: HC32L136-00987654321FEDCBA, and permissions: OP456 - open box + view. The core node of the consortium blockchain (XX Bank headquarters) verifies the integrity of the ciphertext (by decrypting and comparing the hash value using SM4) and the validity of the hardware identifier (by querying historical identifier records on the blockchain to confirm no duplicates). Secondary nodes (XX Bank branches) verify the matching of permission information and node identity. After each node passes the verification, the data packet is written to the blockchain ledger through the PBFT consensus mechanism, generating an immutable notarization record.

[0066] Distributed verification refers to multiple nodes in a consortium blockchain network simultaneously and independently verifying uploaded data, achieving consistent verification results through a consensus mechanism (such as the Practical Byzantine Fault Tolerance (PBFT) algorithm), thus avoiding the risk of single-point verification.

[0067] Control nodes refer to the terminal users and corresponding terminal devices (such as smartphones, industrial tablets, and dedicated control terminals) involved in the control of cash boxes. The terminal devices must support WiFi / Bluetooth / 5G / StarFlash communication and national cryptographic decryption functions.

[0068] Real-time verification refers to the process where, upon accessing a control node, the national cryptographic chip decrypts the terminal's identity information and retrieves pre-stored permission-related data (the node's executable operation permissions) and dynamic hardware identifiers from the consortium blockchain network. The consistency of identity, permissions, and identifiers is compared to complete rapid verification of identity and permissions. For example, operator OP456 uses a tablet DT30 to connect to the cash box via Bluetooth. The APP sends the identity information DT30-001+OP456. After decryption by the national cryptographic chip, OP456's permissions are retrieved from the blockchain: "Can open the box." Current hardware identifier: HC32L136-00987654321FEDCBA. The identity and permissions are verified, and opening authorization is automatically triggered (the electronic lock on the box door unlocks). After OP456 completes the inventory check, the APP generates a log: 2024-05-20 10:30, "OP456, Opened the box for inventory check, Measurement = 1 million yuan (no change)," which is then encrypted with SM4 and uploaded to the blockchain to update the ledger record, completing this control step.

[0069] Operation completion logs refer to the records generated after the control node completes the operation. They include the operator, operation time, operation content (such as time 1, OP123, opening and counting), and changes in the status of the cash box, and are used for full-process traceability.

[0070] The beneficial effects of the above technical solution are as follows: it solves the problem of unstable communication in complex environments by adaptive switching of dual-mode communication, ensuring real-time data transmission; it prevents data leakage and identity theft by using national cryptographic chip encryption and dynamic hardware identification, thus improving the security level; it achieves transparent and traceable management data through distributed verification of consortium blockchain, avoiding single-point tampering; and it ensures operational compliance through real-time node verification, forming a closed-loop management system that effectively solves the pain points of communication interruption, data insecurity, opaque processes, and chaotic permissions in traditional cash box management, significantly improving the informatization and security of cash box management.

[0071] This invention provides a management method for end-to-end IoT-based information control of smart cash registers, which automatically establishes a data transmission channel with the IoT control platform based on the current status and environmental parameters of the smart cash register, including:

[0072] Identify the communication devices connected to the smart cash box and retrieve the historical work logs of each communication device;

[0073] The historical work log is analyzed by working time sequence and non-working time sequence to obtain the corresponding first matrix and second matrix, and the difference vector between the first feature vector of the first matrix and each historical row vector in the latest period of the first matrix is ​​obtained.

[0074] The second eigenvector of the second matrix is ​​determined and compared with the standard eigenvector of the communication device when it is in a non-working state to obtain the static principal element. The change attenuation of the static principal element in the third matrix obtained by extracting the second matrix according to the latest period is analyzed.

[0075] Compare all static principal elements with the elements of each difference vector, and combine the element combination of the difference principal elements of the corresponding difference vector with the change attenuation of all static principal elements to obtain the dynamic attenuation group, and adjust the corresponding sub-attenuation terms to construct the communication loss function.

[0076] Based on the communication loss function and the determination result of the real-time collected environmental electromagnetic interference intensity, the communication connection confidence based on the current state of the smart cash box is determined, the final communication mode is locked, and a data transmission channel is established.

[0077] In this embodiment, the communication device refers to the hardware module on the smart cash box used for data transmission. In this solution, the WiFi module and Bluetooth module are the core hardware for establishing a data transmission channel.

[0078] Historical work logs refer to the working status records of communication devices within a preset period (such as 7 days), including working time sequence data (connection duration, transmission rate, bit error rate, and power consumption during transmission periods) and non-working time sequence data (signal strength, sleep power consumption, and connection waiting time during standby periods), which are stored in eMMC flash memory.

[0079] Work sequence analysis refers to the structured processing of historical logs of communication devices in data transmission state (such as uploading location data to the platform and receiving control instructions), extracting timestamps and transmission parameters to form matrix data for analyzing communication stability.

[0080] Non-working time sequence analysis refers to the structured processing of historical logs of communication devices in standby / sleep state (no data transmission, only maintaining basic connection), extracting timestamps and standby parameters to form matrix data for analyzing the static performance of the device.

[0081] The first matrix refers to the two-dimensional data matrix obtained after working time sequence analysis. The row vectors correspond to the latest period, such as one segment per hour in different time segments within the last 24 hours. The column vectors correspond to working parameters such as connection duration (min), transmission rate (Mbps), bit error rate (%), and power consumption (mA). It is denoted as M1=[m1_i2j2], where i2=1 to 24 and j2=1 to 4.

[0082] The second matrix refers to the two-dimensional data matrix obtained after non-working time sequence analysis. The row vectors correspond to one segment per hour in different time segments within the latest period, and the column vectors correspond to non-working parameters such as signal strength dBm, sleep power consumption mA, and connection waiting time s. It is denoted as M2=[m2_i3j3], where i3=1 to 24 and j3=1 to 3.

