Iot-based two-dimensional code device adaptive control method, system, device and medium

Abstract

The application discloses a two-dimensional code equipment adaptive control method and system based on the Internet of Things, equipment and medium, relates to the technical field of two-dimensional code monitoring, and comprises a method based on cumulative contribution equal division, determines the overlap proportion of a two-dimensional code and an adjacent two-dimensional code on a device state time axis, forms a first shared proportion array, and converts the first shared proportion array into a device state time period, generates a plurality of second shared proportion arrays through continuous displacement disturbance; a corresponding relationship between the shared proportion and a state sampling starting offset and a coverage span is established, the second shared proportion array is mapped to adaptive control object control two-dimensional code monitoring; based on the monitoring results under different shared proportion arrays, the training adaptive control reward points are updated cumulatively through state feedback, the second shared proportion array is compressed into an overall shared representation value, and the best scheme is screened in combination with the reward points, so that the problems of insufficient two-dimensional code monitoring accuracy and continuity caused by state fragmentation or abnormal dilution in the prior art are solved.

Description

Technical Field

[0001] This invention relates to the field of QR code monitoring technology, and more specifically, to an adaptive control method, system, device, and medium for QR code devices based on the Internet of Things. Background Technology

[0002] In manufacturing and logistics processes, IoT-based QR code-based equipment monitoring technology is widely used for work-in-process tracking, process quality traceability, and equipment operating status correlation analysis. In existing technologies, a product's QR code is typically read when it enters or leaves a processing step, and the scanning time is used as a process boundary marker to extract the corresponding time interval of equipment operating status from continuously collected IoT status data from the equipment side. This equipment operating status usually originates from sensor nodes deployed on the processing equipment, collecting data including equipment operating parameters such as current, speed, vibration, and power fluctuations, which are cached and stored chronologically to achieve the binding of the QR code to the equipment status interval.

[0003] In real-world continuous processing or assembly line operations, adjacent QR code-scanned products are often processed consecutively on the same equipment, resulting in a natural continuity and even partial overlap in their corresponding equipment status time intervals on the timeline. Therefore, in IoT-based QR code device monitoring, the question inevitably arises regarding whether and to what extent the same segment of equipment status data is shared by adjacent QR code products—that is, the issue of the sharing ratio of adjacent QR code-scanning product equipment status. This sharing ratio directly determines whether a segment of equipment status is strictly assigned to a single QR code on the timeline, or whether it is allowed to be partially or entirely shared among multiple adjacent QR codes. This is a key technical aspect of the QR code status attribution mechanism.

[0004] The degree of status sharing between adjacent QR code scanning devices has a direct and significant impact on the monitoring results of IoT-based QR code devices. The sharing ratio not only affects the time span of device status reflected by a single QR code, but also the continuity, consistency, and distinguishability of status information between adjacent QR codes. An unreasonable sharing ratio can easily lead to conflicts between device status continuity and QR code product granularity, thereby weakening the technical value of QR codes in status monitoring, anomaly tracing, and quality analysis.

[0005] When the sharing rate of device status between adjacent QR codes is low, existing technologies typically employ a strict state segmentation method based on scanning time, ensuring that each QR code is associated with device status data only within a very short timeframe. In continuous processing scenarios, this approach easily leads to fragmentation of device status at the QR code level. Changes in upstream device status cannot be consistently reflected in downstream QR codes, resulting in drastic jumps in state differences between adjacent QR codes. This not only increases the apparent frequency of state fluctuations but also easily leads to misjudgments of device operational stability and makes it difficult to effectively trace abnormal device evolution processes through QR code sequences.

[0006] When the sharing ratio of device status between adjacent QR code scanning products is high, the same segment of device status data will be widely distributed across multiple QR code products, significantly extending the time window for the device status corresponding to a single QR code. In this situation, critical status information such as short-term device anomalies and local fluctuations can easily be masked by a large number of normal statuses, causing the status reflected by the QR codes to tend to be averaged and historical. At the same time, a high sharing ratio can also blur the correspondence between device anomalies and specific scanning nodes, making responsibility identification and process-level status analysis difficult, and reducing the real-time performance and accuracy of QR code status monitoring.

[0007] Existing adaptive control technologies for QR code devices based on the Internet of Things (IoT) rely heavily on fixed rules or empirical time window divisions to set and regulate the sharing ratio of adjacent scanned product devices. They lack the technical means to systematically model, dynamically adjust, and optimize the sharing ratio. This lack of fine-grained control over state attribution makes it difficult for QR code state monitoring to simultaneously consider both device state continuity and QR code product distinguishability in continuous processing scenarios. This leads to problems such as state fragmentation, anomaly dilution, and ambiguous responsibility, limiting the effectiveness of QR codes in IoT device state monitoring.

[0008] To address the above problems, this invention proposes a solution. Summary of the Invention

[0009] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide an adaptive control method, system, device, and medium for QR code devices based on the Internet of Things. By constructing multiple candidate arrays of the shared state ratio of QR code product devices and combining them with adaptive control reward scores to select the optimal solution, the present invention addresses the problem of insufficient accuracy and continuity of QR code monitoring caused by state fragmentation or abnormal dilution in existing methods.

[0010] To achieve the above objectives, the present invention provides the following technical solution:

[0011] An adaptive control method for QR code devices based on the Internet of Things includes the following steps: First, based on the cumulative contribution, the overlap ratio between each QR code and its adjacent QR codes on the device state time axis is determined to obtain the shared state ratio of adjacent scanning products, which is then summarized to form a first shared ratio array. Second, the first shared ratio array is converted into the start and end positions of the device state time period corresponding to each QR code, and the start and end positions are continuously perturbed to generate multiple sets of corresponding device state time periods. This is then reversed to obtain several sets of second shared ratio arrays. Third, a correspondence is established between the shared ratio and the state sampling start offset and the state sampling coverage span, realizing the conversion of the shared ratio array into an adaptive control object. Fourth, each second shared ratio array is converted into a corresponding adaptive control object and used to control QR code monitoring. Fifth, based on the monitoring results under different second shared ratio arrays, the corresponding adaptive control reward score is trained using the state feedback cumulative update process. Sixth, the second shared ratio array is compressed into an overall shared representation value, and the optimal second shared ratio array is selected based on the adaptive control reward score, and then used to control the QR code product state monitoring.

[0012] The IoT-based adaptive control system for QR code devices includes a shared ratio generation module, a shared ratio disturbance generation module, a shared ratio control mapping module, a multi-ratio state control module, an adaptive control reward training module, and an adaptive control module. The shared ratio generation module determines the overlap ratio between each QR code and its adjacent QR codes on the device state time axis based on cumulative contribution, obtaining the shared ratio of adjacent scanning products' device states, and summarizing them to form a first shared ratio array. The shared ratio disturbance generation module converts the first shared ratio array into the start and end positions of the device state time period corresponding to each QR code, and continuously disturbs the start and end positions to generate multiple sets of corresponding device state time periods, which are then converted in reverse to obtain several sets of second shared ratios. The system comprises the following modules: a shared ratio array; a shared ratio control mapping module, used to establish the correspondence between the shared ratio and the state sampling start offset and state sampling coverage span, realizing the conversion of the shared ratio array into an adaptive control object; a multi-ratio state control module, used to convert each second shared ratio array into a corresponding adaptive control object and control the QR code monitoring respectively; an adaptive control reward training module, used to train the corresponding adaptive control reward score based on the monitoring results under different second shared ratio array controls, combined with the state feedback cumulative update process; and an adaptive control module, used to compress the second shared ratio array into an overall shared representation value, combine the adaptive control reward score to select the best second shared ratio array, and control the QR code product status monitoring.

[0013] An electronic device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to execute an Internet of Things-based QR code device adaptive control method.

[0014] A computer-readable storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements an adaptive control method for QR code devices based on the Internet of Things.

