CN111967547A

CN111967547A - Multi-label checking method, electronic equipment and storage medium

Info

Publication number: CN111967547A
Application number: CN202010641339.5A
Authority: CN
Inventors: 梁甲昌; 李玉惠; 邓木荣
Original assignee: Chainway Information Technology Co ltd
Current assignee: Shenzhen Chengcheng Information Co ltd
Priority date: 2020-07-06
Filing date: 2020-07-06
Publication date: 2020-11-20
Anticipated expiration: 2040-07-06
Also published as: CN111967547B

Abstract

The embodiment of the application provides a multi-label checking method, electronic equipment and a storage medium, and relates to the technical field of radio frequency identification. The embodiment of the application comprises the following steps: acquiring a plurality of label information at each frequency point of the ultrahigh frequency electronic label frequency band by adopting a preset power value; performing signal intensity detection on each label to obtain a signal intensity value of each label; carrying out weighted calculation on the signal intensity value according to a preset weighting rule to obtain a weighted signal intensity value; and filtering the serial reading label information according to a preset first signal intensity threshold value and a weighted signal intensity value. According to the method and the device, the signal intensity value of each label is weighted and calculated, and then the weighted signal intensity value of each label is compared with the signal intensity threshold value, target label information and string reading label information can be distinguished, label string reading is avoided, and the accuracy of multi-label counting is improved.

Description

Multi-label checking method, electronic equipment and storage medium

Technical Field

The embodiment of the application relates to the field of Radio Frequency Identification (RFID), and in particular, to a multi-tag inventory method, an electronic device, and a storage medium.

Background

In retail and warehousing, particularly in the delivery and warehousing links of commodities, the labels of the commodities need to be checked so as to facilitate the management and tracking of the commodities. At present, the counting is usually performed manually, and the whole box of commodities (such as wine, beverage and the like) needs to be unpacked, so that the defects of low counting efficiency, high labor cost, easy damage to the integrity of the commodities and the like exist. Aiming at the defects, an Ultra High Frequency-Radio Frequency Identification (UHF-RFID) technology with a multi-tag inventory mechanism is introduced, but in the warehousing and ex-warehousing links of the whole box of commodities, due to the fact that the number of RFID tags is large and the environment is complex, when the tags of local target commodities are inventory, serial reading is easy to occur, and therefore the accuracy rate of tag inventory is low.

Disclosure of Invention

The embodiment of the application provides a multi-label checking method, electronic equipment and a storage medium, which can avoid label serial reading and improve the accuracy of multi-label checking.

In a first aspect, an embodiment of the present application provides a multi-tag inventory method, including:

acquiring a plurality of label information at each frequency point of the ultrahigh frequency electronic label frequency band by adopting a preset power value, wherein the label information comprises target label information and serial reading label information;

performing signal intensity detection on each label to obtain a signal intensity value of each label;

carrying out weighted calculation on the signal intensity value according to a preset weighting rule to obtain a weighted signal intensity value;

and filtering the serial reading label information according to a preset first signal intensity threshold value and a weighted signal intensity value.

In a second aspect, embodiments of the present application provide an electronic device, which includes a memory, a processor, and a program stored in the memory and executable on the processor, and when the program is executed by the processor, the multi-tag inventory method of some embodiments of the first aspect of the present application is implemented.

In a third aspect, embodiments of the present application provide a storage medium for a computer-readable storage, where the storage medium stores one or more programs, and the one or more programs are executable by one or more processors to implement the multi-tag inventory method of some embodiments of the first aspect of the present application.

The embodiment of the application comprises the following steps: acquiring a plurality of label information at each frequency point of the ultrahigh frequency electronic label frequency band by adopting a preset power value; performing signal intensity detection on each label to obtain a signal intensity value of each label; carrying out weighted calculation on the signal intensity value according to a preset weighting rule to obtain a weighted signal intensity value; and filtering the serial reading label information according to a preset first signal intensity threshold value and a weighted signal intensity value. According to the method and the device, the signal intensity value of each label is weighted and calculated, and then the weighted signal intensity value of each label is compared with the signal intensity threshold value, target label information and string reading label information can be distinguished, label string reading is avoided, and the accuracy of multi-label counting is improved.

