Intelligent warehouse management method and system based on RFID

Abstract

The invention discloses an RFID-based intelligent warehouse management method and system, and the method comprises the steps: building an environment and article joint evaluation factor through collecting RFID tag data and information of articles and sensors in a warehouse, designing a frequency band adaptability scoring formula, and dynamically selecting an optimal working frequency band; and the transmitting power is dynamically adjusted in combination with the optimal frequency band, so that the minimization of the energy consumption of the RFID system and the reduction of the operation cost are realized on the premise of ensuring the identification accuracy and the reading distance, and the reliability and the intelligent level of the warehousing system are effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of RFID-based warehouse management, and particularly to an RFID-based intelligent warehouse management method and system. Background Art

[0002] In recent years, radio frequency identification (RFID) technology, as an important part of the Internet of Things, has been widely used in fields such as warehouse management, logistics tracking, and asset monitoring. RFID technology realizes non-contact identification and data transmission of target objects through radio waves. Compared with traditional barcode technology, it has higher identification efficiency, stronger data storage capacity, and the superiority of multi-target concurrent reading. In the warehouse management scenario, RFID tags are widely used for tracking, inventorying, and managing goods, and its supporting reading and writing devices and the background system form an efficient and reliable data flow closed loop. However, with the continuous expansion of warehouse scale, the diversification of item types, and the improvement of environmental complexity, traditional RFID technology faces many challenges in terms of adaptability and performance optimization, such as the decline in data reading accuracy, the aggravation of frequency band interference, and the inability to dynamically balance power consumption.

[0003] Existing research and applications attempt to improve the performance of RFID systems by adjusting fixed frequency bands, increasing radio frequency power, or adopting multi-tag anti-collision algorithms. However, these methods often only work in specific scenarios and lack the overall adaptability to complex dynamic environments. For example, the stacking method, material density, and temperature and humidity changes of items in the warehouse environment will have a significant impact on the data reading and signal transmission of RFID tags, and the existing methods fail to fully combine environmental and item characteristics for dynamic optimization. In addition, while pursuing efficient management, the control of warehouse operation costs and the optimization of energy consumption have also become the focus of enterprises, but the existing technologies are insufficient in balancing high efficiency and low energy consumption. Therefore, how to construct an RFID adaptability optimization scheme based on the joint evaluation of environmental and item characteristics in a complex warehouse environment has become an important research direction for improving the level of intelligent warehouse management. Summary of the Invention

[0004] The purpose of this part is to outline some aspects of the embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this part, as well as in the abstract and title of the specification of this application, to avoid obscuring the purpose of this part, the abstract, and the title. However, such simplifications or omissions cannot be used to limit the scope of the present invention.

[0005] In view of the above existing problems, the present invention is proposed. Therefore, the present invention provides an RFID-based intelligent warehouse management method to solve the problems mentioned in the background art.

[0006] To solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides an RFID-based intelligent warehouse management method, including:

[0008] Obtain RFID tag data, item information in the warehouse, and receiving parameters of sensors respectively, and considering the comprehensive influence of item information in the warehouse and sensors on the working frequency band in the RFID tag data, establish an environmental and item joint evaluation factor;

[0009] Based on the environmental and item joint evaluation factor, design a frequency band adaptability scoring formula, calculate the adaptability score of each working frequency band in the RFID tag data, take the frequency band with the highest adaptability score as the current optimal working frequency band, and switch the current frequency band of the RFID tag to this optimal working frequency band;

[0010] According to the optimal working frequency band, adjust the transmission power in the RFID tag data. Taking the transmission power in the RFID tag data as the optimization target, while improving the efficiency of warehouse energy management, reduce the operating cost of warehouse management, so as to achieve intelligent warehouse management.

[0011] As a preferred scheme of the RFID-based intelligent warehouse management method described in the present invention, among them: obtaining RFID tag data, item information in the warehouse, and receiving parameters of sensors respectively, including:

[0012] Before obtaining RFID tag data, item information in the warehouse, and receiving parameters of sensors, divide the warehouse into several environmental monitoring sub-areas, deploy at least one group of sensors in each environmental monitoring sub-area, and initialize the sensor groups in the same sub-area, and record the initial environmental feature vectors of each sub-area;

[0013] Obtain the set of working frequency bands of the RFID tag, divide each working frequency band into fine-grained sub-frequency bands, initialize the transmission power of the RFID tag, and at the same time perform a structured binding on the item information in the warehouse and the stacking form of the items to obtain the item stack characteristics.

