A stock mapping statistical system and method based on dynamic average flow rate changes

Abstract

The present invention discloses a stock mapping statistics system and method based on dynamic average flow rate changes, including an information collection module for collecting data information at a collection location, a flow rate calculation module for calculating the speed of an identification flow passing through the collection location within a certain time accuracy, a mapping module for matching a metering mapping index based on an average flow rate from a metering mapping index table, and a calculation correction module for realizing correction calculation of the final stock. The system can not only adapt to changes in flow and time, but also the statistical stock error value can be continuously and effectively controlled within a certain acceptable range under the premise of stable sensor error, thereby avoiding human intervention to the greatest extent.

Description

Technical Field

[0001] The present invention relates to the field of stock statistics, and in particular to a stock mapping statistics system and method based on dynamic average flow velocity changes. Background Art

[0002] At present, most queuing channels use technical means such as video monitoring of human shapes and faces and license plate number recognition, but this technical means has a relatively large problem, which is the error superposition problem. For example, if the entrances and exits of the queue are all IoT devices, when the error is 1%, with a flow rate of 100 per minute, the maximum error of the entrances and exits will reach 1440%. If the queue is continuous 7*24 hours, the annual error limit will reach 525600%, which is 5256 times. This error value is huge, of course, these proportions will be even greater according to actual conditions. In addition, the traditional method of calculating inventory is the original number of entrances + initial inventory number - exit number. With this original method, the errors of the entrances and exits will become more serious as time accumulates. In order to obtain more accurate data, it is often necessary to manually clear or restart a new round of statistics, which is obviously very inconvenient for many scenarios with flow changes.

[0003] Therefore, it is particularly important to design an inventory statistics system that can be controlled within a certain acceptable error range, avoid manual intervention after the calculation begins, and can adapt to changes in queue flow at different times.

[0004] In view of this, it is necessary to improve the inventory statistics system in the existing technology to solve the above problems. Summary of the invention

[0005] The object of the present invention is to provide an inventory statistics system which can not only adapt to flow and time changes, but also continuously and effectively control the counted inventory error value within a certain acceptable range under the premise of stable sensor error, and can avoid manual intervention to the greatest extent.

[0006] To achieve the above-mentioned purpose, the present invention provides a stock mapping statistical system based on dynamic average flow rate changes, including an information collection module for collecting data information at a collection location, a flow rate calculation module for calculating the speed of a marker flow passing through a collection location within a certain time accuracy, a mapping module for matching a metering mapping index based on an average flow rate from a metering mapping index table, and a calculation correction module for realizing correction calculation of the final stock;

[0007] The flow rate calculation module counts the data information of the information collection module according to the predetermined time precision and the number of flow marks passing through the collection location to obtain the average flow rate within the unit time precision;

[0008] The mapping module maps the corresponding metering mapping index in a predetermined metering mapping index table according to the average flow rate;

[0009] The calculation and correction module is provided with an original inventory unit, the original inventory unit is provided with a predetermined initial inventory value, and a final inventory value is obtained according to a predetermined calculation formula based on the average flow rate and the metering mapping index;

[0010] Furthermore, the information collection module adopts a sensor device based on the Internet of Things.

[0011] Furthermore, the information collection module is set with a collection module at the queue entrance and a collection module at the queue exit according to the flow direction of the marker.

[0012] Furthermore, the flow rate calculation module may calculate the average flow rate by accumulating a plurality of average flow rates within the same time precision to obtain a total average flow rate.

[0013] Furthermore, the metering mapping index table is based on the total average flow rate.

[0014] Furthermore, the calculation and correction module is also provided with an identification flow direction identification unit for determining the stock flow direction based on the average flow velocity at the queue entrance and the average flow velocity at the queue exit.

[0015] The present invention also provides a stock mapping statistical method based on dynamic average flow rate changes, which is characterized by comprising the following steps:

[0016] S1. Set the initial value of stock r;

[0017] S2. Preset time accuracy value T;

[0018] S3. Calculate the average flow velocity V;

[0019] S4. Matching the metering mapping index α from the metering mapping index table;

[0020] S5. Calculate the final stock R according to the established formula R=α*V+r.