Additional features and advantages of the application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the application. The objectives and other advantages of the application may be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.

Drawings

Fig. 1 is a flow chart of a multi-tag inventory method according to an embodiment of the present application;

FIG. 2 is a flowchart of one embodiment of step S130 in FIG. 1;

FIG. 3 is a flowchart of another embodiment of step S130 in FIG. 1;

FIG. 4 is a flowchart of one embodiment of step S140 of FIG. 1;

FIG. 5 is a flowchart of another embodiment of step S140 in FIG. 1;

fig. 6 is a flowchart of a multi-tag inventory method according to another embodiment of the present application.

Detailed Description

The conception and the resulting technical effects of the present application will be clearly and completely described below in conjunction with the embodiments to fully understand the objects, features and effects of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, and not all embodiments, and other embodiments obtained by those skilled in the art without inventive efforts based on the embodiments of the present application belong to the protection scope of the present application.

It should be noted that, although a logical order is illustrated in the flowcharts, in some cases, the steps illustrated or described may be performed in an order different from that in the flowcharts. The terms first, second and the like in the description and in the claims, and the drawings described above, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. In the description of the embodiments of the present application, if "a number" is referred to, it means one or more, if "a plurality" is referred to, it means two or more, if "greater than", "less than" or "more than" is referred to, it is understood that the number is not included, and if "greater than", "lower" or "inner" is referred to, it is understood that the number is included.

The methods disclosed in embodiments of the present application include one or more steps or actions for achieving the methods. The method steps and/or actions may be interchanged with one another without departing from the scope of the claims. In other words, unless a specific order of steps or actions is specified, the order and/or use of specific steps and/or actions may be modified without departing from the scope of the claims.

Radio Frequency Identification (RFID) technology implements reading and writing of an electronic tag and communication by electromagnetic waves. The RFID system consists of a Reader, an electronic Tag and a data management system. In operation of an RFID system, radio frequency energy is transmitted by a reader in an area to form an electromagnetic field, the size of the area being dependent on the transmitted power. Tags within the coverage area of the reader are triggered to transmit data stored therein or to modify data stored therein in accordance with the reader's instructions and can communicate with a computer network via an interface. RFID tags can be classified into different categories, such as Low Frequency (LF), High Frequency (HF), Ultra High Frequency (UHF), and microwave. The defined coverage of the UHF RFID frequency band is different globally, for example: the frequency ranges of the China are 840-844 MHz and 920-924 MHz, the frequency range of the European Union is 865 MHz-868 MHz, the frequency range of the Japan is 952 MHz-954 MHz, the frequency ranges of the hong Kong, Thailand and Singapore are 920 MHz-925 MHz, and the frequency ranges of the United states, Canada, Bodori Ricini, Mexico and south America are 902 MHz-928 MHz. The ultra high frequency radio frequency identification (UHF-RFID) technology has the advantages of capability of reading a plurality of labels at one time, long identification distance, high data transmission speed, high reliability and service life, outdoor severe environment resistance and the like, and can be used for asset management, production line management, supply chain management, warehousing, anti-counterfeiting traceability of various articles (such as tobacco, wine, medicine and the like), retail, vehicle management and the like. The Received Signal Strength Indicator (RSSI), which represents the Strength of a Signal in a wireless network, decays with increasing distance, typically being a negative value, with values closer to zero indicating higher Signal strengths.