[0014] As a preferred scheme of the RFID-based intelligent warehouse management method described in the present invention, among them: considering the comprehensive influence of item information in the warehouse and sensors on the working frequency band in the RFID tag data, establishing an environmental and item joint evaluation factor, including:

[0015] Calculate the interference score of the initial environmental feature vector of each sub-area on the transmission power of the RFID tag to obtain the interference score of the sensor under the RFID tag;

[0016] According to the item stacking characteristics, establish the mutual influence factor between the item material and the sub-band, the coefficient factor between the item stacking type and the sub-band, and the attenuation factor between the item packaging density and the sub-band, to obtain the interference score of the item under the RFID tag;

[0017] Based on the interference score of the sensor under the RFID tag and the interference score of the item under the RFID tag, establish the joint evaluation factor of the environment and the item.

[0018] As a preferred solution of the RFID-based intelligent warehouse management method described in the present invention, wherein: based on the joint evaluation factor of the environment and the item, design a frequency band adaptability scoring formula to calculate the adaptability score of each working frequency band in the RFID tag data, including:

[0019] The frequency band adaptability scoring formula is expressed as:

[0020]

[0021] Among them, Adapt_S(F n ,i) represents the adaptability score of each working frequency band in the RFID tag data; Joint_S(f,i) represents the joint evaluation factor of the environment and the item; F n represents the nth working frequency band F; i represents the number of the environmental monitoring sub-region; f m represents the sub-band divided in the working frequency band F, m is the number of sub-bands; ξ represents the translation parameter.

[0022] As a preferred solution of the RFID-based intelligent warehouse management method described in the present invention, wherein: take the frequency band with the highest adaptability score as the current best working frequency band, and switch the current frequency band of the RFID tag to this best working frequency band, including:

[0023] When finding the working frequency band with the highest adaptability score, set it as the preferred working frequency band of the RFID tag in this sub-region, update the initial environmental feature vector of this sub-region, and record the updated initial environmental feature vector;

[0024] Construct a confidence interval based on the initial environmental feature vector before the update. Based on this confidence interval, judge whether the updated initial environmental feature vector is within this confidence interval. When it exceeds this confidence interval, recalculate the frequency band adaptability score.

[0025] As a preferred solution of the RFID-based intelligent warehouse management method described in the present invention, wherein: according to the best working frequency band, adjust the transmission power in the RFID tag data, and take the transmission power in the RFID tag data as the optimization target, including:

[0026] Set the minimum recognition accuracy A of the RFID tag according to the optimal operating frequency band min and the minimum reading distance D min , taking the transmit power in the RFID tag data as the optimization target, the following constraint conditions are obtained:

[0027]

[0028] P max ≥P≥P min .

[0029] Among them, P is the transmit power, denotes the recognition accuracy of the RFID tag, is the switched F n , denotes the reading distance of the RFID tag;

[0030] Based on the above constraint conditions, search simultaneously from the low-power end and the high-power end of the RFID tag until convergence within the power feasible interval, and find the minimum point that satisfies the transmit power within the power feasible interval.

[0031] As a preferred solution of the RFID-based intelligent warehouse management method described in the present invention, wherein: the above-mentioned based on the constraint conditions, search simultaneously from the low-power end and the high-power end of the RFID tag until convergence within the power feasible interval, and find the minimum point that satisfies the transmit power within the power feasible interval, includes:

[0032] Denote the low-power end P low of the RFID tag as the minimum transmit power P min of the RFID tag, and denote the high-power end P high of the RFID tag as the maximum transmit power P max of the RFID tag, to obtain the power feasible interval [P low , P high of the RFID tag;

[0033] Substitute the low-power end P low into the Accuracy and Coverage functions in the constraint conditions. If the constraint conditions of both the Accuracy and Coverage functions are satisfied, it means that any point at the low-power end satisfies the minimum transmit power P min of the RFID tag. Otherwise, substitute the high-power end P highSubstitute into the Accuracy and Coverage functions in the constraint conditions, and continue to determine whether the constraint conditions of both the Accuracy and Coverage functions are satisfied. If not, switch the operating frequency of the RFID tag. If satisfied, use the bisection method to reduce the high-power end P high Repeat the above process until the minimum value of the transmitted power P min or the maximum value of the transmitted power P max is output, and update P max ≥P≥P min ;

[0034] Find the minimum value of the transmitted power within the updated P interval range as the minimum point that satisfies the transmitted power of the RFID tag.