[0021] Furthermore, the method further comprises the following steps:

[0022] S3a. After collecting the average flow rate V of a certain time accuracy, determine whether there are different average flow rates V at the queue entrance in and the average flow velocity V at the queue exit out ; If it exists, calculate V = V in +V out , and run sign(V in -V out) obtain the stock flow direction, and then execute S3b; if it does not exist, set the average flow rate V at the corresponding non-existent queue entrance in Or the average flow velocity V at the queue exit out is 0, V is set to V in or V out The value of and execute S3b;

[0023] S3b is set with a flow rate threshold determination unit, according to the assigned average flow rate V, determine whether the time accuracy T needs to be adjusted, if necessary, return to execute S2; if not, execute S3c;

[0024] S3c determines whether it is necessary to accumulate multiple average flow rates. If it is necessary to accumulate several average flow rates, execute S3d; if not, execute S3e;

[0025] 3d. Set the cumulative time zone tβ~tγ, and calculate the average flow rate V in the time zone tin and V tout The accumulation formula is:

[0026] S3e. Obtain the final total average flow velocity V.

[0027] Furthermore, the method further comprises the following steps:

[0028] S5a. According to sign(V in -V out ), and make the average flow velocity at the queue entrance and the average flow velocity at the queue exit to determine the flow direction;

[0029] S5b. Output the final stock R according to the established formula.

[0030]

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] 1. The inventory can be completely controlled within a certain range of mean difference and is not affected by changes in flow and time.

[0033] 2. When the sensor error range is stable, the error of the obtained inventory is within an acceptable range.

[0034] 3. After the calculation is started, no manual adjustment is required, and the system can realize automatic accounting function. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is a schematic diagram of the inventory mapping statistical system based on the dynamic average flow velocity change of the present invention;

[0036] Figure 2 It is a schematic diagram of another stock mapping statistical system based on dynamic average flow velocity changes;

[0037] Figure 3 It is a schematic diagram of the statistical method of stock mapping based on the dynamic average flow velocity change;

[0038] Figure 4 It is a schematic diagram of another stock mapping statistical method based on the dynamic average flow velocity change;

[0039] Figure 5 It is a logical illustration of the method for realizing inventory mapping statistics based on dynamic average flow velocity changes of the present invention;

[0040] Figure 6 The figure is a logical diagram of another method for implementing inventory mapping statistics based on dynamic average flow velocity changes. DETAILED DESCRIPTION

[0041] The present invention is described in detail below in conjunction with the various embodiments shown in the accompanying drawings, but it should be noted that these embodiments are not limitations of the present invention, and any equivalent transformations or substitutions in functions, methods, or structures made by ordinary technicians in the field based on these embodiments are all within the scope of protection of the present invention.

[0042] Example 1, please refer to Figure 1 As shown, Figure 1 It is a schematic diagram of the inventory mapping statistical system based on dynamic average flow rate changes of the present invention.

[0043] In this embodiment, the inventory mapping statistical system based on the dynamic average flow rate change includes an information collection module for collecting data information at the collection point, a flow rate calculation module, a mapping module for matching the metering mapping index based on the average flow rate from the metering mapping index table, and a calculation correction module for correcting the final inventory. Specifically, in practical applications, the information collection module uses sensor equipment based on the Internet of Things, such as video monitoring of human shape and face, license plate number recognition and other sensor devices. In particular, the information collection module can be set with a collection module at the queue entrance and a collection module at the queue exit according to the flow direction of the marker. In this way, the inventory calculation of the dynamic liquidity of the queue is truly solved in practical applications.

[0044] The flow rate calculation module counts the data information of the information collection module according to the established time accuracy, and identifies the number of flows passing through the collection point to obtain the average flow rate within the unit time accuracy. The mapping module maps the corresponding metering mapping index in the established metering mapping index table according to the average flow rate; the accounting correction module is provided with an original inventory unit, and the original inventory unit is provided with an established inventory initial value, and the final inventory value is obtained according to the established calculation formula based on the average flow rate and the metering mapping index. Specifically, the so-called metering mapping index table is an accounting model established according to the scenario of the application of this system. After repeated calculations, the difference ratio between the calculated inventory value calculated for different average flow rates and the actual inventory value is obtained. The value of this difference ratio is the metering mapping index. It should be noted here that this system is suitable for situations where the actual inventory is verifiable, that is, the actual inventory can be verified by manual means or other intelligent means. Then, after the system calculations are running, as the frequency of the calculation model's operation increases, the obtained metering mapping index will become more accurate, and the dynamic inventory value calculated for the dynamic average flow rate will also become more accurate.