In retail and storage, the labels of the commodities are checked by using an ultra high frequency radio frequency identification technology (UHF-RFID), and when the labels of local target commodities are checked, cross reading is easy to occur, so that the accuracy rate of label checking is low. For example, when carrying out multi-label checking on wine commodities, need to carry out the checking to many casees of wine and many bottles of wine in the same case, the label is located the body of beverage bottle, and scanning equipment scans in the direction perpendicular with the bottle top of beverage bottle, because RFID label is more, the cluster reads easily to lead to the lower, the not enough of reliability of rate of accuracy of checking.

Based on this, the embodiment of the application provides a multi-label checking method, an electronic device and a storage medium, which can avoid label serial reading and improve the accuracy of multi-label checking.

In a first aspect, referring to fig. 1, an embodiment of the present application provides a multi-tag inventory method, including the following steps:

s110, acquiring a plurality of label information at each frequency point of the ultrahigh frequency electronic label frequency band by adopting a preset power value;

s120, performing signal intensity detection on each label to obtain a signal intensity value of each label;

s130, carrying out weighted calculation on the signal intensity value according to a preset weighting rule to obtain a weighted signal intensity value;

s140, filtering the serial reading label information according to a preset first signal intensity threshold value and a weighted signal intensity value.

Step S110, taking the 920-924 MHz ultrahigh frequency electronic tag frequency band specified in china as an example, as shown in table 1, starting from the 920.625MHz frequency point, dividing the frequency band into 16 frequency points by a step value of 0.25MHz, and performing tag inventory at the 16 frequency points respectively by using a preset power value. Due to the complexity of the environment where the tag is located, the tag may not be sensitive to the response of some frequency points, but the response of some frequency points is relatively good, and in order to ensure that the tag can be checked as much as possible, the tag checking needs to be performed at each frequency point of the frequency band one by one. In some embodiments, the label checking is performed at each frequency point of the UHF electronic label frequency band by adopting a plurality of preset power values in the order of the power values from small to large. The power value can be set according to actual scenes, and the power value range can be adjusted according to requirements in different environments. In some embodiments, the power value ranges from 20 dB to 28 dB.

TABLE 1

In some embodiments, the label checking is performed at each frequency point of the UHF electronic label frequency band by adopting a plurality of preset power values in the order of the power values from small to large. Performing label checking according to the sequence of the power values from small to large, wherein the smaller the power value is, the smaller the possibility of serial reading is, but the full label cannot be recorded by adopting the small power value; the larger the power value is, the more possible the disc is full-label, but the phenomenon of serial reading may occur by using a high power value, so that label counting needs to be performed in the order of the power values from small to large.

And step S120, sequentially checking the labels at each frequency point according to the sequence of the power values from small to large by adopting a preset power value to obtain a plurality of labels, and detecting the signal strength of each checked label to obtain the signal strength value (RSSI) of each label. Firstly, label checking is carried out at each frequency point by adopting a small power value, so that label serial reading is avoided; and sequentially adopting the increasing power value to perform label checking at each frequency point to obtain labels which are as complete as possible, so as to avoid label missing.

In other embodiments, referring to fig. 2, step S130 includes the steps of:

s210, recording the number of times that each label information is checked;

s220, calculating to obtain an average signal intensity value according to the number of times that each label information is checked and the signal intensity value;

and S230, carrying out weighted calculation on the average signal intensity value according to a preset weighting rule to obtain a weighted signal intensity value.

When the tag is checked, the scanning device is moved or due to environmental factors, the RSSI value of the tag detected changes within a certain range, and deviation easily occurs, thereby affecting the judgment of the result. The average value can be used for smoothing fluctuation, and the accuracy of the measured RSSI value is improved. Therefore, when the RSSI value is weighted and calculated, the accuracy of label judgment can be improved by adopting the average RSSI value. Polling each frequency point of the whole frequency band under a certain power value, acquiring tag information, recording the number of times TagNumber that each tag information is checked, accumulating the detected RSSI value of each tag to obtain an RSSI accumulated value TagSSIAccumvalue corresponding to each tag, and further calculating to obtain an average RSSI value PowerX _ RSSIAveragevalue of the tag information checked under a certain power value, wherein the average RSSI value is TagSSIAccumvalue/TagNumber.