[0083] The first eigenvector refers to the core vector extracted by principal component analysis (PCA) of the first matrix M1, which reflects the overall pattern of the working state of the communication device, such as average connection time and average transmission rate, and is denoted as V1=[v11,v12,v13,v14].

[0084] The difference vector refers to the difference vector between each historical row vector of the latest period in the first matrix M1, such as the row vector m1_24j2 of the 24th hour, and the first eigenvector V1, denoted as D1_i2=m1_i2j2-V1, and i2=1 to 24, reflecting the deviation between the working status of a single period and the overall pattern.

[0085] The second eigenvector refers to the core vector extracted by PCA from the second matrix M2, which reflects the overall pattern of the communication device in its non-working state, such as average signal strength and average sleep power consumption, and is denoted as V2=[v21,v22,v23].

[0086] Standard eigenvector: refers to the communication device operating under standard laboratory conditions (electromagnetic interference). The non-working state reference vector (without obstruction) is provided by the manufacturer and pre-stored in the main control module, denoted as Vs=[vs1,vs2,vs3]. For example, the standard signal strength of the WiFi module is -60dBm and the standard sleep power consumption is 5mA.

[0087] Static principal elements refer to non-working parameters whose difference rate is ≤5% after comparing the second feature vector V2 with the standard feature vector Vs. These are parameters with high stability, such as a signal strength difference rate of 3% and a sleep power consumption difference rate of 2%, reflecting the basic performance of the communication device in its non-working state.

[0088] The third matrix refers to extracting segments from the second matrix M2 that are similar to the current environmental conditions within the latest period (such as electromagnetic interference in the current environment). Extract interference from historical logs The submatrix formed by the fragments is denoted as M3, and is used to analyze the changes of static principal elements under similar environments.

[0089] The change decay refers to the difference between the value of the static principal element in the third matrix M3 and the corresponding value of the standard eigenvector Vs, denoted as . m3_i4j4-vs_j4 (where m3_i4j4 is the value of the static principal element in M3) reflects the degree of influence of the environment on the static principal element, such as the attenuation amount when the signal strength decreases from -60dBm to -65dBm. -5dBm.

[0090] Dynamic decay groups refer to the decay amount of changes in all static principal elements. This is associated with the principal difference element in each difference vector D1_i2 to form a set of attenuation data, which reflects the correlation between dynamic working deviation and static attenuation.

[0091] The communication loss function refers to the mathematical function that quantifies the communication quality loss based on the dynamic attenuation group G, denoted as It is obtained based on weighted summation, with the weights determined by fitting experimental data. Specifically, the weight for bit error rate deviation is 0.4, the weight for signal strength attenuation is 0.3, the weight for transmission rate deviation is 0.2, and the weight for power consumption deviation is 0.1.

[0092] In this embodiment, the communication connection confidence refers to the confidence level combined with the communication loss function. The intensity of environmental electromagnetic interference is used as an indicator to quantify the reliability of communication channels, denoted as... Its value ranges from 0 to 1. The closer the confidence level is to 1, the higher the communication reliability.

[0093] In this embodiment, if the data transmission time period of the past 24 hours is extracted, the first matrix M1 (24 rows × 4 columns) is obtained, and some data is shown in Table 1:

[0094] Table 1 First Matrix M1

[0095]

[0096] In this embodiment, some of the second matrix M2 is shown in Table 2:

[0097] Table 2 Second Matrix M2

[0098]

[0099] In this embodiment, PCA analysis is performed on M1 to extract the first feature vector V1=[54.5,1.8,0.012,80.2], which represents the average connection duration of 54.5 min, the average transmission rate of 1.8 Mbps, the average bit error rate of 0.012%, and the average power consumption of 80.2 mA. The difference vector between the row vector [52,1.6,0.015,78] and V1 at the 24th hour is calculated to be [-2.5,-0.2,0.003,-2.2].

[0100] The beneficial effects of the above technical solution are as follows: by performing refined analysis of the historical logs of the communication device, extracting feature vectors and analyzing attenuation, a quantitative communication loss function and confidence evaluation model are constructed, realizing data-driven communication mode selection based on the status of the container and the environment. Compared with traditional fixed mode or single parameter judgment, it can more accurately match the communication needs in complex environments, significantly reduce the risk of communication interruption caused by electromagnetic interference and device performance fluctuations, and ensure the stability and continuity of data transmission.

[0101] This invention provides a management method for end-to-end IoT information control of smart cash registers, comprising determining the communication connection confidence level based on the current state of the smart cash register, including:

[0102] The interference influence coefficient is obtained by matching the electromagnetic interference intensity It of the environment in which the smart cash box is located with a preset intensity level-influence correspondence table. ;

[0103] For the communication loss function Perform time-weighted correction to obtain the corrected loss function. ,in, The current moment; The time-series sampling interval is n; n is the length of the historical sampling window. Let be the weight of the i-th historical sampling point, and ;

[0104] Calculate communication connection confidence ,in, The coupling factor is based on the current state;

[0105] Confidence of the communication connection The final communication mode is determined by comparing it with a threshold range.

[0106] In this embodiment, the threshold range is a pre-set reliability standard that distinguishes different communication modes. Taking the WiFi and Bluetooth combined mode as an example:

[0107] like Falling within the high reliability range Choose WiFi mode, as WiFi has a higher transmission rate and is suitable for high-reliability scenarios;

[0108] like Falling into the lower reliability range Switch to Bluetooth mode, as Bluetooth has stronger anti-interference capabilities and is suitable for complex environments.

[0109] In this embodiment, the preset intensity classification-influence correspondence table refers to the electromagnetic interference intensity classification and interference influence coefficient stored in the main control unit beforehand. The corresponding relationship table is shown in Table 3:

[0110] Table 3 Preset Intensity Grading - Corresponding Effects Table

[0111]

[0112] In this embodiment, the time-series sampling interval This refers to the time interval for collecting historical communication loss function data. In this scheme, it is set to 10 seconds, meaning that data is recorded once every 10 seconds. Value, denoted as .