[0035] In a second aspect, the present invention provides an RFID-based intelligent warehousing management system, which includes:

[0036] An environment and item joint evaluation module configured to respectively obtain RFID tag data, item information in the warehouse, and receiving parameters of sensors, consider the comprehensive influence of the item information in the warehouse and the sensors on the operating frequency band in the RFID tag data, and establish an environment and item joint evaluation factor;

[0037] A frequency band adaptability scoring module configured to design a frequency band adaptability scoring formula based on the environment and item joint evaluation factor, calculate the adaptability score of each operating frequency band in the RFID tag data, take the frequency band with the highest adaptability score as the current best operating frequency band, and switch the current frequency band of the RFID tag to this best operating frequency band;

[0038] A transmitted power optimization module configured to adjust the transmitted power in the RFID tag data according to the best operating frequency band, take the transmitted power in the RFID tag data as the optimization target, while improving the efficiency of warehousing energy management, reduce the operating cost of warehousing management, and thus achieve intelligent warehousing management.

[0039] In a third aspect, the present invention provides a computer device including a memory and a processor, where the memory stores a computer program, and: when the processor executes the computer program, any step of the above method is implemented.

[0040] In a fourth aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored, and: when the computer program is executed by a processor, any step of the above method is implemented.

[0041] Compared with the prior art, the beneficial effects of the invention are:

[0042] 1. Through the establishment of the environmental and item joint evaluation factor, the present invention comprehensively considers the item materials, stacking forms, and environmental sensor parameters in the warehousing environment, dynamically calculates the adaptability scores for each working frequency band, and automatically switches to the optimal frequency band for operation, thereby effectively reducing signal interference and improving the recognition accuracy and reading efficiency of RFID data;

[0043] 2. Dynamically adjust the transmission power of RFID tags based on the optimal working frequency band, and combine with the optimization algorithm for the power feasible interval to ensure the use of the minimum transmission power on the premise of meeting the recognition accuracy and reading distance; this not only improves the efficiency of warehousing energy management, but also effectively reduces the operating cost, meeting the requirements of green and low-carbon development;

[0044] 3. Through the update of the environmental feature vectors in the sub-regions, monitor the changes in the warehousing environment in real time, and be able to maintain efficient and stable performance under variable warehousing conditions, greatly reducing the need for manual intervention and realizing intelligent and automated warehousing management. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts. Among them:

[0046] Figure 1 is the overall flowchart of the RFID-based intelligent warehousing management method according to an embodiment of the present invention;

[0047] Figure 2 is the comparison chart of the frequency band adaptability scores between the traditional solution and the solution of the present invention for the RFID-based intelligent warehousing management method according to an embodiment of the present invention;

[0048] Figure 3 is the comparison chart of the recognition accuracy, reading distance, energy consumption, and operating cost for the RFID-based intelligent warehousing management method according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0049] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following will provide a detailed description of the specific embodiments of the present invention in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of the present invention.

[0050] In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. However, the present invention may be practiced in other ways than those specifically described herein, and those skilled in the art may make similar extensions without departing from the spirit of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed below.

[0051] Secondly, as used herein, "an embodiment" or "embodiment" refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The appearances of "in an embodiment" in different places in this specification do not all refer to the same embodiment, nor are they separate or alternative embodiments that exclude each other.

[0052] The present invention will be described in detail in conjunction with the schematic diagrams. When describing the embodiments of the present invention in detail, for the sake of convenience of explanation, the cross-sectional views showing the device structure will be enlarged locally out of the general scale, and the schematic diagrams are only examples and should not limit the scope of protection of the present invention herein. In addition, in actual production, three-dimensional spatial dimensions including length, width, and depth should be included.

[0053] Meanwhile, in the description of the present invention, it should be noted that the orientation or positional relationship indicated by terms such as "upper, lower, inner, and outer" is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present invention. In addition, the terms "first, second, or third" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance.