The scanning device may be a Mobile phone, a tablet Computer, a desktop, a laptop, a handheld Computer, a notebook, an Ultra-Mobile Personal Computer (UMPC), a netbook, a cellular phone, a Personal Digital Assistant (PDA), an Augmented Reality (AR) \\ Virtual Reality (VR) device, etc. with a scanning function.

In some embodiments, referring to fig. 3, step S130 includes the following specific steps:

s310, calculating the product of the signal intensity value and a preset first weighting coefficient to obtain a calculation result;

and S320, adding the calculation result with a preset second weighting coefficient to obtain a weighted signal strength value.

Calculating a weighted RSSI value TagRSWeightedValue according to the RSSI value of each tag measured under a certain power value, wherein the weighting rule is as follows: (1) the smaller the power value is, the smaller the possibility of serial reading is, the smaller the power value is, the label counting is performed by adopting the small power value, and the probability that the counted label information is the target label information is higher, so that a higher weighting coefficient can be set; (2) the label is checked by adopting a high-power value, so that the label can be checked as much as possible, but label information beside a target label can be read in a serial mode, namely the probability that the checked label information is the serial read label information is relatively high, and a small weighting coefficient needs to be set; (3) the power value is gradually increased, and the corresponding weighting coefficient is gradually decreased, namely the weighting coefficient is in negative correlation with the power value, and the weighting coefficient can be adjusted according to different environments. With the increment of the power value, a descending weighting coefficient is set, under the condition that the label can be completely read, the weighting RSSI value is obtained through the calculation of the weighting coefficient, and the difference value between the weighted RSSI value corresponding to the serial reading label information and the weighted RSSI value corresponding to the target label information is increased along with the increment of the power value, so that the serial reading label information and the target label information can be distinguished, and the accuracy and the reliability of label inventory are improved.

In some embodiments, the weighted RSSI values are calculated using the weighted formula of equation (1):

Y＝A*RSSI+C (1)

wherein Y represents a weighted RSSI value, RSSI represents an RSSI value detected at a certain power value, a represents a first weighting coefficient, and C represents a second weighting coefficient. In some embodiments, the first weighting factor and the second weighting factor are both inversely related to the power value. In other embodiments, when the value range of the power value is 20-28 dB, the first weighting coefficient and the second weighting coefficient that are correspondingly set are shown in table 2. In other embodiments, each frequency point is polled at a certain power value, an average RSSI value is calculated according to the RSSI value obtained by detection, and the average RSSI value is multiplied by a first weighting coefficient to obtain a calculation result; and adding the calculation result and the second weighting coefficient to obtain a weighted RSSI value. Under a certain power value, the distance between the tags serially read beside the target tag is relatively far, and the measured RSSI value is generally small, but the RSSI value measured by the target tag is also small due to shielding or other reasons, so that the accuracy of the judgment result is not high when the RSSI value detected once is adopted for serial reading judgment. The average RSSI value is calculated according to the RSSI values of different frequency points, so that the error of single detection can be reduced, and the reliability of serial reading judgment is improved.

TABLE 2

Power level (dB)	Weighting coefficient
		20	A＝2.0，C＝20
21	A＝1.8，C＝18
		22	A＝1.6，C＝16
23	A＝1.4，C＝14
		24	A＝1.2，C＝12
25	A＝1.0，C＝10
		26	A＝0.8，C＝8
27	A＝0.6，C＝6
		28	A＝0.4，C＝4

In some embodiments, referring to fig. 4, step S140 includes the following specific steps:

s410, comparing the first signal intensity threshold value with the weighted signal intensity value, and if the weighted signal intensity value is smaller than the first signal intensity threshold value, executing the step S420; if the weighted signal strength value is not less than the first signal strength threshold, performing step S430;

s420, labeling the checked label information as serial reading label information and filtering the serial reading label information;

and S430, marking the checked label information as target label information and recording the number of the target label information.