[0113] In this embodiment, the historical sampling window length n refers to the number of historical sampling points participating in the time-weighted correction. In this scheme, n=5, that is, the historical data of the 5 sampling points before the current time (data within 50 seconds) is used for correction to balance timeliness and data volume.

[0114] In this embodiment, the coupling factor This refers to a coefficient reflecting the coupling degree between the smart vending machine's current state (such as movement speed and battery level) and the communication device. It collects the smart vending machine's current state parameters, including the remaining battery power percentage. Cash box opening / closing status ,in, Indicates that it is turned on. Indicates that it is closed, and ,and .

[0115] The beneficial effects of the above technical solution are as follows: it quantifies environmental interference based on the electromagnetic interference influence coefficient, improves the timeliness of the loss function by time-weighted correction, considers the additional impact of the container status on communication by the coupling factor, and constructs a scientific communication connection confidence model. This model can objectively and accurately assess the reliability of the communication channel, provide a quantitative basis for switching between dual-mode communication modes, avoid switching errors caused by subjective judgment, and further ensure the stability of data transmission. It is especially suitable for mobile transportation scenarios with complex electromagnetic environments.

[0116] This invention provides a management method for the full-process IoT information control of smart cash registers. Based on the national cryptographic chip, the method encrypts the collected cash register opening and closing status, location trajectory, internal item measurement parameters, and transmitted control commands and node identity information, including:

[0117] Each acquisition parameter involved in each acquisition moment is encoded and randomly combined to obtain the first code;

[0118] Extract the start and end positions of each operation item from the entire process. Using the end position of the first operation item as the starting point and the initial start position of the latest executed operation item as the ending point, obtain the first two adjacent moments of each trigger position. At the same time, obtain the second two adjacent moments where there is a mode switch, and determine the operation item change status of each second two adjacent moments for encoding to obtain the second code.

[0119] Based on the data changes at the first two adjacent time points, analyze the multidimensional satisfaction factors of the change conditions based on the corresponding adjacent operation items, and perform separate extended analysis on the same-dimensional satisfaction factors at all the first two adjacent time points and comprehensive extended analysis on the multidimensional satisfaction factors at all the first two adjacent time points to obtain the compensation function.

[0120] Based on the compensation function, the first code, and the second code, the influencing factors at the corresponding acquisition time are obtained;

[0121] Based on the national cryptographic chip, the collected data is encrypted according to the national cryptographic algorithm and in combination with influencing factors.

[0122] In this embodiment, the acquisition parameters refer to the cash box status and item data obtained at the acquisition time, including the opening and closing status (high and low levels output by the Hall sensor, corresponding to opening / closing), location trajectory (latitude and longitude coordinates output by GPS), and the item measurement parameters inside the box (item weight / amount converted by the weight sensor), which are the core data for encryption processing.

[0123] The first code refers to the unique code obtained by binary encoding and random arrangement of all acquisition parameters at the acquisition time. For example, at acquisition time 1, the acquisition parameters are: on / off state = off (low level, code 0101), position trajectory = 30.1234° North latitude (code 00110010), 120.5678° East longitude (code 10010110), and the measurement parameter of the items in the box = 1 million yuan (weight 10kg, code 01010000). The encoding module generates a pseudo-random arrangement of position → measurement → on / off, resulting in the first code 0011001010010110010100000101 (32 bits).

[0124] In this embodiment, mode switching refers to the change of the working mode of the smart cash box, which is automatically determined by the main control module based on the operation item. The working modes in this solution include storage mode (cash box is stationary, low frequency data reporting), transportation mode (cash box moves, high frequency data reporting), and inventory mode (cash box is opened, real-time reporting of measurement data). The mode switching is triggered by a change in the operation item (such as opening the box and counting triggering storage mode → inventory mode).

[0125] The change status of an operation item refers to the change of the operation item corresponding to two adjacent times, such as 10:29 (storage mode, operation item = closed storage) → 10:31 (transportation mode, operation item = transportation handover), the change status is closed storage → transportation handover, which is used to identify the operation association of mode switching.

[0126] The second code refers to the unique code obtained by binary encoding the change status of the operation item at two adjacent times. The length is fixed at 16 bits. For example, the code for closing the box and storing → transporting and handing over is 1010011011001001, which is used to associate mode switching and operation items.

[0127] Multidimensional satisfaction factors refer to multiple dimensions of judgment factors that determine whether the change conditions of adjacent operation items are met based on the data changes of the first two adjacent time points. These factors include location change satisfaction factors (whether the location is within the preset range when the operation item changes), time interval satisfaction factors (whether the interval between operation items is within the preset duration), and parameter fluctuation satisfaction factors (whether the measurement parameters are within the allowable fluctuation range). For example, the location change satisfaction factor for the transportation handover operation item is that the distance from the vault coordinates to the transport vehicle coordinates is less than or equal to 1km.

[0128] The compensation function is a mathematical function constructed based on the results of same-dimensional extended analysis and multi-dimensional comprehensive analysis. It is used to correct the deviation between the first code and the second code (such as the deviation of the coded data caused by sensor error).

[0129] Influencing factors refer to the core set of factors obtained by combining the parameter features of the first encoding, the operation item state features of the second encoding, and the correction features of the compensation function. These factors are used to optimize the encryption process of the national cryptographic algorithm (such as as auxiliary parameters of the key) and improve encryption strength.