[0015] The technical effects and advantages of the adaptive control method, system, device, and medium for QR code devices based on the Internet of Things in this invention are as follows:

[0016] 1. This invention achieves a balance between continuity and distinguishability of device status in QR code product status monitoring by modeling the sharing ratio of adjacent QR code scanning device statuses and generating multiple candidate sharing ratio arrays. This technology can equally divide the QR code status assignment interval based on cumulative contribution and generate multiple candidate sharing ratios through continuous displacement perturbation, thus effectively avoiding the status fragmentation problem caused by low sharing ratios in traditional methods. Simultaneously, it improves the sensitivity and real-time response capability of QR codes to device anomalies and status changes in continuous processing scenarios. Therefore, QR code product status monitoring can not only reflect the precise status of each process but also maintain reasonable status continuity between adjacent QR codes, achieving high-precision, multi-process, and continuous status tracking.

[0017] 2. This invention establishes a correspondence between the sharing ratio, the initial offset of state sampling, and the coverage span, and uses adaptive control reward scores accumulated based on state feedback to achieve the selection and application of the optimal second sharing ratio array. This technology can compress multiple sets of sharing ratio information into an overall sharing representation value, and evaluate the monitoring effect based on the adaptive control reward score. This ensures that the final applied sharing ratio avoids both excessively high ratios leading to abnormal dilution and excessively low ratios causing state jumps, thereby significantly enhancing the accuracy, stability, and traceability of QR code status monitoring. Therefore, IoT-based adaptive control of QR code devices can achieve more reliable status identification, anomaly warning, and process quality traceability functions in complex scenarios such as continuous processing and multi-product shared equipment. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating the adaptive control method for QR code devices based on the Internet of Things according to the present invention.

[0019] Figure 2 This is a schematic diagram of the adaptive control system for QR code devices based on the Internet of Things (IoT) of the present invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0021] Example 1, Figure 1 The present invention provides an adaptive control method for QR code devices based on the Internet of Things, comprising the following steps:

[0022] S1. Based on the cumulative contribution, the overlap ratio of each QR code and the adjacent QR code on the device status time axis is determined to obtain the device status sharing ratio of adjacent scanning products, and the sum is used to form the first sharing ratio array.

[0023] In this embodiment, the overlap ratio between each QR code and its adjacent QR codes on the device status time axis is determined based on cumulative contribution, resulting in the device status sharing ratio of adjacent scanning products. This ratio is then summarized to form a first sharing ratio array, specifically:

[0024] Collect the QR code scanning time series of the product in the Internet of Things environment, as well as the device status sampling time series of the corresponding scanning node, and arrange the device status sampling points in chronological order;

[0025] Using the time between two adjacent QR code scans as the time boundary, the device status sampling points in between are divided into a continuous status sampling interval;

[0026] For the device state sampling points within the state sampling interval, the corresponding state change amplitudes are accumulated in chronological order to obtain the cumulative state change sequence within the interval.

[0027] The final cumulative value of the state change accumulation sequence is taken as the total state change contribution for the scanning time interval, and the total state change contribution is divided into several continuous contribution segments in an equal division manner.

[0028] Using the corresponding QR code scanning time as a reference point, the boundary positions of adjacent contribution segments are located along the cumulative sequence of state changes forward and backward, respectively, to determine the forward and backward boundaries of the QR code on the device state time axis.

[0029] The device status time interval between the forward boundary and the backward boundary is taken as the device status belonging interval of the QR code;

[0030] Align the device status affiliation intervals of adjacent QR codes with the time axis, calculate the time length of overlap between the affiliation intervals, and determine the sharing ratio of device status of adjacent scanning products by the ratio of the overlap time length to the time length of the corresponding QR code affiliation interval.

[0031] Repeat the steps of determining the sharing ratio of adjacent scanning product device status for all QR codes, and summarize the sharing ratio of adjacent scanning product device status for each QR code to form the first sharing ratio array.

[0032] In the QR code scanning time sequence of this embodiment, it refers to the time stamp sequence formed by reading the QR code of the product through the scanning device each time the product passes through the corresponding process node in the Internet of Things production environment. The timestamp is only used to identify the time position of the product entering or leaving a certain equipment process node, and does not contain any product quality or processing parameter information. Its function is to provide an anchor point for the time attribution of subsequent equipment status data.

[0033] In the device status sampling time series of this embodiment, it refers to the timestamp sequence corresponding to the device operating status data continuously collected by IoT sensor nodes at a fixed or quasi-fixed sampling period on the corresponding processing equipment. This time series reflects the continuous operating status of the device on the time axis, rather than the exclusive status of a specific QR code product.

[0034] In this embodiment, the state sampling interval refers to a continuous time segment extracted from the device state time axis using the time boundaries of two adjacent QR code scanning times. The device state sampling points within this segment are continuously distributed in time, reflecting the overall operation process of the device between two scanning events. This interval does not presuppose that it belongs entirely to a certain QR code product.

[0035] In this embodiment, the state change amplitude refers to the degree of change between two adjacent device state sampling points in the same or multiple state dimensions. This change is used to characterize the fluctuation strength of the device operating state during the time process. Its value reflects the drastic degree of change in the device state, rather than the absolute size of the state itself.

[0036] In this embodiment, the cumulative sequence of state changes refers to an ordered sequence formed by accumulating the state change amplitudes corresponding to each device state sampling point within the state sampling interval in chronological order. This sequence progresses monotonically on the time axis, and its final cumulative result reflects the overall intensity distribution of device state changes within the scanning time interval.

[0037] In this embodiment, the total state change contribution refers to the cumulative result corresponding to the end of the state change cumulative sequence at the end of the state sampling interval. This result is used to characterize the overall change contribution of the equipment operating state to the entire production process between two adjacent scanning times. This contribution value is used for subsequent equal division processing and does not directly participate in the product state evaluation.

[0038] In the equal division method of this embodiment, the total state change contribution is divided into several continuous segments with the same contribution amount according to the distribution order of the change contribution on the time axis. This equal division is not based on the time length, but on the proportion of the state change contribution in the cumulative sequence, so as to ensure that each contribution segment has equivalent significance in terms of the intensity of the equipment state change.

[0039] In this embodiment, the continuous contribution segment refers to the time interval between two adjacent equally divided boundary points in the cumulative sequence of state changes. Each continuous contribution segment corresponds to a part of the contribution of device state changes and is continuously distributed on the time axis, serving as a reference unit for subsequently determining the boundary of QR code state attribution.

[0040] In this embodiment, the forward boundary and the backward boundary refer to the time points corresponding to the boundary positions of adjacent continuous contribution segments, respectively, in the cumulative sequence of state changes, with a certain QR code scanning time as a reference point, and located in the forward and backward directions of the time axis. These two time points together define the state belonging range of the QR code on the device state time axis.

[0041] In this embodiment, the device status attribution interval refers to the device status time segment defined by the forward boundary and the backward boundary. This segment indicates that, under the current sharing strategy, the device operating status within this time range is considered to primarily serve the product with the corresponding QR code identifier. This attribution does not preclude the status within this segment from being partially shared by adjacent QR codes.

[0042] In the timeline alignment of this embodiment, it means mapping the device status belonging intervals corresponding to two adjacent QR codes onto a unified device status timeline, using time position as the unique alignment benchmark, so as to directly identify whether the two belonging intervals overlap on the timeline and the specific range of the overlap.

[0043] In this embodiment, the overlap time length refers to the length of time range that the device status belonging intervals of two adjacent QR codes simultaneously cover on the time axis after the time axis is aligned. This length reflects the degree to which the same device operating status is referenced by multiple QR codes at the same time.

[0044] In this embodiment, the sharing ratio of adjacent scanning product device status refers to the ratio between the overlap time length and the corresponding QR code device status belonging interval time length. This ratio is used to quantify the proportion of the current QR code device status that is shared with adjacent QR codes. The denominator is the belonging interval length of the current QR code itself, so as to ensure that the sharing ratio reflects the "degree of status sharing from the perspective of the current QR code".

[0045] In this embodiment, the first sharing ratio array refers to an ordered array formed by summarizing the sharing ratios of the device status of all adjacent QR codes according to the QR code scanning time. This array reflects the distribution of the degree of device status sharing among different QR codes in the continuous production process, providing an initial reference basis for subsequent sharing ratio disturbance and optimization.