Determining a first signal strength Threshold, placing a commodity with known label information in a certain distance range of the to-be-detected commodity, reading an RSSI value of the commodity with the known label information when performing label checking on the to-be-detected commodity, and performing weighted calculation on the RSSI value according to a preset weighting rule to obtain an RSSI Threshold RSSI _ Threshold. In an actual measurement environment, performing label checking on commodities to be measured, wherein the distance between the commodities to be measured is generally larger than 30cm, placing the commodities with known label information in a range of 10-30 cm away from the commodities to be measured, taking the RSSI value of the commodities with the known label information read to be larger than the RSSI value of a serial reading label read in the actual measurement environment, taking the RSSI value of the commodities with the known label information as the maximum RSSI value of the serial reading label, and performing weighted calculation on the maximum RSSI value according to a preset weighting rule to obtain an RSSI Threshold value RSSI _ Threshold. After the first signal strength threshold value is determined, label checking is carried out on the to-be-detected commodity, the RSSI value of the checked label is detected, and the measured RSSI value is weighted and calculated according to a preset weighting rule to obtain a weighted RSSI value. Labeling label information with the weighted RSSI value smaller than a preset RSSI threshold value as serial reading label information; and marking the tag information of which the weighted RSSI value is not less than the RSSI threshold value as target tag information. By comparing the RSSI threshold value with the weighted RSSI value, the information of the serial reading label and the information of the target label can be distinguished, and the accuracy rate of label inventory is improved. And filtering out the label information marked as the serial reading label information, wherein the rest label information is the target label information, and recording the quantity of the target label information, thereby being convenient for checking the quantity of the commodities.

In other embodiments, referring to fig. 5, step S140 includes the steps of:

s510, performing statistical calculation on the weighted signal strength value corresponding to each power value to obtain a statistical calculation result of the weighted signal strength value;

s520, filtering the serial reading label information according to a preset second signal intensity threshold value and a statistical calculation result.

When the labels are checked, the RSSI value of the checked labels is detected, the measured RSSI value is weighted and calculated according to a preset weighting rule to obtain a weighted RSSI value, and the weighted RSSI value is statistically calculated. In some embodiments, the statistical calculation comprises at least one of: accumulated value calculation, average value calculation, variance calculation, standard deviation calculation and average difference calculation. If the weighted RSSI value is subjected to accumulated value calculation to obtain a weighted RSSI accumulated value TagRSIightedAccumvalue, calculating the pre-measured minimum RSSI value by adopting the same calculation rule to obtain a weighted RSSI accumulated threshold value, and comparing the weighted RSSI accumulated threshold value with the weighted RSSI accumulated value. Labeling label information of which the weighted RSSI accumulated value is smaller than a preset RSSI accumulated threshold value as serial read label information; and marking the tag information of which the weighted RSSI accumulated value is not less than the RSSI accumulated threshold value as target tag information. And if the arithmetic mean value calculation is carried out on the weighted RSSI values to obtain a weighted RSSI mean value, calculating the pre-measured minimum RSSI value by adopting the same calculation rule to obtain a weighted RSSI average threshold value, and comparing the weighted RSSI average threshold value with the weighted RSSI mean value. Labeling label information of which the weighted RSSI average value is smaller than a preset RSSI average threshold value as serial reading label information; and marking the tag information of which the weighted RSSI average value is not less than the RSSI average threshold value as target tag information. If the variance calculation is carried out on the weighted RSSI value to obtain a weighted RSSI variance value, the same calculation rule is adopted to calculate the pre-measured minimum RSSI value to obtain a weighted RSSI variance threshold value, and the weighted RSSI variance threshold value and the weighted RSSI variance value are compared. Labeling label information of which the weighted RSSI variance value is smaller than a preset RSSI variance threshold value as serial reading label information; and marking the label information of which the weighted RSSI variance value is not less than the RSSI variance threshold value as target label information. If the weighted RSSI value is subjected to standard deviation calculation to obtain a weighted RSSI standard deviation value, calculating the pre-measured minimum RSSI value by adopting the same calculation rule to obtain a weighted RSSI standard deviation threshold value, and comparing the weighted RSSI standard deviation threshold value with the weighted RSSI standard deviation value. Labeling label information of which the weighted RSSI standard deviation value is smaller than a preset RSSI standard deviation threshold value as serial reading label information; and marking the tag information of which the weighted RSSI standard deviation value is not less than the RSSI standard deviation threshold value as target tag information. If the weighted RSSI value is subjected to average difference calculation to obtain a weighted RSSI average difference value, calculating the minimum RSSI value measured in advance by adopting the same calculation rule to obtain a weighted RSSI average difference threshold value, and comparing the weighted RSSI average difference threshold value with the weighted RSSI average difference value. Labeling label information of which the weighted RSSI average difference value is smaller than a preset RSSI average difference threshold value as serial reading label information; and marking the label information of which the weighted RSSI average difference value is not less than the RSSI average difference threshold value as target label information. In other embodiments, multiple calculation methods in the statistical calculation method may be adopted to perform calculation respectively, so as to obtain multiple determination results, and the determination results may be optimized by inspecting each determination result, thereby improving the accuracy of label checking.