[0130] In this embodiment, the sequence of operations is as follows: Warehouse storage (trigger start / end position = 30.1234°N, 120.5678°E, trigger end time = 09:30) → Box locking (trigger start / end position = same coordinates, trigger end time = 09:45) → Transportation handover (trigger start position = same coordinates, trigger end position = 30.1235°N, 120.5679°E, trigger start time = 10:00); taking the trigger end time of the first operation item, warehouse storage, at 09:30, as the starting point, the trigger start time of the latest operation item, transportation handover, is 1. With 0:00 as the endpoint, extract the first two adjacent times for each trigger position: storage trigger position (vault) adjacent times 09:29 / 09:31, lockout trigger position (vault) adjacent times 09:44 / 09:46, and transport handover trigger start position (vault) adjacent times 09:59 / 10:01; the current mode switches to storage mode → transport mode (triggered at 09:59), the second two adjacent times 09:59 / 10:01, the operation item changes the status to lockout → transport handover, the code is 10100110 (8 bits), resulting in the second code 10100110;

[0131] In this embodiment, the data changes between the first two adjacent time points are analyzed: for example, 09:44 (opening / closing = closed, location = vault, measurement = 100kg) and 09:46 (opening / closing = closed, location = vault, measurement = 100kg). The position change amplitude is 0m (satisfying the condition that the lock position remains unchanged when the vault is closed), the time interval is 2 minutes (satisfying the condition of less than or equal to 5 minutes), and the measurement fluctuation is 0kg (satisfying the condition of less than or equal to 0.1kg). All multidimensional satisfaction factors are met. A total of 5 groups of the first two adjacent time points are analyzed. The pass rate of the same dimension satisfaction factors is: position change pass rate 100%, time interval pass rate 100%, measurement fluctuation pass rate 100%, and the average value is 100%. The synergy rate of multidimensional satisfaction factors is 5 / 5 = 100%. The compensation function F = 0.6 × 1.0 + 0.4 × 1.0 = 1.0.

[0132] Extract the first 32-bit coding feature, which includes location / metering / opening / closing parameters; the second 8-bit coding feature, which represents the change status as closed container to transport; and the compensation function feature F = 1.0 (no bias), forming a set of influencing factors {coding length: 32 + 8 bits; parameter integrity: location + metering + opening / closing; change type: storage → transport; correction value: 1.0}.

[0133] The national cryptographic chip calls the SM4 algorithm, with the initial key being K=0x0123456789ABCDEF0123456789ABCDEF. The correction value of 1.0 in the influencing factors is used as the key expansion parameter (adjusting the S-box replacement rule of the round function). The collected data 2024-05-20 10:00, closed, 30.1234° / 120.5678°, 100kg is encrypted, and the ciphertext 9B2D6E8F1A3C5E7D0B4F2A6C8E0D1B3F is output.

[0134] The beneficial effects of the above technical solution are as follows: by associating the first code with the collected parameters and the second code with the operation item changes, the data and the control process are deeply bound together; by constructing a compensation function through multi-dimensional factor extension analysis, the data deviation is corrected; and finally, the influencing factors are integrated into the national cryptographic encryption process, which significantly improves the uniqueness and anti-cracking ability of the encrypted data compared with traditional fixed key encryption, while ensuring the adaptability of the encrypted data to the control scenario, effectively preventing data theft and tampering, and ensuring the security of the entire process data of the cash box.

[0135] This invention provides a management method for the full-process IoT information control of smart cash registers. It involves performing individual extended analysis on the same-dimensional satisfaction factors of all first two adjacent time points and comprehensive extended analysis on the multi-dimensional satisfaction factors of all first two adjacent time points to obtain a compensation function, including:

[0136] Based on the full-process control attributes of smart cash boxes, the core dimensions corresponding to the same-dimensional satisfaction factors are divided into time-series-location trajectory dimension, time-series-single measurement dimension, and multi-parameter correlation dimension.

[0137] Obtain the same-dimensional extension coefficient of a single dimension at the corresponding time, obtain the comprehensive correlation degree of multiple dimensions at the corresponding time, and obtain the expansion coefficient along the time axis at the corresponding time to obtain the compensation function at the corresponding time.

[0138] In this embodiment, the specific process of obtaining the compensation function at the corresponding time includes:

[0139] Get Dimensions Calculate the data similarity between the parameter data of the first interval before the first two adjacent time intervals at the i1th time. And k=1,2,3, where, For dimension The m-th parameter value within the first interval; For dimension The m-th parameter value within the second interval; M is the total number of parameters within the interval;

[0140] Computational Dimensions degree of difference ,in, For dimension The preset standard values ​​of the core parameters in the previous moment; For dimension The core parameter values ​​of the previous time step; For dimension The core parameter values ​​at the later time step;

[0141] Based on data similarity And degree of difference Generate Dimensions Same-dimensional extension coefficients at the i1th first two adjacent time points ;

[0142] Calculate the correlation between any two dimensions and the core parameters within the first interval. And obtain the comprehensive correlation of multi-dimensional data. , as the multidimensional extension coefficient at that moment, where, The function for calculating covariance; This is the variance calculation function; These are the core parameter values ​​within the first interval of dimension p; These are the core parameter values ​​within the first interval of dimension q;

[0143] Based on the priority of smart cash box management, the same dimension extension coefficient is applied. Weighted integration is performed to obtain the integrated value Zi1 at the corresponding time point;

[0144] Calculate the expansion coefficient along the time axis at the corresponding time point. ,in, This refers to the time point preceding the corresponding moment. This is the time point after the corresponding moment; The preset standard duration for the actual operation item at the corresponding time;

[0145] The corresponding time Multiply them, and use the result as a compensation function.

[0146] In this embodiment, the full-process control attribute refers to the core characteristics of the full-process control of the smart cash box, including temporal continuity (operations are executed in chronological order without jumps), location correlation (operations are strongly bound to physical locations, such as storage only being performed in the vault), and parameter coordination (collected parameters corroborate each other, such as the opening state should be accompanied by changes in measurement parameters), which are the basis for dividing the core dimensions.