[0045] For further information, please refer to Figure 2 , Figure 2 This is a schematic diagram of another inventory mapping statistical system based on dynamic average flow rate changes of the present invention. The calculation method of the average flow rate in the flow rate calculation module can also be adopted by accumulating multiple average flow rates within the same time accuracy to obtain the total average flow rate. Specifically, the flow rate calculation module includes several average flow rate calculation modules, such as average flow rate 1, average flow rate 2, average flow rate 3...average flow rate n, and each average flow rate n is respectively calculated The average flow rate of a certain time accuracy value within a certain time interval. At this time, the metering mapping index table is based on the total average flow rate. After the total average flow rate is obtained by multiple superposition of average flow rates, the corresponding metering mapping index is obtained through the reference mapping of the metering mapping index table. The method of superimposing average flow rates, relative to the traditional inventory calculation method, is simply to add the number at the inlet to the original inventory minus the number at the outlet to obtain the existing inventory. Simply performing subtraction operations on direct data obtained by sensing means often increases the error value to a greater extent. In this embodiment, the metering mapping index table is obtained by accumulating multiple average flow rates and then performing further repeated self-learning of the calculation model based on the total average flow rate, which better weakens the physical errors caused by the sensing equipment and makes the system calculation more accurate.

[0046] Furthermore, the calculation and correction module is also provided with a flow direction identification unit (not shown) for determining the flow direction of the stock according to the average flow velocity at the queue entrance and the average flow velocity at the queue exit. The purpose is to solve the influence of the flow velocity and direction of the queue at the entrance and exit on the circulation of the actual stock. For example, when the average flow velocity at the entrance is higher than the average flow velocity at the exit, then generally speaking, the stock will increase; otherwise, the stock will decrease.

[0047] Experiments have shown that under certain conditions, the data information obtained from the information acquisition module can be greatly reduced by the mapping calculation method of the dynamic average flow rate after being processed by the superposition of the flow rate calculation module and the mapping module. The data inaccuracy caused by the data error obtained by the sensing means can be greatly reduced. In practical applications, we were surprised to find that when the monitoring efficiency of the Internet of Things or other sensors is less than 100%, and the time and conditions for inventory clearance are unknown, the inventory value obtained by this system can be completely controlled within a certain range of mean difference, and is not affected by changes in flow and time; in addition, when the sensor error range is stable, the error of the inventory value obtained is within an acceptable range; no manual adjustment is required after the calculation is started.

[0048] Example 2, please refer to Figure 3 and Figure 5 , Figure 3 Schematic diagram of the stock mapping statistical method based on dynamic average flow rate changes. Figure 5 This is a logical diagram of the statistical implementation method of stock mapping based on dynamic average flow velocity changes.

[0049] In this embodiment, the implementation prerequisites of this method are:

[0050] 1. The stock is known at the beginning of the calculation;

[0051] 2. The actual inventory is verifiable, that is, the actual inventory can be verified through existing technical means.

[0052] This method specifically comprises the following steps:

[0053] S1. Set the initial value r of the stock; specifically, the original stock known in the premise.

[0054] S2. Preset time accuracy value T; specifically, the setting of the time accuracy value T can be determined according to the actual application scenario. For example, for a queue with a faster traffic speed, a lower time accuracy value T can be set, such as 5 minutes or less; conversely, a higher time accuracy value T can be set.

[0055] S3. Collect the average flow rate V of a certain time precision; specifically, when calculating the average flow rate V, a certain time zone can be set forward from the current time precision, and within the time zone, the corresponding average flow rate V is obtained with the time precision T as the unit. For example, in a parking lot with a time precision T of 5 minutes, within the first half hour of the current time precision T, there are 6 vehicle flow rate values ​​with a unit time precision T, namely 6 vehicles, 8 vehicles, 4 vehicles, 9 vehicles, 6 vehicles, and 10 vehicles. In this half hour, the average flow rate V for the queue in the parking lot is 7 vehicles / 5 minutes.