In some embodiments, referring to fig. 6, before performing tag inventory, a power table and a frequency table are provided, the power table is used for recording each power point in a certain value range, and the frequency table is used for recording each frequency point in a certain frequency band. Polling the power meter, polling the frequency meter at each power value. Performing label checking under a certain power value, acquiring checked labels, detecting the RSSI value of each label, recording the times of checking each label, judging whether the polling of the frequency table is finished or not, and if not, continuing to perform label checking under the frequency points which are not polled; and if the polling is finished, calculating the average RSSI value of each label, and carrying out weighted calculation on the average RSSI value according to a preset weighting rule to obtain the weighted RSSI value of each label. Judging whether the polling of the power meter is finished or not, if not, continuously polling the frequency meter under the power value which is not polled, and checking the label; if polling is complete, the weighted RSSI values for each tag at different power values are stored. And performing accumulation calculation on the weighted RSSI values under different power values to obtain a weighted RSSI accumulated value of each tag. Comparing the weighted RSSI accumulated value TagRSWeightedAccumvalue with a preset weighted RSSI accumulated Threshold value RSSI _ Threshold, and if the TagRSWeightedAccumvalue is less than RSSI _ Threshold, marking the checked label as a serial reading (misreading) label and filtering the serial reading label; if TagRSIightedAccumValue > is RSSI _ Threshold, label the checked tag as the target tag and record the number of the target tags.

The electronic device may include, for example, at least one of a smart phone, a tablet, a Personal Computer (PC), a mobile phone, a video phone, an e-book reader, a desktop PC, a laptop PC, a netbook, a computer, a workstation, a server, a Personal Digital Assistant (PDA), a Portable Multimedia Player (PMP), an MPEG-1 audio layer 3(MP3) Player, a mobile medical device, a camera, and a wearable device. The wearable Device may include at least one of an accessory type (e.g., watch, ring, bracelet, foot chain, necklace, glasses, contact lens, or Head-Mounted Device (HMD)), a fabric or garment integration type (e.g., electronic garment), a body-Mounted type (e.g., skin pad or tattoo), and a bio-implantable type (e.g., implantable circuitry).

In the electronic device of the embodiment of the present Application, the Processor may be a Central Processing Unit (CPU), or may be other general-purpose processors, Digital Signal Processors (DSP), Application Specific Integrated Circuits (ASIC), Field-Programmable Gate arrays (FPGA) or other Programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, and the like. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, the processor being the control center for the operable device of a multi-tag inventory method, various interfaces and lines connecting the various parts of the operable device of the overall multi-tag inventory method.