[0054] Unless otherwise clearly defined and limited in the present invention, the terms "installed, connected, and coupled" should be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection; it may also be a mechanical connection, an electrical connection, or a direct connection, or may be indirectly connected through an intermediate medium, or may be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0055] Embodiment 1

[0056] Referring to Figure 1 , which is the first embodiment of the present invention, this embodiment provides an RFID-based intelligent warehouse management method, including:

[0057] S1. Obtain RFID tag data, item information in the warehouse, and the receiving parameters of the sensors respectively, and considering the comprehensive influence of the item information in the warehouse and the sensors on the working frequency band in the RFID tag data, establish an environmental and item joint evaluation factor;

[0058] Further, before obtaining the RFID tag data, the information of the items in the warehouse, and the receiving parameters of the sensors, the warehouse is divided into several environmental monitoring sub-areas, at least one group of sensors is deployed in each environmental monitoring sub-area, and the sensor groups in the same sub-area are initialized to record the initial environmental feature vector E of each sub-area i ;

[0059] Specifically, each group of sensors contains several different types of sensors;

[0060] Furthermore, obtain the set of operating frequency bands F of the RFID tags, divide each operating frequency band into fine-grained sub-bands f, initialize the transmission power of the RFID tags, and at the same time perform a structured binding on the information of the items obtained in the warehouse and the stacking form of the items to obtain the item stacking characteristics;

[0061] Specifically, the set of operating frequency bands of the RFID tags is represented as F = {F 1 , F 2 , F 3 , …, F n}, and the sub-bands in each operating frequency band are represented as F n = {f 1 , f 2 , f 3 , …, f m};

[0062] Specifically, the item information includes item materials (such as metal, plastic, paper, liquid), packaging density, volume, etc.; the stacking forms of the items include laying flat, standing upright, and staggered stacking, etc.;

[0063] It should be noted that the structured binding aims to associate the item information with the stacking form of the items. For example, [item material: metal, packaging density: high, stacking layers: 3 layers, stacking method: laying flat]; and by establishing this association relationship, the scattered items become a unified data format that can be analyzed, improving the standardization degree of warehouse management and reducing data redundancy and chaos;

[0064] Specifically, by associating the item stacking characteristics with the initial environmental feature vector of each sub-area, the mapping relationship between "item - sensor - RFID" can be obtained; for example, according to the above [item material: metal, packaging density: high, stacking layers: 3 layers, stacking method: laying flat], it becomes: [item material: metal, packaging density: high, stacking layers: 3 layers, stacking method: laying flat, humidity: 65%, temperature: 28°, transmission power: 100mW];

[0065] Further, calculate the interference score of the initial environmental feature vector of each sub-region on the transmission power of the RFID tag to obtain the interference score of the sensor under the RFID tag;

[0066] Specifically, the interference score of the sensor under the RFID tag can be calculated by the formula:

[0067]

[0068] where, E_S(f m , i) represents the interference score of the sensor under the RFID tag, represents the weight w of the k-th environment for the frequency band f, e k,i represents the normalized value e of the sub-region i in the k-th environment;

[0069] Further, according to the item stacking characteristics, establish the interaction factor between the item material and the sub-band, the coefficient factor between the item stacking type and the sub-band, and the attenuation factor between the item packaging density and the sub-band to obtain the interference score of the item under the RFID tag;

[0070] Specifically, the interference score of the item under the RFID tag is expressed by the formula:

[0071] O_S(f m , j) = M(Material j , f m ) + S(StackType j , f m ) + D(Density j , f m )

[0072] where, M(Material j , f m ) represents the interaction factor M between the item material Material and the sub-band f m ; S(StackType j , f m ) represents the coefficient factor S between the item stacking type StackType and the sub-band f m ; D(Density j , f m ) represents the attenuation factor D between the item packaging density Density and the sub-band f m ; O_S(f m , j) is the interference score of the item under the RFID tag; j represents the item;

[0073] Further, based on the interference score of the sensor under the RFID tag and the interference score of the item under the RFID tag, an environmental and item joint evaluation factor is established;

[0074] Specifically, the formula for the environmental and item joint evaluation factor is expressed as:

[0075]

[0076] Among them, Joint_S(f m , i) represents the environmental and item joint evaluation factor;

[0077] Specifically, the larger the environmental and item joint evaluation factor, the more severe the attenuation and interference of the signal when using frequency band f m in the sub-region i; the smaller the environmental and item joint evaluation factor, it indicates that the frequency band f m is more suitable for the sub-region i;

[0078] S2. Based on the environmental and item joint evaluation factor, design a frequency band adaptability scoring formula, calculate the adaptability score of each working frequency band in the RFID tag data, take the frequency band with the highest adaptability score as the current best working frequency band, and switch the current frequency band of the RFID tag to this best working frequency band;