[0056] S4. Match the metering mapping index α from the metering mapping index table; specifically, according to the source of the metering mapping index table mentioned above, that is, the mapping table between the average flow rate and the metering mapping index (i.e., V-α) obtained by learning the difference ratio between the inventory calculation value and the actual inventory value through the accounting model, the average flow rate V is used as the mapping element V an , by comparing in sequence n=n+1, find the reference average flow rate V corresponding to the average flow rate V in the mapping table a , according to V a The mapping output corresponds to the metering mapping index α.

[0057] S5. According to the established formula R=α*V+r, calculate the final stock R; the final stock R obtained is the stock value within the current unit time precision. For example, for a certain parking lot, it is the number of vehicles in the parking lot within the current time precision.

[0058] Example 3, please refer to Figure 4 and Figure 6 , Figure 4 This is another schematic diagram of a stock mapping statistical method based on dynamic average flow rate changes. Figure 6 A logical diagram of another method for implementing inventory mapping statistics based on dynamic average flow rate changes

[0059] The difference from the above-mentioned second embodiment is that this embodiment can be applied to the scenario where a unidirectional or bidirectional circulation queue affects the inventory, and the implementation steps further include the following steps:

[0060] S3a. After collecting the average flow rate V of a certain time accuracy, determine whether there are different average flow rates V at the queue entrance in and the average flow velocity V at the queue exit out ; If it exists, calculate V = V in +V out , and run sign(V in -V out ), then execute S3b; if it does not exist, set the average flow rate V at the entrance of the corresponding non-existent queue in Or the average flow velocity V at the queue exit outis 0, V is set to V in or V out , and execute S3b; Specifically, in most application scenarios, when the queue has both an inlet and an outlet, the change in the stock provides the inevitability of the change in flow direction. In other words, the stock will increase or decrease due to the change in flow direction.

[0061] S3b. A flow rate threshold determination unit is set to determine whether the time accuracy T needs to be adjusted according to the assigned average flow rate V. If necessary, return to execute S2; if not, execute S3c. Specifically, in actual applications, there are often peaks and troughs in the queue. For such peak flow and trough flow, the setting of the time accuracy T should be adjusted to be closer to the actual situation, so as to obtain more accurate data. Therefore, this step is preset with a flow rate threshold determination unit, that is, according to the average flow rate V, when the average flow rate V is higher than the flow rate V0 preset in the flow rate threshold determination unit, then the time accuracy value needs to be readjusted. Otherwise, the next step can be continued.

[0062] S3c determines whether it is necessary to accumulate multiple average flow rates. If it is necessary to accumulate several average flow rates, execute S3d; if not, execute S3e;

[0063] 3d. Set the cumulative time zone t β ~t γ , for all average flow velocities V in its time zone tin and V tout The accumulation formula is:

[0064] S3e. Obtain the final total average flow velocity V.

[0065] This embodiment also includes the following steps:

[0066] S5a. According to sign(V in -V out ) obtain the stock flow direction, and make the average flow velocity at the queue entrance and the average flow velocity at the queue exit to determine the flow direction; specifically, when the average flow velocity at the queue entrance V in Higher than the average flow rate V at the queue entrance out , then for the stock, it will increase relative to the original stock, otherwise it will decrease relative to the original stock.

[0067] S5b. Combine the total average flow velocity V obtained in the above steps and the stock flow direction result, and output the final stock R; specifically, the final stock value R is obtained according to the following formula.

[0068]

[0069] Specifically, case ① does not perform the accumulation of multiple average flow rates, and case ② performs the accumulation of multiple average flow rates.

[0070] Embodiment 4 provides a stock mapping statistics device based on dynamic average flow rate changes, including a processor and a memory, wherein the memory is used to store computer programs; the processor is used to execute the computer programs stored in the memory to implement the stock mapping statistics method based on dynamic average flow rate changes of the above-mentioned embodiment 2 or 3.