[0046] It should be noted that in this embodiment, the IoT-based QR code device adaptive control does not directly collect or record the physical attributes or quality parameters of the product itself. Instead, it uses the QR code as a time anchor to perform time slicing and classification of the continuously collected device operating status, thereby indirectly constructing the association between the QR code and the device status.

[0047] It should be noted that since device status sampling is continuous on the time axis, while QR code scanning events occur discretely on the time axis, the same device status may naturally cover the processing of multiple QR codes simultaneously. This embodiment introduces an equal-division mechanism based on the contribution of status changes, so that the attribution of device status no longer depends solely on the length of time, but is dynamically adjusted in combination with the intensity of device status changes, thereby laying the foundation for subsequent sharing ratio adjustment, reward evaluation, and selection of the optimal sharing strategy.

[0048] S2, convert the first shared ratio array into the start and end positions of the device status time period corresponding to each QR code, and continuously shift and disturb the start and end positions to generate multiple sets of corresponding device status time periods, and reverse the conversion to obtain several sets of second shared ratio arrays.

[0049] In this embodiment, the process of converting the first shared ratio array into the start and end positions of the device status time period corresponding to each QR code, and continuously displacing and perturbing the start and end positions to generate multiple sets of corresponding device status time periods, and then reversing the conversion to obtain several sets of second shared ratio arrays, specifically involves:

[0050] Read the shared ratio of adjacent scanning product device status corresponding to each QR code in the first shared ratio array, and simultaneously read the device status belonging range of the QR code.

[0051] Each device status interval is represented as a device status time period defined by a start time point and an end time point, and the position of this time period on the device status time axis is recorded.

[0052] Based on the overlap between the device status time period and the adjacent QR code device status time periods, determine the overlap time length and the exclusive time length corresponding to the current time period;

[0053] Using the start and end times of the equipment state time period as displacement references, the equipment state time period is continuously displaced synchronously or in reverse along the equipment state time axis to generate multiple sets of candidate equipment state time periods that have undergone different degrees of expansion or translation.

[0054] For each group of candidate device status time periods, keep the adjacent QR code device status time periods unchanged, and redetermine their corresponding overlapping time length and exclusive time length.

[0055] Based on the ratio between the overlap length of the candidate device status time period and its own time length, the corresponding candidate adjacent scanning product device status sharing ratio is obtained;

[0056] The sharing ratios corresponding to the time periods of candidate device status around the same QR code are summarized to form multiple sets of second sharing ratio arrays that correspond one-to-one with the first sharing ratio array.

[0057] In this embodiment, the first sharing ratio array refers to the ordered array formed by determining the sharing ratio of adjacent scanning product equipment status for each QR code in step S1 based on the overlap of adjacent QR code device status affiliation intervals on the time axis. This array is arranged in the order of QR code scanning time and is used to characterize the initial equipment status sharing level corresponding to each QR code in the continuous production process.

[0058] In this embodiment, the device state attribution interval refers to the time segment determined for each QR code on the device state time axis in step S1 based on the state change contribution equalization mechanism. This segment represents the range of device operating states that are considered to mainly belong to the QR code under the current sharing ratio.

[0059] In this embodiment, the device state time period refers to the time period description formed by expressing the device state belonging interval with a clear start time point and end time point. This time period has a definite position and length on the device state time axis and is the basic object for subsequent time displacement and scaling operations.

[0060] In this embodiment, the overlap time length refers to the time range during which the device status time period corresponding to the current QR code and the device status time period of the adjacent QR code are simultaneously covered on the device status time axis. This time range reflects the degree to which the same device operating status is referenced by multiple QR codes at the same time.

[0061] In this embodiment, the dedicated time length refers to the time length of the portion of the device state time period corresponding to the current QR code that does not overlap with the time period of the adjacent QR code device state. This time length is used to characterize the proportion of device states that only serve the current QR code.

[0062] In this embodiment, the displacement reference refers to the time anchor point used as the reference point for time adjustment when changing the position or span of the time period on the equipment state time axis, with the start and end times of the equipment state time period as reference points.

[0063] In this embodiment, continuous displacement refers to the process of gradually adjusting the start and end times of the equipment state time period along the equipment state time axis. This adjustment can be manifested as a translation of the entire time period on the time axis, or a gradual expansion or contraction of the time period length, and the adjustment range changes continuously on the time axis rather than discretely jumping.

[0064] In the synchronous displacement of this embodiment, it means that when performing continuous displacement, the start time point and the end time point of the equipment state time period move in the same direction and with the same time offset, so as to keep the length of the time period unchanged and only change its position on the equipment state time axis.

[0065] In the reverse displacement of this embodiment, it means that during continuous displacement, the start and end times of the device state time period move in opposite directions, thereby causing the coverage span of the device state time period on the time axis to expand or contract, which is used to adjust the size of the shared range of device states.

[0066] In this embodiment, the candidate device state time period refers to multiple new time periods generated by synchronously shifting or reversing the start and end times of the current QR code device state time period to different degrees, while keeping the adjacent QR code device state time periods unchanged. These time periods correspond to different device state sharing conditions.

[0067] In this embodiment, the sharing ratio of candidate adjacent scanning product device status refers to the degree of sharing obtained by re-identifying the overlap between each candidate device status time period and the adjacent QR code device status time period on the time axis, and using the ratio of the overlap time length to the length of the candidate device status time period itself.

[0068] In this embodiment, the second sharing ratio array refers to the array set formed by summarizing the sharing ratio of candidate adjacent scanning product device status obtained by each QR code under different candidate device status time periods around the same group of QR codes. Each array in this array set is structurally one-to-one with the first sharing ratio array, but numerically reflects the status sharing distribution under different sharing strategies.

[0069] It should be noted that in this embodiment, by continuously shifting and perturbing the start and end positions of the device state time period, rather than directly modifying the shared ratio value, the change in the shared ratio always originates from the actual time relationship change on the device state time axis, thereby ensuring that the subsequently generated second shared ratio array has a clear physical time meaning and is feasible.

[0070] It should be noted that this step fixes the device state time periods of adjacent QR codes and only performs displacement and scaling processing on the device state time period of the current QR code. This allows the differences between different second sharing ratio arrays to be clearly attributed to the adjustment of the sharing strategy, rather than changes in the device state itself. This provides a comparable basis for subsequent adaptive control reward score training and optimal sharing ratio selection.

[0071] S3, establish the correspondence between the shared ratio and the state sampling start offset and the state sampling coverage span, and realize the conversion of the shared ratio array into an adaptive control object;

[0072] In this embodiment, establishing the correspondence between the shared ratio and the state sampling start offset and the state sampling coverage span, thereby realizing the conversion of the shared ratio array into an adaptive control object, specifically involves:

[0073] For each group of second shared ratio arrays, read its corresponding candidate device status time period and obtain the start and end time points of the time period on the device status time axis.

[0074] Using the scanning trigger time of the corresponding QR code as a time reference point, the starting offset of the state sampling after scanning is determined based on the positional relationship between the starting time point of the candidate device state time period and the scanning trigger time on the time axis.

[0075] Based on the interval range between the start and end times of the candidate device status time period on the time axis, determine the coverage span of status sampling after the scan is triggered;

[0076] By jointly setting the starting offset of state sampling and the coverage span of state sampling, the state sampling time period after the scanning is triggered forms a time overlap relationship with the state time period corresponding to the adjacent QR code on the device state time axis, which is consistent with the second shared ratio array.

[0077] The state sampling start offset and state sampling coverage span corresponding to each QR code are combined to form an adaptive control object set that corresponds one-to-one with the second shared ratio array.

[0078] Based on the set of adaptive control objects, the reverse conversion from the second shared ratio array to the starting offset of the scanning trigger state sampling and the state sampling coverage span is realized.

[0079] In the second sharing ratio array of this embodiment, it refers to the multiple sets of adjacent scanning product device status sharing ratio arrays obtained by reverse derivation from the candidate device status time period in step S2. Each set of arrays corresponds to a specific device status time period configuration scheme, which is used to represent the distribution of the degree of status sharing between each QR code under different sharing strategies.