[0079] Specifically, the frequency band adaptability scoring formula is expressed as:

[0080]

[0081] Among them, Adapt_S(F n , i) represents the adaptability score of each working frequency band in the RFID tag data; Joint_S(f, i) represents the environmental and item joint evaluation factor; F n represents the nth working frequency band F; i represents the number of the environmental monitoring sub-region; f m represents the sub-frequency band divided in the working frequency band F, m is the number of sub-frequency bands; ξ represents the translation parameter;

[0082] It should be noted that when Joint_S(f m , i) = ξ, the output is 0.5, which means that when Joint_S(f m , i) is greater than ξ, Adapt_S(F n , i) will be greater than 0.5, and when Joint_S(f m , i) is less than ξ, Adapt_S(F n , i) will be less than 0.5; therefore, the translation parameter is Adapt_S(F n, the demarcation line of (i); in practical applications, the value range of the frequency band adaptability score in different warehousing environments may vary greatly. By adjusting ξ, RFID can be compared within a more suitable numerical range. For example, when the interference level is generally high, most of the frequency band adaptability scores are close to or slightly higher than ξ, avoiding all frequency band adaptability scores from tending to 0 or 1 and losing the discrimination, thus more accurately reflecting the real frequency band situation;

[0083] Further, when the working frequency band with the highest adaptability score is found, set it as the preferred working frequency band of the RFID tag in this sub-region, update the initial environmental feature vector of this sub-region, and record the updated initial environmental feature vector;

[0084] Furthermore, construct a confidence interval based on the initial environmental feature vector before update. Based on the confidence interval, judge whether the updated initial environmental feature vector is within this confidence interval. When it exceeds this confidence interval, recalculate the frequency band adaptability score;

[0085] It should be noted that the construction of the confidence interval can help evaluate the reliability of the current working frequency band and judge whether it exceeds the reasonable range. In the solution of the present invention, the construction of the confidence interval can be obtained by using the mean and standard deviation of the traditional method according to the actual model of RFID, which will not be elaborated here;

[0086] S3. According to the optimal working frequency band, adjust the transmission power in the RFID tag data. Taking the transmission power in the RFID tag data as the optimization target, while improving the warehousing energy management efficiency, reduce the operating cost of warehousing management, so as to realize intelligent warehousing management;

[0087] Further, according to the optimal working frequency band, set the minimum recognition accuracy A min and the minimum reading distance D min of the RFID tag. Taking the transmission power in the RFID tag data as the optimization target, the following constraint conditions are obtained:

[0088]

[0089] P max ≥P≥P min .

[0090] Among them, P is the transmission power, represents the recognition accuracy of the RFID tag, is the switched F n , represents the reading distance of the RFID tag;

[0091] It should be noted that setting the minimum recognition accuracy and the minimum reading distance can help the RFID tag dynamically adjust the transmission power, so as to minimize the power consumption while improving the recognition rate and maintaining a reasonable reading distance;

[0092] Furthermore, based on the constraint conditions, search from both the low-power end and the high-power end of the RFID tag until convergence within the power feasible range, and find the minimum point that satisfies the transmission power within the power feasible range;

[0093] Specifically, the search process is as follows:

[0094] Denote the low-power end P of the RFID tag low as the minimum transmission power P of the RFID tag min , and denote the high-power end P of the RFID tag high as the maximum transmission power P of the RFID tag max , to obtain the power feasible range [P low , P high of the RFID tag;

[0095] It should be noted that the low-power end refers to the minimum power lower limit allowed by the RFID tag configuration, while the minimum transmission power refers to the minimum feasible power under the constraint conditions; similarly, the high-power end refers to the maximum power upper limit allowed by the RFID tag configuration, while the maximum transmission power refers to the maximum feasible power under the constraint conditions;

[0096] Substitute the low-power end P low into the Accuracy and Coverage functions in the constraint conditions. If the constraint conditions of both the Accuracy and Coverage functions are satisfied simultaneously, it means that any point at the low-power end satisfies the minimum transmission power P min of the RFID tag, that is, directly output the unique minimum transmission power; otherwise, substitute the high-power end P high into the Accuracy and Coverage functions in the constraint conditions, and continue to judge whether the constraint conditions of both the Accuracy and Coverage functions are satisfied simultaneously. If they are still not satisfied, switch the operating frequency of the RFID tag. If they are satisfied, perform a reduction of the high-power end P high by the bisection method, and repeat the above process until the unique minimum transmission power P min or the maximum transmission power P max is output, and update P max ≥P≥P min ;

[0097] Find the minimum value of the transmission power within the updated P interval range as the minimum point that satisfies the transmission power of the RFID tag;

[0098] Specifically, the dichotomy method is to select an intermediate value within the power feasible range. When the condition is met each time, the high-power end shrinks once, that is, P high →P mid gets closer; this approach is to reduce the computational complexity in the one-way search process and improve the search efficiency.