[0147] The core dimensions refer to the compensation function analysis dimensions based on the attributes of the entire process control, totaling three:

[0148] Time-location trajectory dimension: Correlate time with location trajectory to analyze the continuity and rationality of location at different times. For example, during transportation, the location should change gradually along the route without abrupt changes.

[0149] Time series - single measurement dimension: Correlate time with a single measurement parameter (such as the weight of items in the box) to analyze the stability and compliance of the measurement parameter at different times. For example, the measurement parameter should not change significantly when the storage is static.

[0150] Multi-parameter correlation dimension: Correlate multiple collected parameters (such as open / closed status, location, and measurement) and analyze the synergy between parameters. For example, the open status and vault location should be accompanied by changes in measurement parameters (counting operation).

[0151] Same-dimensional satisfaction factors refer to satisfaction factors under a single core dimension, such as the position change amplitude of the time-location trajectory dimension ≤ 0.1km / minute, the measurement fluctuation of the time-single measurement dimension ≤ 0.1kg, and the opening and closing of the multi-parameter correlation dimension → measurement change.

[0152] In this embodiment, the weighted integration value of the same dimension extension coefficient is calculated based on the control priority of each core dimension (time series-location trajectory weight 0.4, time series-single measurement weight 0.3, multi-parameter association weight 0.3).

[0153] The beneficial effects of the above technical solution are as follows: by dividing the core dimensions that match the attributes of the whole process control, the compensation function is decomposed into same-dimensional extension analysis, multi-dimensional correlation analysis, and time expansion analysis, ensuring that the compensation function can fully reflect the data continuity, collaboration, and time compliance; compared with traditional single-parameter compensation, the compensation function of this solution is more in line with the cash box control scenario, has higher correction accuracy, provides a more reliable basis for deviation correction for subsequent encryption processing, and further improves the accuracy and security of encrypted data.

[0154] This invention provides a management method for end-to-end IoT information control of smart cash registers. Based on the compensation function, the first code, and the second code, the influencing factors at the corresponding data collection time are obtained, including:

[0155] Extract the acquisition time interval corresponding to the first code and the operation item triggering time interval corresponding to the second code, and verify the time sequence coverage relationship between the acquisition time and the operation item to determine the time sequence matching degree between the two.

[0156] The initial weights of the compensation function at the corresponding time point are adjusted based on the time-series matching degree.

[0157] Obtain the associated weights of the scene at the corresponding time for the compensation function, the first code, and the second code from the scene-weight lookup table, and combine them with the adjusted initial weights to obtain the updated weights for the compensation function, the first code, and the second code, respectively.

[0158] The parameter features of the first code, the operation item state features of the second code, and the correction features of the compensation function are mapped hierarchically. The basic feature layer is constructed with the element with the highest update weight as the core, and the remaining elements are embedded into the associated nodes of the basic feature layer according to their update weights to generate a preliminary set of influence factors.

[0159] In this embodiment, the acquisition time interval refers to the time range corresponding to the first encoding, that is, the acquisition and encoding period of the acquisition parameters, which consists of 1 second before the acquisition time to 1 second after the acquisition time. For example, if the acquisition time is 10:00:00, the interval is 10:00:00±1s, ensuring that the complete acquisition and encoding process is covered.

[0160] The operation item triggering time interval refers to the time range corresponding to the second code, that is, the time period from the start of the operation item to the end of the trigger. It is determined by the start time and end time of the operation item. For example, if the transportation exchange starts at 10:00:00 and ends at 10:05:00, the interval is 10:00:00-10:05:00, reflecting the execution time of the operation item.

[0161] Timing coverage refers to the time overlap between the data acquisition interval and the operation triggering interval, including complete coverage (the acquisition interval is within the triggering interval), partial coverage (the acquisition interval and the triggering interval partially overlap), and no coverage (the acquisition interval and the triggering interval do not overlap). It is the basis for determining the timing matching degree.

[0162] Timing matching degree refers to the degree of overlap between the data acquisition time interval and the operation item triggering time interval, which is calculated by dividing the overlap duration by the data acquisition time interval duration.

[0163] The initial weight W0 refers to the initial weighting coefficient set for the compensation function F based on the temporal matching degree M0. W0 = M0 × 0.8 + 0.2, ensuring that W0 = 0.2 when M0 = 0, avoiding a weight of 0. The larger M is, the larger W0 is, reflecting the degree of correlation between the compensation function and the current operation item.

[0164] The scenario-weight lookup table refers to the table that pre-stores the correspondence between the control scenarios and the associated weights of the compensation functions, first codes, and second codes in the main control module, as shown in Table 4:

[0165] Table 4 Scenario-Weight Comparison Table

[0166]

[0167] In this embodiment, the control scenario refers to the control stage of the smart cash box based on the operation item. For example, the storage scenario corresponds to the storage and locking operation items, the transportation scenario corresponds to the transportation handover operation item, and the inventory scenario corresponds to the opening and inventory operation item. The main control unit automatically determines the operation item.

[0168] The updated weight Wup refers to the final weighting coefficient obtained by combining the initial weight W0 and the associated weight Wsc. Wup (compensation function) = W0 × Wsc (compensation function), Wup (first code) = 1.0 × Wsc (first code), Wup (second code) = 1.0 × Wsc (second code). The default value is 1.0 for those without initial weights, and it is used to determine the hierarchical priority of influencing factors.

[0169] Parameter characteristics: refers to the acquisition parameter information contained in the first code C1, such as code length, parameter type (location / metering / on / off), and parameter completeness (whether it contains all parameters).

[0170] Operation item status characteristics: refers to the operation item change information contained in the second code C2, such as change type (storage → transportation), code length, and change time.

[0171] Correction characteristics: refers to the numerical characteristics of the compensation function F, such as the magnitude of the F value (degree of deviation) and the basis for the calculation of F (same-dimensional / multi-dimensional analysis results).