[0071] Embodiment 5 provides a computer-readable storage medium. When the program in the storage medium is executed by a processor, the inventory mapping statistical method based on dynamic average flow rate changes of the above embodiment 2 or 3 is implemented.

[0072] The series of detailed descriptions listed above are only specific descriptions of feasible implementation methods of the present invention. They are not intended to limit the scope of protection of the present invention. Any equivalent implementation methods or changes that do not deviate from the technical spirit of the present invention should be included in the scope of protection of the present invention.

[0073] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

Claims

1. A stock mapping statistical system based on dynamic average flow rate changes, comprising an information collection module for collecting data information at a collection location, a flow rate calculation module, a mapping module for matching a metering mapping index based on an average flow rate from a metering mapping index table, and a calculation correction module for realizing correction calculation of the final stock, wherein the flow rate calculation module is used to calculate the speed of the marker flow passing through the collection location within a certain time accuracy; characterized in that: The flow rate calculation module counts the data information of the information collection module according to the predetermined time precision and the number of flow marks passing through the collection location to obtain the average flow rate within the unit time precision; The mapping module maps the corresponding metering mapping index in a predetermined metering mapping index table according to the average flow rate; The calculation and correction module is provided with an original inventory unit, the original inventory unit is provided with a predetermined initial inventory value, and a final inventory value is obtained according to a predetermined calculation formula based on the average flow rate and the metering mapping index; Also included is a stock mapping statistical method based on dynamic average flow rate changes, comprising the following steps: S1. Set the initial value of stock r; S2. Preset time accuracy value T; S3. Collect the average flow rate V of a certain time accuracy; S4. Matching the metering mapping index α from the metering mapping index table; S5. Calculate the final stock R according to the established formula R=α*V+r.

2. The inventory mapping statistical system based on dynamic average flow rate changes according to claim 1, characterized in that: The information collection module adopts a sensor device based on the Internet of Things.

3. The inventory mapping statistical system based on dynamic average flow rate changes according to claim 1, characterized in that: The information collection module is set with a collection module at the queue entrance and a collection module at the queue exit according to the flow direction of the marker.

4. The inventory mapping statistical system based on dynamic average flow rate changes according to claim 2 or 3, characterized in that: The flow rate calculation module calculates the average flow rate by accumulating a plurality of average flow rates within the same time precision to obtain a total average flow rate.

5. The inventory mapping statistical system based on dynamic average flow rate changes according to claim 4, characterized in that: The metering mapping index table is based on the total average flow rate.

6. The inventory mapping statistical system based on dynamic average flow rate changes according to claim 4, characterized in that: The calculation and correction module is also provided with a flow direction identification unit for determining the flow direction of the stock based on the average flow velocity at the queue entrance and the average flow velocity at the queue exit.

7. The inventory mapping statistical system based on dynamic average flow rate changes according to claim 4, characterized in that: The following steps are also included: S3a. After collecting the average flow rate V of a certain time accuracy, determine whether there are different average flow rates V at the queue entrance in and the average flow velocity V at the queue exit out ; If it exists, calculate V = V in +V out , and run sign(V in -V out ) obtain the stock flow direction, and then execute S3b; if it does not exist, set the average flow rate V at the corresponding non-existent queue entrance in Or the average flow velocity V at the queue exit out is 0, V is set to V in or V out The value of and execute S3b; S3b is set with a flow rate threshold determination unit, according to the assigned average flow rate V, determine whether the time accuracy T needs to be adjusted, if necessary, return to execute S2; if not, execute S3c; S3c determines whether it is necessary to accumulate multiple average flow rates. If it is necessary to accumulate several average flow rates, execute S3d; If not required, execute S3e; S3d. Set the cumulative time zone t β ~t γ , for all average flow velocities V in its time zone tin and V tout The accumulation formula is: S3e. Obtain the final total average flow velocity V.

8. The inventory mapping statistical system based on dynamic average flow rate changes according to claim 7 is characterized in that The following steps are also included: S5a. According to sign(V in -V out ), and make the average flow velocity at the queue entrance and the average flow velocity at the queue exit to determine the flow direction; S5b. Output the final stock R according to the established formula Case ① does not perform the accumulation of multiple average flow rates, and case ② performs the accumulation of multiple average flow rates.

Images