[0099] It should be noted that there are usually a large number of RFID tags in the warehousing environment. If each tag maintains a high power, the overall power consumption will be extremely large. By dynamically adjusting and finding the minimum feasible point of power, the overall energy consumption of the warehousing system can be significantly reduced, so as to reduce the electricity cost, and further reduce the overall operating cost, thereby improving the energy management efficiency of the entire warehouse.

[0100] Furthermore, this embodiment also provides an RFID-based intelligent warehousing management system, including:

[0101] An environment and item joint evaluation module, configured to respectively obtain RFID tag data, item information in the warehouse, and receiving parameters of sensors, consider the comprehensive influence of item information in the warehouse and sensors on the working frequency band in the RFID tag data, and establish an environment and item joint evaluation factor;

[0102] A frequency band adaptability scoring module, configured to design a frequency band adaptability scoring formula based on the environment and item joint evaluation factor, calculate the adaptability score of each working frequency band in the RFID tag data, take the frequency band with the highest adaptability score as the current best working frequency band, and switch the current frequency band of the RFID tag to this best working frequency band;

[0103] A transmission power optimization module, configured to adjust the transmission power in the RFID tag data according to the best working frequency band, take the transmission power in the RFID tag data as the optimization target, while improving the warehousing energy management efficiency, reduce the operating cost of warehousing management, so as to achieve intelligent warehousing management.

[0104] This embodiment also provides a computer device, applicable to the situation of the RFID-based intelligent warehousing management method, including:

[0105] A memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the RFID-based intelligent warehousing management method proposed in the above embodiment.

[0106] The computer device may be a terminal, which includes a processor, a memory, a communication interface, a display screen, and an input device connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The communication interface of the computer device is used to communicate with external terminals in a wired or wireless manner, and the wireless manner can be achieved through WIFI, carrier network, NFC (Near Field Communication), or other technologies. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball, or touchpad provided on the computer device housing, or an external keyboard, touchpad, or mouse, etc.

[0107] This embodiment also provides a storage medium, on which a computer program is stored, and when the program is executed by a processor, it implements the RFID-based intelligent warehouse management method proposed in the above embodiment.

[0108] The storage medium proposed in this embodiment and the data storage method proposed in the above embodiment belong to the same inventive concept. Technical details not described in detail in this embodiment can be referred to in the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0109] Embodiment 2

[0110] Referring to Figure 2 and Figure 3 , this is the second embodiment of the present invention. This embodiment provides an RFID-based intelligent warehouse management method, including: In order to verify that significantly reducing the overall energy consumption of the warehouse system, thereby reducing electricity costs and overall operating costs, by dynamically adjusting and finding the minimum feasible point of the RFID tag transmission power, this experiment was conducted multiple times in a small warehouse environment, comparing the differences between a traditional RFID system and an RFID system applying the method of the present invention in terms of power optimization, energy consumption, and operating costs;

[0111] The experimental site is a 600-square-meter warehouse, equipped with 8 shelves, storing various items, including metals, wood, plastic packaging, etc.; the warehouse temperature is maintained between 22°C and 30°C, and the relative humidity is 50% to 75%, simulating a typical warehousing environment; the height of each shelf is 2 meters, and the items are stacked on standard pallets, with each pallet sized 1 meter × 1 meter; high-frequency (UHF) RFID tags are selected, with a frequency band of 860 - 865 MHz and a maximum working distance of 10 meters; the tag specification is anti-metal interference type, suitable for the warehousing environment; a high-performance RFID reader of model R-Reader-5000 is used; an environmental sensor Env-Sensor-1000 is deployed to monitor the warehouse environment in real-time and provide data to the RFID system for dynamically adjusting the transmission power; a power meter is used to record the power consumption data of the system, with the unit of watt (W).