[0172] In this embodiment, the basic feature layer is constructed with the compensation function F, which has the highest update weight, as the core. The modified feature of F is F=0.67 (based on time-location / quantitative / multi-parameter dimension analysis, same-dimensional extension coefficient 1.0, comprehensive correlation degree 1.0, expansion coefficient 0.6703).

[0173] The parameter feature C1 of the first code C1 is encoded as a 32-bit binary code, which includes the location (30.1234°N / 120.5678°E), measurement (100kg), and on / off (closed) parameters. The parameter integrity is 100% as the associated feature 1, which is embedded in the parameter association node of the basic feature layer.

[0174] The operation item status feature C2 of the second code C2 is encoded as an 8-bit binary code, with change type = box locking → transportation handover, change time = 10:00:00, and code integrity of 100% as the associated feature 2, and is embedded into the operation item associated node of the basic feature layer.

[0175] Preliminary set of influencing factors = {Basic features: compensation function F, modified features: F=0.67 (same-dimensional extension coefficient 1.0, comprehensive correlation degree 1.0, expansion coefficient 0.6703), correlation feature 1: first code C1, parameter features: 32 bits, including position / measurement / open / close (complete), parameter values: 30.1234° / 120.5678°, 100kg, closed, correlation feature 2: second code C2, operation item status features: 8 bits, change type = close box → transport, change time = 10:00:00}.

[0176] The beneficial effects of the above technical solution are as follows: it ensures the temporal correlation between influencing factors and operation items through time-series matching degree verification; it matches the priority requirements of different control scenarios through scenario-based weight configuration; and it constructs a structured set of influencing factors through hierarchical mapping. Compared with the traditional disordered element stacking, it makes the influencing factors more in line with the control scenario and the hierarchy clearer. It provides scenario-adaptive and key-point-focused encryption input for subsequent national cryptographic encryption, further improving the targeting and anti-cracking ability of encryption. At the same time, it ensures the interpretability of influencing factors, which facilitates subsequent data traceability and anomaly investigation.

[0177] This invention provides a management method for end-to-end IoT information control of smart cash registers, which synchronizes in real time to a consortium blockchain network for distributed verification, including:

[0178] The consortium blockchain network nodes are divided into a core verification layer, a secondary verification layer, and an audit verification layer. Differentiated verification permissions and data visibility ranges are preset for each layer of nodes.

[0179] The core verification layer performs basic verifications on data encryption integrity, dynamic hardware identifier validity, and node identity and authorization legality, and generates basic verification credentials that are synchronized to the corresponding secondary verification layer group.

[0180] The secondary verification layer is based on the basic verification credentials and cross-verifies the consistency of the data with the historical chain data and the rationality of the operation sequence. The group leader node summarizes the verification results within the group to form a secondary verification report.

[0181] The audit verification layer conducts sampling reviews of the verification process for high-security-level data, while low / medium-security-level data is only reviewed when an anomaly warning is triggered.

[0182] In this embodiment, the core verification layer node, such as the XX Bank headquarters node, receives the encrypted data ciphertext, dynamic hardware identifier HC32L136-00987654321FEDCBA, and node permission information OP456 uploaded by the smart vault. The core node decrypts the ciphertext using the SM4 algorithm, compares the ciphertext hash value with the uploaded hash digest to verify the encryption integrity, queries the blockchain historical identifier records to confirm that the hardware identifier has not been forged, and compares the permission database to confirm that OP456 has the authorization for transportation and handover operations. After successful verification, a basic verification credential is generated.

[0183] In this embodiment, the XX Bank branch node in the secondary verification layer compares the cash box data corresponding to the encrypted message with the bank's cash box ledger (confirming that cash box ID001234 belongs to the bank and the measurement parameter of RMB 1 million is consistent with the ledger); the YY Logistics network node compares the data time sequence (the transportation handover operation trigger time of 10:00 matches the logistics dispatch time of 9:55); both sets of node verification results are passed, and the group leader node (XX Bank branch node) summarizes and forms a secondary verification report.

[0184] In this embodiment, if the current cash box measurement parameter is 1 million yuan (medium security level), the audit verification layer node (local financial regulatory bureau node) will not trigger real-time review; if the measurement parameter is 6 million yuan (high security level), the audit verification layer node will retrieve the basic verification certificate + secondary verification report + original encrypted data, sample and review the signature legality of the core node and the cross-verification logic of the secondary node, and record the audit pass mark on the blockchain after the review is passed; if any objection is found (such as a contradiction in the verification conclusion of the secondary node), the manual verification process will be triggered.

[0185] The beneficial effects of the above technical solution are as follows: Through a three-layer distributed verification architecture of core-secondary-audit, multi-subject authorized access verification of control data is achieved: the core layer ensures basic data security, the secondary layer strengthens the consistency of multi-subject data, and the audit layer focuses on the review of high-risk data. This not only avoids the single point of failure and tampering risk of centralized verification, but also balances security and privacy through differentiated permissions and data visibility scope, ensuring the immutability and traceability of control data throughout the entire process, and significantly improving the credibility and security level of cash box control.

[0186] This invention provides a management method for end-to-end IoT information control of smart cash registers, which automatically generates new unique hardware identifiers for updating, including:

[0187] After the update is triggered, the original root key and historical update log of the current hardware identifier are automatically retrieved based on the national cryptographic chip. A temporary encryption seed is generated based on the original root key, and hash fragments of the last n0 on-chain data are extracted as auxiliary factors. The security enhancement function is determined by combining the temporary encryption seed and auxiliary factors. This is then combined with the current state parameters of the cash box and an intermediate identifier generated using the national cryptographic algorithm. This intermediate identifier is then encrypted again using a unique verification code pre-allocated by the core verification layer node to form a new unique hardware identifier. This new identifier includes a historical identifier traceability field and an update trigger reason flag. The security enhancement function is as follows:

[0188] Where N0 is the number of auxiliary factors; The security increment coefficient between the s0th auxiliary factor and the temporary encryption seed; The mutual exclusion angle between the s0th auxiliary factor and the temporary encryption seed The value; This is a secure increment function based on the temporary encryption seed and all auxiliary factors.