The memory may be used to store computer programs and/or modules, and the processor may implement the various functions of the executable device of the multi-tag inventory method by executing or executing the computer programs and/or modules stored in the memory and invoking the data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.

It should be understood that all or some of the steps of the methods, apparatuses, functional modules/units in the devices disclosed in the above embodiments may be implemented as software, firmware, hardware, and suitable combinations thereof.

In a hardware implementation, the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed by several physical components in cooperation. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term "computer storage media" includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as is well known to those of ordinary skill in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by a computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as known to those skilled in the art.

The embodiments of the present application have been described in detail with reference to the drawings, but the present application is not limited to the embodiments, and various changes can be made within the knowledge of those skilled in the art without departing from the gist of the present application. Furthermore, the embodiments and features of the embodiments of the present application may be combined with each other without conflict.

Claims

1. The multi-label checking method is characterized by comprising the following steps:

acquiring a plurality of label information at each frequency point of an ultrahigh frequency electronic label frequency band by adopting a preset power value, wherein the label information comprises target label information and serial reading label information;

performing weighted calculation on the signal intensity value according to a preset weighting rule to obtain a weighted signal intensity value;

and filtering the information of the serial reading label according to a preset first signal intensity threshold value and the weighted signal intensity value.

2. The multi-tag inventory method according to claim 1, wherein the obtaining of the plurality of tag information at each frequency point of the uhf electronic tag frequency band using the preset power value includes:

and acquiring a plurality of label information at each frequency point of the ultrahigh frequency electronic label frequency band by adopting a plurality of preset power values according to the sequence of the power values from small to large.

3. The multi-tag inventory method according to claim 1 or 2, wherein the performing a weighted calculation on the signal strength value according to a preset weighting rule to obtain a weighted signal strength value includes:

recording the number of times each piece of label information is checked;

calculating to obtain an average signal intensity value according to the number of times that each piece of label information is checked and the signal intensity value;

and performing weighted calculation on the average signal intensity value according to a preset weighting rule to obtain a weighted signal intensity value.

4. The multi-tag inventory method according to claim 1 or 2, wherein the performing a weighted calculation on the signal strength value according to a preset weighting rule to obtain a weighted signal strength value includes:

calculating the product of the signal intensity value and a preset first weighting coefficient to obtain a calculation result;

and adding the calculation result and a preset second weighting coefficient to obtain the weighted signal intensity value.

5. The multi-tag inventory method of claim 4, wherein the first weighting factor and the second weighting factor are both inversely related to the power value.

6. The multi-tag inventory method of claim 1 or 2, wherein the filtering of the serial read tag information according to the preset first signal strength threshold and the weighted signal strength value comprises:

comparing the first signal strength threshold value to the weighted signal strength value;

if the weighted signal intensity value is smaller than the first signal intensity threshold value, labeling the checked label information as the read-string label information and filtering the read-string label information.

7. The method for multi-tag inventory of claim 2, wherein the filtering of the serial read tag information according to the preset first signal strength threshold and the weighted signal strength value comprises:

performing statistical calculation on the weighted signal intensity value corresponding to each power value to obtain a statistical calculation result of the weighted signal intensity value;

and filtering the serial reading label information according to a preset second signal intensity threshold value and the statistical calculation result.

8. The multi-label inventory method of claim 7, wherein the statistical calculations include at least one of: accumulated value calculation, average value calculation, variance calculation, standard deviation calculation and average difference calculation.

9. Electronic device, characterized in that it comprises a memory, a processor and a program stored on said memory and executable on said processor, said program, when executed by said processor, implementing a multi-tag inventory method according to any one of claims 1 to 8.

10. A storage medium for a computer-readable storage, the storage medium storing one or more programs, the one or more programs being executable by one or more processors to implement the multi-tag inventory method of any of claims 1 to 8.