[0112] For the traditional RFID system test, under the condition of no power optimization, a fixed frequency band and transmission power (2 watts) are used for continuous testing for one week, recording the recognition accuracy, reading distance, and energy consumption of each RFID tag.

[0113] For the RFID system test of the present invention, the transmission power of the RFID tag is dynamically adjusted according to the temperature and humidity changes and the item stacking method. The power starts from the default value of 2 watts and is adjusted to the minimum feasible point (power range: 1.2 watts to 1.5 watts) through an algorithm.

[0114] Record the recognition accuracy, reading distance of the RFID tags under the two systems, and the power consumption of the system respectively, and conduct data comparison to analyze the impact of power optimization on energy efficiency and operating costs.

[0115] Through Figure 2 It can be seen that the solution of the present invention can significantly improve the adaptability score of RFID tags in a specific frequency band. Especially in the 861 MHz frequency band, its adaptability score has increased by 8.24%; in addition, through Figure 3 , it can be seen that the solution of the present invention is significantly superior to the traditional solution in terms of recognition accuracy, reading distance, energy consumption, and operating costs; especially under power optimization, the energy efficiency of the solution of the present invention has increased by 50%, while the operating cost has been reduced by 50%, that is, as the system energy consumption decreases, the operating cost also decreases.

[0116] It shows that through the optimization of the solution of the present invention, the RFID system not only performs better in terms of performance, but also shows significant advantages in energy efficiency and cost control, providing strong support for the intelligent and sustainable development of warehousing management.

[0117] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present application can be implemented in various computer languages, for example, object-oriented programming languages such as Java and interpreted scripting languages such as JavaScript.

[0118] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in one Figure 1 flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0119] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in one Figure 1 flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0120] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one Figure 1 flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0121] Although the preferred embodiments of the present application have been described, those skilled in the art can make additional changes and modifications once they learn the basic creative concepts. Therefore, the appended claims are intended to be construed as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0122] Obviously, those skilled in the art can make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalent technologies, this application is also intended to cover these modifications and variations.

Claims

1. The intelligent warehouse management method based on RFID is characterized by: include: The RFID tag data, the item information in the warehouse, and the receiving parameters of the sensor are obtained respectively, and the comprehensive impact of the item information and the sensor in the warehouse on the working frequency band in the RFID tag data is considered to establish the joint evaluation factor of the environment and the item; Based on the environment and item joint evaluation factors, a frequency band adaptability scoring formula is designed to calculate the adaptability score of each working frequency band in the RFID tag data, and the frequency band with the highest adaptability score is used as the current optimal working frequency band, and the current frequency band of the RFID tag is switched to the optimal working frequency band; According to the optimal working frequency band, the transmission power in the RFID tag data is adjusted, and the transmission power in the RFID tag data is used as the optimization target. While improving the efficiency of warehouse energy management, the operating cost of warehouse management is reduced, thereby realizing intelligent warehouse management.

2. The RFID-based intelligent warehouse management method according to claim 1, characterized in that: Get RFID tag data, item information in the warehouse, and sensor receiving parameters, including: Before obtaining RFID tag data, information about items in the warehouse, and receiving parameters of sensors, the warehouse is divided into several environmental monitoring sub-areas, at least one group of sensors is deployed in each environmental monitoring sub-area, and the sensor groups in the same sub-area are initialized, and the initial environmental feature vector of each sub-area is recorded; The working frequency band set of the RFID tag is obtained, each working frequency band is divided into fine-grained sub-frequency bands, the transmission power of the RFID tag is initialized, and the information of the items in the warehouse is structurally bound with the stacking form of the items to obtain the stacking characteristics of the items.

3. The RFID-based intelligent warehouse management method according to claim 2, characterized in that: Considering the comprehensive impact of the item information and sensors in the warehouse on the working frequency band in the RFID tag data, establish the joint evaluation factors of the environment and items, including: Calculate the interference score of the initial environmental feature vector of each sub-area on the transmission power of the RFID tag to obtain the interference score of the sensor under the RFID tag; According to the stacking characteristics of the items, the mutual influence factor between the item material and the sub-frequency band, the coefficient factor between the item stacking type and the sub-frequency band, and the attenuation factor between the item packaging density and the sub-frequency band are established to obtain the interference score of the item under the RFID tag; Based on the interference score of the sensor under the RFID tag and the interference score of the object under the RFID tag, an environment and object joint evaluation factor is established.