[0080] In this embodiment, the candidate device state time period refers to the device state time interval determined for each QR code for each group of second shared ratio arrays, which has a clear start time point and end time point. This time interval has a definite position on the device state time axis and is used to carry subsequent state sampling operations.

[0081] In this embodiment, the device status timeline refers to a unified time series axis formed by the continuous collection of device operating status by IoT sensors on the device side according to a fixed sampling period. This timeline serves as a common time reference basis for all QR code status sampling behaviors.

[0082] In this embodiment, the scanning trigger time refers to the time point when the QR code product enters the target process and the scanning device reads the QR code and records it. This time point is used to identify the sampling reference time of the QR code status in the current process, rather than the actual collection time of the device status.

[0083] In this embodiment, the time reference point refers to the scanning trigger moment as the time zero point or reference point, which is used to describe the relationship between the candidate device state time period and the QR code trigger event on the device state time axis, thereby realizing the mapping of the device state time period to the scanning trigger sampling control parameters.

[0084] In this embodiment, the state sampling start offset refers to the time offset from the moment the QR code scanning is triggered, moving forward or backward along the device state time axis to the starting time point of the candidate device state time period. This offset is used to control the start time of the state sampling behavior after the QR code scanning is triggered.

[0085] In this embodiment, the state sampling coverage span refers to the time range that extends backward along the device state time axis from the actual start time of state sampling to the end time of the candidate device state time period. This span is used to limit the length of the device state time covered in one state sampling process.

[0086] In this embodiment, the state sampling time period refers to the time interval during which device state sampling is actually performed, which is defined by the state sampling start offset and the state sampling coverage span after the QR code scanning is triggered. The position of this time interval on the device state time axis is consistent with the candidate device state time period.

[0087] In the consistent time overlap relationship of this embodiment, it means that by setting the state sampling start offset and the state sampling coverage span, the overlap between the actual state sampling time period after the QR code is triggered and the state sampling time period corresponding to the adjacent QR code is maintained on the device state time axis, and the shared ratio distribution described by the second shared ratio array is maintained.

[0088] In the adaptive control object of this embodiment, it refers to the parameter pair consisting of the state sampling start offset and the state sampling coverage span. This parameter pair is directly used to control the device state sampling behavior after the QR code is triggered, and belongs to the set of control parameters that can be directly executed by the system.

[0089] In this embodiment, the set of adaptive control objects refers to the set of parameters formed by combining the starting offset of state sampling and the coverage span of state sampling of all QR codes around the same set of second shared ratio arrays. Each set of parameters in this set corresponds one-to-one with a specific QR code.

[0090] In the reverse conversion of this embodiment, it means starting from the candidate device state time period corresponding to the second shared ratio array, deriving the state sampling start offset and state sampling coverage span through the time axis position relationship, so that the abstract shared ratio description is transformed into specific control parameters that can be directly applied to state sampling control.

[0091] It should be noted that in this embodiment, the sharing ratio is not directly used as a control command. Instead, the sharing ratio constraint is transformed into the control of the start time and duration of state sampling after the scanning is triggered through the intermediate time representation of the candidate device state time period. This ensures that the adjustment of the sharing ratio can be accurately executed during the actual device state sampling process.

[0092] It should be noted that this step establishes a clear correspondence between the sharing ratio and the adaptive control object, so that each set of second sharing ratio arrays can be completely mapped to a set of executable state sampling parameters, providing a unified control basis for subsequent QR code device status monitoring, adaptive control reward score training, and optimal sharing ratio selection under different sharing strategies.

[0093] S4, convert each of the second shared ratio arrays into corresponding adaptive control objects and control the QR code monitoring respectively;

[0094] In this embodiment, the step of converting each second shared ratio array into a corresponding adaptive control object and controlling the QR code monitoring respectively involves:

[0095] For each set of second shared ratio arrays, read the state sampling start offset and state sampling coverage span that correspond one-to-one with the second shared ratio array;

[0096] When a QR code product enters the target process and triggers a scanning operation, the corresponding scanning trigger timestamp is recorded, and this timestamp is used as the sampling reference time of the QR code in the current process.

[0097] Based on the state sampling start offset, the actual start time point of state sampling is determined along the device state time axis after the scanning trigger timestamp;

[0098] Based on the state sampling coverage span, the actual end time of state sampling is determined along the equipment state time axis after the actual start time point, thereby forming the equipment state sampling time period of the QR code in the current process;

[0099] In the IoT device status time-series data continuously collected on the device side, the corresponding device status data subsequence is extracted based on the time interval defined by the actual start time point and the actual end time point.

[0100] The device status data subsequence is bound to the QR code that triggered the sampling process to form the QR code device status monitoring result under the second shared ratio array condition;

[0101] The above process is performed on the state sampling start offset and state sampling coverage span corresponding to all second sharing ratio arrays to obtain multiple sets of QR code device status monitoring results under different sharing ratio conditions.

[0102] It should be noted that in this embodiment, the status monitoring of QR code products on the production equipment is not based on fixed time window sampling, but rather on an adaptive sampling process based on the dynamic mapping relationship between QR code scanning behavior and the equipment status time axis. The scanning times of different QR codes in the same process are not entirely consistent, and the equipment status changes continuously over time. Therefore, by introducing a status sampling start offset and a status sampling coverage span, the abstract evaluation result of the sharing ratio is transformed into a specific adaptive control object that can directly affect the equipment status sampling, thereby enabling a comparable analysis of the QR code equipment status monitoring effects under different sharing ratio conditions.

[0103] It should be noted that this embodiment generates multiple sets of second shared ratio arrays by perturbing the shared ratio array. The purpose is not to randomly adjust the sampling parameters, but to systematically traverse the device state sampling intervals under different shared ratio conditions so that the QR code monitoring results can cover different degrees of overlapping device states. This provides a stable and reproducible sample basis for subsequent adaptive control reward score updates and optimal shared ratio selection based on state feedback.

[0104] In the second sharing ratio array of this embodiment, the second sharing ratio array is a set of candidate sharing ratios obtained by continuously shifting and perturbing the first sharing ratio array. Each set of second sharing ratio arrays represents the distribution of the degree of device status sharing between different QR codes and their adjacent QR codes on the device status time axis. This degree of sharing reflects the overlap relationship of QR codes in the device status sampling time period and is used to characterize the difference in the sharing intensity of device status information by different QR codes within the same device operating cycle.

[0105] In this embodiment, the adaptive control object is a set of executable sampling parameters obtained by reverse mapping of the second shared ratio array. Essentially, it converts the evaluation result of the shared ratio into an actual control quantity at the device state sampling level. This adaptive control object includes at least a state sampling start offset and a state sampling coverage span, used to clarify the specific position and duration of the QR code device state sampling on the time axis, enabling the shared ratio to directly affect monitoring behavior rather than remaining at the evaluation level.

[0106] In this embodiment, the state sampling start offset refers to the amount of time that is shifted backward on the device state timeline relative to the QR code scanning trigger timestamp, used to determine the actual starting position of device state sampling. This offset is not a fixed value, but is adjusted according to the sharing ratio, so that when the sharing ratio is high, the sampling start positions of multiple QR codes are closer on the timeline, thereby forming a shared sampling interval for the device state.

[0107] In this embodiment, the state sampling coverage span refers to the length of time during which state data is continuously collected on the device state timeline, starting from the actual start time of state sampling. This coverage span controls the width of the device state sampling time period, and its size corresponds to the sharing ratio, so that changes in the coverage span can reflect the differences in the time range of shared device state information between QR codes.

[0108] In this embodiment, the scan trigger timestamp refers to the time stamp recorded when the QR code product enters the target process and completes the scan operation. This timestamp serves as a reference time base for the QR code in the current process. By using the scan trigger timestamp as a unified reference point, it can be ensured that the state sampling of different QR codes under different sharing ratios is based on the same timing alignment logic, avoiding monitoring offset caused by differences in process entry time.