[0189] In this embodiment, when the original root key is pre-set with the national cryptographic chip at the factory, the original root key is written into the security key area, which is inaccessible at this time;

[0190] The temporary encryption seed generation is achieved by the SM3 hash algorithm module built into the national cryptographic chip, which generates a 16-byte temporary encryption seed based on the original root key.

[0191] Hash fragment extraction involves the main control module retrieving the hash values ​​of the three most recent on-chain data from the blockchain and extracting the first 16 bits of the fragment.

[0192] The new identifier is generated by combining a national cryptographic chip with a temporary encryption seed, a security value-added function, and a check code to generate a new hardware identifier that includes a traceability field and a trigger marker.

[0193] In this embodiment, for example, when the cash box has completed 50 operations (triggering an update), the national cryptographic chip retrieves the original root key and historical update log (the most recent old identifier is HC32L136-00123456789ABCDEF); and generates a temporary encryption seed using the SM3 algorithm: S=0x789ABCDEF0123456789ABCDEF01234567;

[0194] Extract the hash fragments of the three most recent on-chain data: d1=0x1122334455667788, d2=0x99AABBCCDDEEFF00, d3=0x0011223344556677, and calculate the security increment function;

[0195] The current status parameters of the cash box are: location = 30.1234° North latitude, number of operations = 50. The national cryptographic chip, combined with the temporary encryption seed and Hf, generates an intermediate identifier: MID = HC32L136-XXXXYYYYZZZZAAAA;

[0196] The national cryptographic chip calls the pre-allocated verification code (0xABCDEF1234567890) of the core verification layer, performs secondary encryption on the intermediate identifier, embeds the old identifier traceability field (0x12345678) and trigger reason flag (01), and generates a new hardware identifier: HC32L136-87654321ZZZZAAAA1234567801;

[0197] The new identifier is synchronized to the IoT management platform and the blockchain, and historical update logs are updated and stored in an encrypted manner.

[0198] In this embodiment, the security enhancement coefficient is a value pre-configured through experimental fitting or control scenarios. It is used to quantify the security correlation between the auxiliary factor of the corresponding sequence number and the temporary encryption seed. For example, if the hash length of the auxiliary factor perfectly matches the length of the temporary encryption seed, it can be pre-configured. =1.0; If there is a difference in length, adjust linearly according to the proportion of the difference, such as when the length difference is 20%, =0.8.

[0199] In this embodiment, the security features of the auxiliary factor and the temporary encryption seed (such as the binary distribution of hash values ​​and the entropy distribution of pseudo-random numbers) are mapped to a multi-dimensional space (such as a 128-dimensional vector space), and the angle between the two vectors is calculated as the theoretical value of the mutual exclusion angle. For example, if the two vectors are completely orthogonal (features do not overlap), then... =90°; if the heights coincide, then =0°.

[0200] The beneficial effects of the above technical solution are as follows: Through the dynamic identifier generation logic of original root key + temporary seed + multiple auxiliary factors, the hardware identifier can be securely updated. The new identifier integrates control data features and traceability information, which not only avoids the risk of fixed identifiers being copied, but also supports the historical traceability of identifiers. Combined with the core verification layer check code for secondary encryption, the uniqueness and anti-cracking ability of the cash box identity identifier are significantly improved, and the identity security of the entire cash box control process is further strengthened.

[0201] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A management method for end-to-end IoT-based information control of smart cash registers, characterized in that, include: Step 1: Using a multi-mode communication mode, a data transmission channel is automatically established with the IoT management platform based on the current status and environmental parameters of the smart cash box. The multi-mode communication mode includes at least two of the following communication methods: WiFi, Bluetooth, StarFlash, and 5G. Step 2: Bind the initial unique hardware identifier of the smart cash box to the national cryptographic algorithm. Based on the national cryptographic chip, encrypt the collected cash box opening and closing status, location trajectory, measurement parameters of items in the box, as well as the transmitted control commands and node identity information. When the smart cash box completes a preset number of operations, or when a physical disassembly attempt to target the smart cash box is detected, a new unique hardware identifier is automatically generated and updated. Step 3: Associate the encrypted end-to-end control data, the dynamically updated hardware identification information, and the corresponding node permission information, and synchronize them to the consortium blockchain network in real time for distributed verification; Step 4: When each control node connects to the smart cash box via a communication device through a terminal device, the terminal identity information is decrypted by a national cryptographic chip, and the permission association data and dynamically updated hardware identification information stored in the consortium blockchain network are retrieved to complete real-time verification. After the verification is successful, the corresponding operation permission is automatically triggered, and the operation completion log is immediately uploaded to the consortium blockchain network for update, thus completing the entire process control.

2. The management method for full-process IoT information control of smart cash registers according to claim 1, characterized in that, Based on the current status and environmental parameters of the smart cash register, a data transmission channel is automatically established with the IoT management platform, including: Identify the communication devices connected to the smart cash box and retrieve the historical work logs of each communication device; The historical work log is analyzed by working time sequence and non-working time sequence to obtain the corresponding first matrix and second matrix, and the difference vector between the first feature vector of the first matrix and each historical row vector in the latest period of the first matrix is ​​obtained. The second eigenvector of the second matrix is ​​determined and compared with the standard eigenvector of the communication device when it is in a non-working state to obtain the static principal element. The change attenuation of the static principal element in the third matrix obtained by extracting the second matrix according to the latest period is analyzed. Compare all static principal elements with the elements of each difference vector, and combine the element combination of the difference principal elements of the corresponding difference vector with the change attenuation of all static principal elements to obtain the dynamic attenuation group, and adjust the corresponding sub-attenuation terms to construct the communication loss function. Based on the communication loss function and the determination result of the real-time collected environmental electromagnetic interference intensity, the communication connection confidence based on the current state of the smart cash box is determined, the final communication mode is locked, and a data transmission channel is established.