4. The RFID-based intelligent warehouse management method according to claim 3, characterized in that: Based on the environment and item joint evaluation factors, a frequency band adaptability scoring formula is designed to calculate the adaptability score of each working frequency band in the RFID tag data, including: The frequency band adaptability scoring formula is expressed as: Among them, Adapt_S(F n ,i) represents the adaptability score of each working frequency band in the RFID tag data; Joint_S(f,i) represents the joint evaluation factor of the environment and the item; F n represents the nth working frequency band F; i represents the number of the environmental monitoring sub-area; f m It represents the sub-bands divided in the working frequency band F, m is the number of sub-bands; ξ represents the translation parameter.

5. The RFID-based intelligent warehouse management method according to claim 4, characterized in that: The frequency band with the highest adaptability score is used as the current best working frequency band, and the current frequency band of the RFID tag is switched to the best working frequency band, including: When the working frequency band with the highest adaptability score is found, it is set as the preferred working frequency band of the RFID tags in the sub-area, the initial environment feature vector of the sub-area is updated, and the updated initial environment feature vector is recorded; A confidence interval is constructed based on the initial environment feature vector before updating, and the confidence interval is used as a reference to determine whether the updated initial environment feature vector is within the confidence interval. When it exceeds the confidence interval, the frequency band adaptability score is recalculated.

6. The RFID-based intelligent warehouse management method according to claim 2 or 5, characterized in that: According to the optimal working frequency band, adjusting the transmission power in the RFID tag data, taking the transmission power in the RFID tag data as the optimization target, includes: According to the optimal working frequency band, set the minimum recognition accuracy of the RFID tag A min And the minimum reading distance D min , taking the transmission power in the RFID tag data as the optimization target, the constraints are as follows: P max ≥P≥P min . Where P is the transmit power, Expressed as the recognition accuracy of the RFID tag, F after switching n , Expressed as the reading distance of the RFID tag; Based on the constraint condition, the low power end and the high power end of the RFID tag are searched simultaneously until they converge to a feasible power interval, and the minimum point satisfying the transmission power is found within the feasible power interval.

7. The RFID-based intelligent warehouse management method according to claim 6, characterized in that: The method of searching simultaneously from the low power end and the high power end of the RFID tag based on the constraint condition until converging to a feasible power interval, and finding a minimum point satisfying the transmission power within the feasible power interval, includes: The low power terminal P of the RFID tag low Expressed as the minimum transmission power P of the RFID tag min , the high power terminal P of the RFID tag high Expressed as the maximum transmission power P of the RFID tag max , and obtain the feasible power interval of the RFID tag [P low ,P high ]; The low power terminal P low Substitute the Accuracy and Coverage functions in the constraints. If the constraints of the Accuracy and Coverage functions are met at the same time, it means that any point on the low-power end meets the minimum transmission power P of the RFID tag. min Otherwise, the high power terminal P high Substitute the Accuracy and Coverage functions in the constraints to continue to determine whether the constraints of the Accuracy and Coverage functions are met at the same time. If not, switch the working frequency of the RFID tag. If it is met, use the dichotomy method to perform high-power P high Repeat the above process until the unique minimum transmit power value P is output. min Or the maximum transmission power P max , update P max ≥P≥P min ; The minimum value of the transmission power in the updated P interval range is found as the minimum point that satisfies the RFID tag transmission power.

8. An RFID-based intelligent warehouse management system, based on the RFID-based intelligent warehouse management method according to any one of claims 1 to 7, characterized in that: include: The environment and item joint evaluation module is configured to respectively obtain RFID tag data and item information in the warehouse and receiving parameters of sensors, consider the comprehensive impact of the item information and sensors in the warehouse on the working frequency band in the RFID tag data, and establish an environment and item joint evaluation factor; A frequency band adaptability scoring module is configured to design a frequency band adaptability scoring formula based on the environment and item joint evaluation factors, calculate the adaptability score of each working frequency band in the RFID tag data, take the frequency band with the highest adaptability score as the current best working frequency band, and switch the current frequency band of the RFID tag to the best working frequency band; The transmission power optimization module is configured to adjust the transmission power in the RFID tag data according to the optimal working frequency band, and take the transmission power in the RFID tag data as the optimization target, thereby improving the efficiency of warehouse energy management and reducing the operating cost of warehouse management, thereby realizing intelligent warehouse management.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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