[0109] In this embodiment, the sampling reference time is the scanning trigger timestamp corresponding to the QR code, which serves as the time base for calculating the starting time point of subsequent state sampling. By combining the sampling reference time with the state sampling start offset, the state sampling window of each QR code can be accurately located on the device state timeline.

[0110] In this embodiment, the actual starting time point refers to the specific sampling start position determined along the device state time axis based on the state sampling start offset after the scanning trigger timestamp. This time point marks the starting point for extracting the device state data subsequence, and its position changes with the adaptive control object corresponding to the second shared ratio array, thereby enabling the differentiation of sampling strategies under different shared ratio conditions.

[0111] In this embodiment, the actual end time point refers to the equipment status sampling termination position determined based on the status sampling coverage span after the actual start time point. The actual end time point and the actual start time point together define the equipment status sampling time period of the QR code in the current process, which is used to extract the corresponding status data subsequence from the continuous equipment status time sequence data.

[0112] In this embodiment, the device status sampling time period is a continuous time interval defined by the actual start time and the actual end time on the device status time axis. This time period is used to clarify the range of device operating status that can be observed under the current sharing ratio, and is a direct reflection of the effect of the sharing ratio on the actual monitoring process.

[0113] In this embodiment, the device status data subsequence refers to a set of local status data extracted from the continuous time-series data of IoT device status collected from the device side, based on the device status sampling time period. This subsequence contains the device operating status information that the QR code can perceive under the corresponding sharing ratio, and is the basic data for subsequent monitoring result analysis and reward score updates.

[0114] In the QR code device status monitoring results of this embodiment, the QR code device status monitoring results are data objects formed by binding a subsequence of device status data with the QR code that triggered the sampling process. These objects characterize the device status observation results corresponding to the QR code under a specific second sharing ratio array condition. Different second sharing ratio arrays will form multiple sets of monitoring results to reflect the impact of changes in the sharing ratio on the QR code device status monitoring effect.

[0115] S5, based on the monitoring results under different second shared ratio array control, combined with the state feedback cumulative update process, train the corresponding adaptive control reward score;

[0116] In this embodiment, the process of training the corresponding adaptive control reward score based on the monitoring results under different second shared ratio array control and the state feedback cumulative update process is specifically as follows:

[0117] For each group of second shared ratio arrays, read the QR code device status sampling results formed during the QR code monitoring process, and arrange them according to the QR code scanning time order to obtain the QR code sequence corresponding to the second shared ratio array;

[0118] Along the QR code sequence, select two adjacent QR codes in sequence, read the corresponding device status sampling time periods, and determine the overlapping time interval of the two on the device status time axis.

[0119] Within the overlapping time interval, a state difference sequence is formed for each of the device state sampling points of adjacent QR codes at the same time position, and the number of sampling points with a state difference greater than a preset state difference threshold is counted as the first feature value of the adjacent QR code pair.

[0120] For the non-overlapping portion of the device status sampling time period of adjacent QR codes, determine the maximum and minimum state values ​​of their respective device status sampling points, and use the overlap length of their value intervals as the second feature value of the adjacent QR code pair.

[0121] The first feature value is normalized according to a preset upper limit value to obtain a first normalized feature value whose value range is limited to (0,1);

[0122] The second feature value is normalized and mapped according to the preset state interval width to obtain a second normalized feature value whose value range is limited to (0,1);

[0123] According to the preset weights, the first normalized feature value and the second normalized feature value are linearly merged to obtain the shared deduction value corresponding to the adjacent QR code pair.

[0124] Along the QR code sequence, the shared deduction values ​​of all adjacent QR code pairs are accumulated and summarized to obtain the total deduction amount corresponding to the second shared ratio array;

[0125] Using a preset benchmark reward value as the initial value, the corresponding total deduction is subtracted from the benchmark reward value to output a single continuous scalar, which serves as the adaptive control reward score corresponding to the second shared ratio array.

[0126] In the QR code device status sampling results of this embodiment, the QR code device status sampling results refer to the set of device status data collected for each QR code within a device status sampling time period defined by the status sampling start offset and the status sampling coverage span under a certain second sharing ratio array condition. This sampling result not only includes the time series information of the device status but also implicitly contains the influence of the sharing ratio on the sampling time position and coverage range.

[0127] In the QR code sequence of this embodiment, the QR code sequence is an ordered set formed by sorting multiple QR codes under the same second shared ratio array condition according to their scanning trigger timestamps from earliest to latest. This sorting method ensures that subsequent state difference analysis always unfolds in the natural order of device operation time, making the comparison between adjacent QR codes have clear temporal semantics, rather than random pairing.

[0128] In this embodiment, adjacent QR code pairs refer to two QR codes that are temporally adjacent in the QR code sequence, and whose corresponding device status sampling time periods have potential overlap or adjacency on the device status time axis. By analyzing only adjacent QR codes, the problem of incomparable device status caused by excessively long time intervals can be avoided.

[0129] In this embodiment, the device status sampling time period is the device status observation interval corresponding to each QR code under the current sharing ratio, defined by its actual start time and actual end time. This time period determines the range of device operating states that the QR code can perceive, and is the basis for judging the state sharing and differences between different QR codes.

[0130] In this embodiment, the overlapping time interval refers to the time interval during which the device status sampling periods of two adjacent QR codes simultaneously cover each other on the device status time axis. This interval is used to characterize whether there are significant differences in the device status observed by the two QR codes at the same time position, and is an important basis for sharing consistency evaluation.

[0131] In the state difference sequence of this embodiment, the state difference sequence refers to the difference sequence formed by comparing the device state sampling points of adjacent QR codes at the same time position within the overlapping time interval. Each state difference reflects the degree of deviation between the state perception results corresponding to different QR codes at the same device operating time.

[0132] In this embodiment, the preset state difference threshold is a criterion used to distinguish between normal state fluctuations and abnormal state deviations. Its value is preset according to the normal range of device state changes. When the state difference exceeds the threshold, it indicates that there is a significant inconsistency in the device state perceived by adjacent QR codes at the same time and location. This inconsistency is considered an adverse factor on the rationality of sharing.

[0133] In this embodiment, the first feature value refers to the number of sampling points where the state difference is greater than a preset state difference threshold within the overlapping time interval. This feature value is used to quantify the frequency of significant state differences between adjacent QR codes within a shared sampling time period; the larger the value, the more abnormal differences occur within the shared time period.

[0134] In this embodiment, the non-overlapping portion refers to the intervals where the sampling time periods of adjacent QR codes' device status do not overlap. This portion reflects the device status information independently collected by the QR codes at different time locations, and is used to evaluate the impact of the sharing ratio on the device status coverage.

[0135] In this embodiment, the maximum and minimum state values ​​refer to the extreme values ​​obtained after traversing the device state sampling points corresponding to each QR code within a non-overlapping time period, which are used to characterize the range of state changes of the QR code within an independent sampling interval.

[0136] In the second feature value of this embodiment, the second feature value refers to the numerical overlap length formed between the device state change intervals of adjacent QR codes within their respective non-overlapping sampling intervals. This feature value is used to describe whether the device state ranges covered by the two QR codes in different sampling time periods are consistent. The greater the overlap, the higher the similarity between the two sampling results in the state space.

[0137] In this embodiment, the preset upper limit is a normalized reference scale set for the first feature value, used to limit the maximum reference value of the number of abnormal difference sampling points within a reasonable range. This upper limit allows the first feature values ​​under different sharing ratios to be mapped to a unified scale, avoiding excessive influence of extreme cases on subsequent evaluations.

[0138] In the first normalized feature value of this embodiment, the first normalized feature value is the result obtained by scaling the first feature value relative to a preset upper limit value, and its value range is limited to between zero and one. This normalized feature value is used to represent the proportion of abnormal differences within a shared time period, making sampling time periods of different lengths comparable.

[0139] In this embodiment, the preset state interval width is a reference interval set for the magnitude of device state changes, used to normalize the second feature value. This interval width reflects the range of state changes that the device may experience under normal operating conditions and is an important benchmark for measuring the degree of overlap between state intervals.