3. The management method for full-process IoT information control of smart cash registers according to claim 2, characterized in that, Determining the communication connection confidence based on the current state of the smart cash register includes: The interference influence coefficient is obtained by matching the electromagnetic interference intensity It of the environment in which the smart cash box is located with a preset intensity level-influence correspondence table. ; For the communication loss function Perform time-weighted correction to obtain the corrected loss function. ,in, The current moment; The time-series sampling interval is n; n is the length of the historical sampling window. Let be the weight of the i-th historical sampling point, and ; Calculate communication connection confidence ,in, The coupling factor is based on the current state; Confidence of the communication connection The final communication mode is determined by comparing it with a threshold range.

4. The management method for full-process IoT information control of smart cash registers according to claim 1, characterized in that, Based on the aforementioned national cryptographic chip, the collected data on the opening and closing status of the cash box, its location trajectory, the measurement parameters of the items inside the box, as well as the transmitted control commands and node identity information, are encrypted, including: Each acquisition parameter involved in each acquisition moment is encoded and randomly combined to obtain the first code; Extract the start and end positions of each operation item from the entire process. Using the end position of the first operation item as the starting point and the initial start position of the latest executed operation item as the ending point, obtain the first two adjacent moments of each trigger position. At the same time, obtain the second two adjacent moments where there is a mode switch, and determine the operation item change status of each second two adjacent moments for encoding to obtain the second code. Based on the data changes at the first two adjacent time points, analyze the multidimensional satisfaction factors of the change conditions based on the corresponding adjacent operation items, and perform separate extended analysis on the same-dimensional satisfaction factors at all the first two adjacent time points and comprehensive extended analysis on the multidimensional satisfaction factors at all the first two adjacent time points to obtain the compensation function. Based on the compensation function, the first code, and the second code, the influencing factors at the corresponding acquisition time are obtained; Based on the national cryptographic chip, the collected data is encrypted according to the national cryptographic algorithm and in combination with influencing factors.

5. The management method for full-process IoT information control of smart cash registers according to claim 4, characterized in that, By performing individual extended analysis on all same-dimensional satisfaction factors at the first two adjacent time points and comprehensive extended analysis on multi-dimensional satisfaction factors at all first two adjacent time points, the compensation function is obtained, including: Based on the full-process control attributes of smart cash boxes, the core dimensions corresponding to the same-dimensional satisfaction factors are divided into time-series-location trajectory dimension, time-series-single measurement dimension, and multi-parameter correlation dimension. Obtain the same-dimensional extension coefficient of a single dimension at the corresponding time, obtain the comprehensive correlation degree of multiple dimensions at the corresponding time, and obtain the expansion coefficient along the time axis at the corresponding time to obtain the compensation function at the corresponding time.

6. The management method for full-process IoT information control of smart cash registers according to claim 4, characterized in that, Based on the compensation function, the first encoding, and the second encoding, the influencing factors corresponding to the acquisition time are obtained, including: Extract the acquisition time interval corresponding to the first code and the operation item triggering time interval corresponding to the second code, and verify the time sequence coverage relationship between the acquisition time and the operation item to determine the time sequence matching degree between the two. The initial weights of the compensation function at the corresponding time point are adjusted based on the time-series matching degree. Obtain the associated weights of the scene at the corresponding time for the compensation function, the first code, and the second code from the scene-weight lookup table, and combine them with the adjusted initial weights to obtain the updated weights for the compensation function, the first code, and the second code, respectively. The parameter features of the first code, the operation item state features of the second code, and the correction features of the compensation function are mapped hierarchically. The basic feature layer is constructed with the element with the highest update weight as the core, and the remaining elements are embedded into the associated nodes of the basic feature layer according to their update weights to generate a preliminary set of influence factors.

7. The management method for full-process IoT information control of smart cash registers according to claim 1, characterized in that, Real-time synchronization to the consortium blockchain network for distributed verification, including: The consortium blockchain network nodes are divided into a core verification layer, a secondary verification layer, and an audit verification layer. Differentiated verification permissions and data visibility ranges are preset for each layer of nodes. The core verification layer performs basic verifications on data encryption integrity, dynamic hardware identifier validity, and node identity and authorization legality, and generates basic verification credentials that are synchronized to the corresponding secondary verification layer group. The secondary verification layer is based on the basic verification credentials and cross-verifies the consistency of the data with the historical chain data and the rationality of the operation sequence. The group leader node summarizes the verification results within the group to form a secondary verification report. The audit verification layer conducts sampling reviews of the verification process for high-security-level data, while low / medium-security-level data is only reviewed when an anomaly warning is triggered.

8. The management method for full-process IoT information control of smart cash registers according to claim 1, characterized in that, Automatically generate new unique hardware identifiers for updates, including: After the update is triggered, the original root key and historical update log of the current hardware identifier are automatically retrieved based on the national cryptographic chip. A temporary encryption seed is generated based on the original root key, and hash fragments of the last n0 on-chain data are extracted as auxiliary factors. The security enhancement function is determined by combining the temporary encryption seed and auxiliary factors. This is then combined with the current state parameters of the cash box and an intermediate identifier generated using the national cryptographic algorithm. This intermediate identifier is then encrypted again using a unique verification code pre-allocated by the core verification layer node to form a new unique hardware identifier. This new identifier includes a historical identifier traceability field and an update trigger reason flag. The security enhancement function is as follows: Where N0 is the number of auxiliary factors; The security increment coefficient between the s0th auxiliary factor and the temporary encryption seed; The mutual exclusion angle between the s0th auxiliary factor and the temporary encryption seed The value; This is a secure increment function based on the temporary encryption seed and all auxiliary factors.

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