[0140] In the second normalized feature value of this embodiment, the second normalized feature value is the result obtained by scaling the second feature value relative to the width of the preset state interval. Its value is also limited to between zero and one, and is used to represent the degree of consistency of device state between adjacent QR codes in the non-overlapping sampling interval.

[0141] In the preset weights of this embodiment, the preset weights are weight parameters used to balance the influence of the first normalized feature value and the second normalized feature value in the shared evaluation. By setting different weights, the system's focus on the frequency of abnormal differences and the consistency of state coverage can be adjusted, making the shared evaluation more in line with the needs of specific equipment operating scenarios.

[0142] In the shared deduction value of this embodiment, the shared deduction value is a single evaluation quantity obtained by merging the first normalized feature value and the second normalized feature value according to a preset weight. It is used to represent the degree of negative impact of a certain adjacent QR code pair on the overall sharing rationality under the current sharing ratio.

[0143] In this embodiment, the total deduction is the result of summing the shared deduction values ​​corresponding to all adjacent QR code pairs along the QR code sequence. This total deduction comprehensively reflects the cumulative penalty degree caused by state differences and coverage inconsistencies among all QR codes under a certain second sharing ratio array condition.

[0144] In this embodiment, the benchmark reward value is a pre-set initial reference value for sharing evaluation, used to represent the optimal reward level under ideal sharing conditions. This benchmark reward value provides a unified starting point for all second sharing ratio arrays, making reward scores under different sharing ratio conditions comparable.

[0145] In the adaptive control reward score of this embodiment, the adaptive control reward score is a single continuous scalar obtained by deducting the corresponding total deduction from the baseline reward value as the initial value. It is used to comprehensively evaluate the sharing rationality of the second sharing ratio array in the actual QR code device status monitoring. The higher the adaptive control reward score, the better the sharing ratio performs in reducing abnormal differences and improving status consistency.

[0146] It should be noted that in this embodiment, the adaptive control reward score is not calculated statically all at once, but is gradually formed based on the device status monitoring results generated by QR codes under different sharing ratios, through cumulative analysis of the consistency and differences in device status between adjacent QR codes. This adaptive control reward score is used to comprehensively reflect the rationality of a certain second sharing ratio array in actual device operation monitoring, and its numerical change directly reflects the impact of different sharing ratios on redundant acquisition of device status, amplification of abnormal differences, and effective information sharing capabilities.

[0147] It should be noted that the state feedback cumulative update process introduced in this embodiment does not rely on external annotation results or manual intervention, but is entirely based on objective sampling data on the device state time axis. By uniformly measuring the behavioral characteristics of adjacent QR code device states in overlapping and non-overlapping time periods, the adaptive control reward score can form a comparable and sortable continuous evaluation basis among different second shared ratio arrays.

[0148] S6 compresses the second shared ratio array into an overall shared representation value, combines adaptive control reward score to select the optimal second shared ratio array, and controls the QR code product status monitoring.

[0149] In this embodiment, the process of compressing the second shared ratio array into an overall shared representation value, combining it with adaptive control reward scores to select the optimal second shared ratio array, and controlling the QR code product status monitoring specifically involves:

[0150] Read all the second shared ratio arrays, and read the adaptive control reward points corresponding to each second shared ratio array one by one, and construct the corresponding set of the second shared ratio arrays and the adaptive control reward points;

[0151] For each group of second shared ratio arrays, read the shared ratio of the device status of each adjacent scanning product in the array along the QR code sequence, and use the shared ratio as array element to form the shared ratio sequence corresponding to the second shared ratio array;

[0152] The values ​​of each shared proportion in the shared proportion sequence are squared, and the squared results are summed to obtain the sum of squares representation value corresponding to the second shared proportion array.

[0153] The sum of squares representation values ​​are normalized and mapped according to a preset normalization range, and the output value is a shared representation value whose range is limited to (0,1).

[0154] Using the overall shared representation value as the independent variable and the corresponding adaptive control reward score as the dependent variable, a two-dimensional discrete point set of overall shared representation value and adaptive control reward score is constructed.

[0155] The two-dimensional discrete point set is sorted according to the size of the overall shared representation value, and adjacent points are connected sequentially along the sorting direction to form a curve relationship between the adaptive control reward score and the overall shared representation value.

[0156] In the curve, the overall shared representation value corresponding to the adaptive control reward score reaching the maximum value is selected, and a second shared ratio array corresponding one-to-one with the overall shared representation value is determined as the optimal second shared ratio array;

[0157] The optimal second shared ratio array is remapped to an adaptive control object with corresponding state sampling start offset and state sampling coverage span, and the subsequent IoT-based QR code monitoring process is controlled based on the adaptive control object.

[0158] In the second shared ratio array of this embodiment, the second shared ratio array refers to a set of multiple shared ratios generated by the aforementioned continuous displacement disturbance process. Each set of arrays corresponds to a different equipment state time period configuration scheme and maintains a one-to-one mapping relationship with a set of determined state sampling start offset and state sampling coverage span.

[0159] In the adaptive control reward score of this embodiment, the adaptive control reward score is a continuous scalar evaluation result obtained through a state feedback cumulative update process for each second shared ratio array, which is used to reflect the comprehensive performance of the shared ratio configuration in reducing device state differences and improving QR code state consistency.

[0160] In the corresponding set of this embodiment, the corresponding set of the second shared ratio array and the adaptive control reward score is a data structure formed by binding each second shared ratio array with its corresponding adaptive control reward score. This set is used to ensure that in the subsequent analysis process, each overall shared representation value can be accurately associated with its source shared ratio configuration and its evaluation result.

[0161] In this embodiment, the shared ratio sequence refers to an ordered sequence formed by sequentially reading the shared ratios of adjacent scanning product equipment statuses in a given second shared ratio array, according to the order of the QR codes in the production process or scanning timeline. This sequence maintains the spatial or temporal distribution characteristics of the shared ratios in the QR code sequence, rather than being a simple unordered set.

[0162] In the squaring process of this embodiment, the squaring process is a method of amplifying the amplitude of each shared ratio value in the shared ratio sequence. Its purpose is to amplify the influence of larger shared ratios in the overall representation, while suppressing the interference of scattered and extremely small shared ratios on the judgment of the overall shared strength, so that the overall shared representation value can better reflect the main shared structural features.

[0163] In this embodiment, the sum of squares characterization value is the result of squaring and summing the values ​​of each sharing ratio in the sharing ratio sequence. It is used to comprehensively characterize the sharing intensity level of the second sharing ratio array across the entire QR code range. This characterization value reflects both the magnitude and distribution density of the sharing ratio, and its value increases with the overall sharing level.

[0164] In this embodiment, the preset normalization range is a reference interval pre-defined based on the possible range of shared ratio values ​​in the second shared ratio array, used to perform scale unification processing on the sum of squares representation values. This normalization range ensures that the overall shared representation values ​​among different second shared ratio arrays have a consistent value range, facilitating horizontal comparison.

[0165] In the overall shared representation value of this embodiment, the overall shared representation value is a continuous scalar obtained by mapping the sum of squares representation value to a preset normalization range, and its value is limited to between zero and one. This overall shared representation value is used to represent the sharing intensity level of a certain second sharing ratio array across all QR code dimensions, and is a compressed expression of the overall sharing ratio array.

[0166] In this embodiment, the two-dimensional discrete point set is constructed using the overall shared representation value as the horizontal dimension and the corresponding adaptive control reward score as the vertical dimension. This point set is used to characterize the reward change trend under actual equipment status monitoring feedback for different sharing intensity configurations.

[0167] In the sorting process of this embodiment, sorting by the size of the overall shared representation value means arranging the two-dimensional discrete point set according to the overall sharing intensity from low to high or from high to low, so as to form an ordered observation path in which the adaptive control reward score changes with the overall sharing degree.

[0168] In the curve relationship of this embodiment, the curve relationship of the adaptive control reward score changing with the overall shared characterization value is represented by the trend formed by connecting the sorted two-dimensional discrete point set in sequence. It is used to reflect the overall change law of the adaptive control reward score during the process of increasing or decreasing the sharing intensity, rather than fitting it as a continuous function.

[0169] In the maximum adaptive control reward score of this embodiment, the maximum adaptive control reward score means that the highest value reward result is selected from all the adaptive control reward scores corresponding to the second sharing ratio array. This result represents the state consistency and redundancy control effect brought about by the optimal sharing ratio configuration under the current device operation and QR code monitoring scenario.

[0170] In the optimal second sharing ratio array of this embodiment, the optimal second sharing ratio array refers to the second sharing ratio array corresponding to the maximum adaptive control reward score. Under the joint constraints of the overall sharing characterization value and the state feedback evaluation, this array is determined to be the sharing ratio configuration scheme that best meets the state monitoring requirements of the QR code device in this embodiment.

[0171] In the remapping process of this embodiment, remapping the optimal second shared ratio array to the state sampling start offset and state sampling coverage span means restoring the selected shared ratio configuration to a time control parameter that can be directly applied to the device state sampling process, based on the established correspondence between the aforementioned second shared ratio array and the adaptive control object.

[0172] In the QR code product status monitoring process of this embodiment, the adaptive control object controlling the subsequent IoT-based QR code monitoring means that in the actual operation phase, according to the status sampling start offset and status sampling coverage span corresponding to the optimal second shared ratio array, the device status sampling behavior after the QR code is triggered is uniformly controlled, thereby achieving a stable and optimal QR code device status monitoring effect.

[0173] It should be noted that, in this embodiment, the purpose of introducing the overall shared representation value is not simply to mathematically compress the second shared ratio array, but to uniformly map the shared ratio information distributed among multiple QR codes into a single continuous scalar, so that different second shared ratio arrays are comparable in terms of overall shared intensity, thereby forming a one-to-one evaluation relationship with the aforementioned adaptive control reward score.

[0174] It should be noted that this embodiment avoids judging solely based on the sharing status between local QR codes or a single reward indicator by jointly analyzing the overall shared representation value and the adaptive control reward score. Instead, it takes into account both the global distribution intensity of the sharing ratio and the actual feedback effect in the device status consistency evaluation, thereby selecting the second sharing ratio array that performs best in the actual IoT device operating environment.

[0175] Example 2, Figure 2 This invention presents an adaptive control system for QR code devices based on the Internet of Things (IoT), comprising a shared ratio generation module, a shared ratio disturbance generation module, a shared ratio control mapping module, a multi-ratio state control module, an adaptive control reward training module, and an adaptive control module. The shared ratio generation module is used to determine the overlap ratio between each QR code and its adjacent QR codes on the device state time axis based on cumulative contribution, obtaining the shared ratio of adjacent scanning product device states, and summarizing them to form a first shared ratio array. The shared ratio disturbance generation module is used to convert the first shared ratio array into the start and end positions of the device state time period corresponding to each QR code, and to continuously disturb the start and end positions to generate multiple sets of corresponding device state time periods, which are then converted in reverse to obtain several sets of... The second shared ratio array; the shared ratio control mapping module, used to establish the correspondence between the shared ratio and the state sampling start offset and the state sampling coverage span, to realize the conversion of the shared ratio array into an adaptive control object; the multi-ratio state control module, used to convert each second shared ratio array into a corresponding adaptive control object and control the QR code monitoring respectively; the adaptive control reward training module, used to train the corresponding adaptive control reward score based on the monitoring results under different second shared ratio arrays and the state feedback cumulative update process; the adaptive control module, used to compress the second shared ratio array into an overall shared representation value, combine the adaptive control reward score to select the best second shared ratio array, and control the QR code product status monitoring.

[0176] The present invention also includes an electronic device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to execute an Internet of Things-based adaptive control method for QR code devices.

[0177] The present invention also includes a computer-readable storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements an adaptive control method for QR code devices based on the Internet of Things.

[0178] In the embodiments provided by this invention, it should be understood that the disclosed system can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0179] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0180] Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be embraced within the invention. No appended diagram markings in the claims should be construed as limiting the scope of the claims.

[0181] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0182] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0183] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above.

[0184] In the embodiments provided in this disclosure, it should be understood that the disclosed systems and methods can also be implemented in other ways. The system embodiments described above are merely illustrative; for example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0185] It should be noted that, in this disclosure, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element limited by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0186] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. An adaptive control method for QR code devices based on the Internet of Things, characterized in that, Includes the following steps: Based on the cumulative contribution, the overlap ratio of each QR code with the adjacent QR code on the device status time axis is determined to obtain the device status sharing ratio of adjacent scanning products, and the sum is used to form the first sharing ratio array. The first shared ratio array is converted into the start and end positions of the device status time period corresponding to each QR code, and the start and end positions are continuously shifted to generate multiple sets of corresponding device status time periods. The reverse conversion is then used to obtain several sets of second shared ratio arrays. Establish the correspondence between the shared ratio and the state sampling start offset and the state sampling coverage span to realize the conversion of the shared ratio array into an adaptive control object; Each second shared ratio array is converted into a corresponding adaptive control object and used to control the QR code monitoring respectively; Based on the monitoring results under different second shared ratio arrays, the corresponding adaptive control reward score is trained by combining the state feedback cumulative update process. The second shared ratio array is compressed into an overall shared representation value. The optimal second shared ratio array is selected by combining adaptive control reward score and the QR code product status monitoring is controlled. The step of converting each second shared ratio array into a corresponding adaptive control object and controlling the QR code monitoring respectively is as follows: For each set of second shared ratio arrays, read the state sampling start offset and state sampling coverage span that correspond one-to-one with the second shared ratio array; When a QR code product enters the target process and triggers a scanning operation, the corresponding scanning trigger timestamp is recorded, and this timestamp is used as the sampling reference time of the QR code in the current process. Based on the state sampling start offset, the actual start time point of state sampling is determined along the device state time axis after the scanning trigger timestamp; Based on the state sampling coverage span, the actual end time of state sampling is determined along the equipment state time axis after the actual start time point, thereby forming the equipment state sampling time period of the QR code in the current process; In the IoT device status time-series data continuously collected on the device side, the corresponding device status data subsequence is extracted based on the time interval defined by the actual start time point and the actual end time point. The device status data subsequence is bound to the QR code that triggered the sampling process to form the QR code device status monitoring result under the second shared ratio array condition; The above process is performed on the state sampling start offset and state sampling coverage span corresponding to all second sharing ratio arrays to obtain multiple sets of QR code device status monitoring results under different sharing ratio conditions; The monitoring results based on different second shared ratio arrays, combined with the state feedback cumulative update process, are used to train the corresponding adaptive control reward score, specifically as follows: For each group of second shared ratio arrays, read the QR code device status sampling results formed during the QR code monitoring process, and arrange them according to the QR code scanning time order to obtain the QR code sequence corresponding to the second shared ratio array; Along the QR code sequence, select two adjacent QR codes in sequence, read the corresponding device status sampling time periods, and determine the overlapping time interval of the two on the device status time axis. Within the overlapping time interval, a state difference sequence is formed for each of the device state sampling points of adjacent QR codes at the same time position, and the number of sampling points with a state difference greater than a preset state difference threshold is counted as the first feature value of the adjacent QR code pair. For the non-overlapping portion of the device status sampling time period of adjacent QR codes, determine the maximum and minimum state values ​​of their respective device status sampling points, and use the overlap length of their value intervals as the second feature value of the adjacent QR code pair. The first feature value is normalized according to a preset upper limit value to obtain a first normalized feature value whose value range is limited to (0,1); The second feature value is normalized and mapped according to the preset state interval width to obtain a second normalized feature value whose value range is limited to (0,1); According to the preset weights, the first normalized feature value and the second normalized feature value are linearly merged to obtain the shared deduction value corresponding to the adjacent QR code pair. Along the QR code sequence, the shared deduction values ​​of all adjacent QR code pairs are accumulated and summarized to obtain the total deduction amount corresponding to the second shared ratio array; Using a preset benchmark reward value as the initial value, the corresponding total deduction is subtracted from the benchmark reward value to output a single continuous scalar, which serves as the adaptive control reward score corresponding to the second shared ratio array.

2. The adaptive control method for QR code devices based on the Internet of Things according to claim 1, characterized in that, The method of determining the overlap ratio between each QR code and its adjacent QR codes on the device status time axis based on cumulative contribution yields the device status sharing ratio of adjacent scanning products, which is then summarized to form the first sharing ratio array, specifically: Collect the QR code scanning time series of the product in the Internet of Things environment, as well as the device status sampling time series of the corresponding scanning node, and arrange the device status sampling points in chronological order; Using the time between two adjacent QR code scans as the time boundary, the device status sampling points in between are divided into a continuous status sampling interval; For the device state sampling points within the state sampling interval, the corresponding state change amplitudes are accumulated in chronological order to obtain the cumulative state change sequence within the interval. The final cumulative value of the state change accumulation sequence is taken as the total state change contribution for the scanning time interval, and the total state change contribution is divided into several continuous contribution segments in an equal division manner. Using the corresponding QR code scanning time as a reference point, the boundary positions of adjacent contribution segments are located along the cumulative sequence of state changes forward and backward, respectively, to determine the forward and backward boundaries of the QR code on the device state time axis. The device status time interval between the forward boundary and the backward boundary is taken as the device status belonging interval of the QR code; Align the device status affiliation intervals of adjacent QR codes with the time axis, calculate the time length of overlap between the affiliation intervals, and determine the sharing ratio of device status of adjacent scanning products by the ratio of the overlap time length to the time length of the corresponding QR code affiliation interval. Repeat the steps of determining the sharing ratio of adjacent scanning product device status for all QR codes, and summarize the sharing ratio of adjacent scanning product device status for each QR code to form the first sharing ratio array.

3. The adaptive control method for QR code devices based on the Internet of Things according to claim 2, characterized in that, The process involves converting the first shared ratio array into the start and end positions of the device status time period corresponding to each QR code, continuously shifting and perturbing the start and end positions to generate multiple sets of corresponding device status time periods, and then reversing the conversion to obtain several sets of second shared ratio arrays. Specifically: Read the shared ratio of adjacent scanning product device status corresponding to each QR code in the first shared ratio array, and simultaneously read the device status belonging range of the QR code. Each device status interval is represented as a device status time period defined by a start time point and an end time point, and the position of this time period on the device status time axis is recorded. Based on the overlap between the device status time period and the adjacent QR code device status time periods, determine the overlap time length and the exclusive time length corresponding to the current time period; Using the start and end times of the equipment state time period as displacement references, the equipment state time period is continuously displaced synchronously or in reverse along the equipment state time axis to generate multiple sets of candidate equipment state time periods that have undergone different degrees of expansion or translation. For each group of candidate device status time periods, keep the adjacent QR code device status time periods unchanged, and redetermine their corresponding overlapping time length and exclusive time length. Based on the ratio between the overlap length of the candidate device status time period and its own time length, the corresponding candidate adjacent scanning product device status sharing ratio is obtained; The sharing ratios corresponding to the time periods of candidate device status around the same QR code are summarized to form multiple sets of second sharing ratio arrays that correspond one-to-one with the first sharing ratio array.

4. The adaptive control method for QR code devices based on the Internet of Things according to claim 3, characterized in that, The establishment of the correspondence between the shared ratio and the state sampling start offset and the state sampling coverage span, realizing the conversion of the shared ratio array into an adaptive control object, is specifically as follows: For each group of second shared ratio arrays, read its corresponding candidate device status time period and obtain the start and end time points of the time period on the device status time axis. Using the scanning trigger time of the corresponding QR code as a time reference point, the starting offset of the state sampling after scanning is determined based on the positional relationship between the starting time point of the candidate device state time period and the scanning trigger time on the time axis. Based on the interval range between the start and end times of the candidate device status time period on the time axis, determine the coverage span of status sampling after the scan is triggered; By jointly setting the starting offset of state sampling and the coverage span of state sampling, the state sampling time period after the scanning is triggered forms a time overlap relationship with the state time period corresponding to the adjacent QR code on the device state time axis, which is consistent with the second shared ratio array. The state sampling start offset and state sampling coverage span corresponding to each QR code are combined to form an adaptive control object set that corresponds one-to-one with the second shared ratio array. Based on the set of adaptive control objects, the reverse conversion from the second shared ratio array to the starting offset of the scanning trigger state sampling and the state sampling coverage span is realized.

5. The adaptive control method for QR code devices based on the Internet of Things according to claim 4, characterized in that, The process of compressing the second shared ratio array into a total shared representation value, combining it with adaptive control reward scores to select the optimal second shared ratio array, and controlling the QR code product status monitoring specifically involves: Read all the second shared ratio arrays, and read the adaptive control reward points corresponding to each second shared ratio array one by one, and construct the corresponding set of the second shared ratio arrays and the adaptive control reward points; For each group of second shared ratio arrays, read the shared ratio of the device status of each adjacent scanning product in the array along the QR code sequence, and use the shared ratio as array element to form the shared ratio sequence corresponding to the second shared ratio array; The values ​​of each shared proportion in the shared proportion sequence are squared, and the squared results are summed to obtain the sum of squares representation value corresponding to the second shared proportion array. The sum of squares representation values ​​are normalized and mapped according to a preset normalization range, and the output value is a shared representation value whose range is limited to (0,1). Using the overall shared representation value as the independent variable and the corresponding adaptive control reward score as the dependent variable, a two-dimensional discrete point set of overall shared representation value and adaptive control reward score is constructed. The two-dimensional discrete point set is sorted according to the size of the overall shared representation value, and adjacent points are connected sequentially along the sorting direction to form a curve relationship between the adaptive control reward score and the overall shared representation value. In the curve, the overall shared representation value corresponding to the adaptive control reward score reaching the maximum value is selected, and a second shared ratio array corresponding one-to-one with the overall shared representation value is determined as the optimal second shared ratio array; The optimal second shared ratio array is remapped to an adaptive control object with corresponding state sampling start offset and state sampling coverage span, and the subsequent IoT-based QR code monitoring process is controlled based on the adaptive control object.

6. A system using the IoT-based adaptive control method for QR code devices as described in any one of claims 1-5, characterized in that, It includes a shared ratio generation module, a shared ratio perturbation generation module, a shared ratio manipulation mapping module, a multi-ratio state control module, an adaptive control reward training module, and an adaptive control module; The sharing ratio generation module is used to determine the overlap ratio of each QR code and its adjacent QR codes on the device status time axis based on the cumulative contribution, so as to obtain the device status sharing ratio of adjacent scanning products and summarize them to form the first sharing ratio array. The shared ratio perturbation generation module is used to convert the first shared ratio array into the start and end positions of the device status time period corresponding to each QR code, and to continuously perturb the start and end positions to generate multiple sets of corresponding device status time periods, and then convert them in reverse to obtain several sets of second shared ratio arrays. The shared ratio control mapping module is used to establish the correspondence between the shared ratio and the state sampling start offset and the state sampling coverage span, so as to realize the conversion of the shared ratio array into an adaptive control object; The multi-proportion state control module is used to convert each second shared proportion array into a corresponding adaptive control object and control the QR code monitoring respectively; The adaptive control reward training module is used to train the corresponding adaptive control reward score based on the monitoring results under different second shared ratio arrays and the cumulative update process of state feedback. The adaptive control module is used to compress the second shared ratio array into an overall shared representation value, combine the adaptive control reward score to select the optimal second shared ratio array, and control the monitoring of QR code product status.

7. An electronic device, characterized in that, The electronic device includes: At least one processor; And, a memory communicatively connected to the at least one processor; The memory stores a computer program that can be executed by the at least one processor, which is then executed by the at least one processor to enable the at least one processor to perform the IoT-based adaptive control method for QR code devices as described in any one of claims 1 to 5.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the IoT-based adaptive control method for QR code devices as described in any one of claims 1 to 5.

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