A method and system for equipment area positioning and identification based on RFID technology

Abstract

The present invention relates to the field of positioning and identification technology, and in particular to a method and system for positioning and identifying equipment areas based on RFID technology. The method comprises the following steps: attaching an RFID tag to each piece of equipment cargo in the equipment area and using an RFID reader to read the RFID tag in real time to obtain RFID tag identification data of the equipment area cargo; using a display screen on the side of the equipment area to perform compartment positioning, identification and counting of designated equipment cargo to obtain the RFID tag counting result of the designated cargo; using a video camera to perform cargo status video capture and video cargo occlusion calibration counting to obtain the video frame counting result of the designated cargo; performing double counting verification based on the RFID tag counting result of the designated cargo and the video frame counting result of the designated cargo, and performing positioning reminder response operations on the corresponding designated compartment area. The present invention can realize rapid positioning and accurate identification of medical equipment cargo.

Description

Technical Field

[0001] The present invention relates to the field of positioning and identification technology, and in particular to an equipment area positioning and identification method and system based on RFID technology. Background Art

[0002] Effective equipment area positioning and identification methods can improve the efficiency of medical equipment use, reduce the risk of medical equipment loss, and improve hospital operation management. In recent years, the emergence of radio frequency identification (RFID) technology has provided a new solution for equipment area positioning and identification. The RFID system can achieve non-contact identification and positioning, overcoming many defects of traditional methods. By attaching RFID tags to medical equipment and deploying RFID readers in the equipment management area, an efficient positioning network is formed. By using the remote identification and real-time video frame data acquisition capabilities of RFID technology, the position of equipment can be automatically identified and located, and the use status of medical equipment can be updated in real time. However, although the existing RFID technology has played a certain role in medical equipment management, its limitations in distance and viewing angle often cause the equipment to be blocked or difficult to identify, resulting in barcode scanning failures and inaccurate video recognition counts, further affecting the identification, positioning and management of designated equipment. Summary of the invention

[0003] Based on this, it is necessary for the present invention to provide an equipment area positioning and identification method and system based on RFID technology to solve at least one of the above technical problems.

[0004] To achieve the above purpose, a method for locating and identifying equipment areas based on RFID technology includes the following steps:

[0005] Step S1: by attaching an RFID tag to each piece of equipment cargo in the equipment area, and using an RFID reader to scan and read the RFID tags in the equipment area in real time, so as to obtain the RFID tag identification data of the equipment area cargo; based on the RFID tag identification data of the equipment area cargo, the side display screen of the equipment area is used to perform compartment positioning, identification and counting of the designated equipment cargo corresponding to the user, and obtain the RFID tag counting results of the designated equipment cargo compartment area and the designated cargo corresponding to each designated compartment area;

[0006] Step S2: Use a video camera to capture the cargo status video of the designated equipment cargo compartment area to obtain the designated equipment cargo video image frames corresponding to each designated compartment area; perform video cargo occlusion calibration counting on the corresponding designated equipment cargo based on the designated equipment cargo video image frames corresponding to each designated compartment area to obtain the designated cargo video frame counting results corresponding to each designated compartment area; perform double counting verification based on the designated cargo RFID tag counting results and the designated cargo video frame counting results to obtain the designated cargo double counting verification comparison results;

[0007] Step S3: Based on the double counting verification and comparison results of the designated goods, the side display screen of the equipment area is used to perform a positioning reminder response operation on the corresponding designated compartment area.

[0008] Further, step S1 includes the following steps:

[0009] Step S11: attaching an RFID tag to each piece of equipment cargo in the equipment area to obtain an RFID-labeled equipment cargo;

[0010] Step S12: Use the RFID reader to scan and read the RFID tag corresponding to the RFID-identified equipment cargo in the equipment area in real time to obtain the RFID tag identification data of the equipment area cargo, wherein the RFID tag identification data of the equipment area cargo includes the equipment cargo name, the equipment cargo quantity and the equipment cargo storage compartment location;

[0011] Step S13: Based on the equipment cargo storage compartment position in the equipment area cargo RFID tag identification data, the equipment area side display screen is used to locate and identify the storage compartment of the designated equipment cargo corresponding to the user, and the designated equipment cargo compartment area is obtained;

[0012] Step S14: Based on the designated equipment cargo compartment area and the equipment cargo quantity in the equipment cargo area RFID tag identification data, regional RFID tag counting is performed on the corresponding designated equipment cargo to obtain the designated cargo RFID tag counting result corresponding to each designated compartment area.

[0013] Further, step S2 includes the following steps:

[0014] Step S21: using a video camera to capture the cargo status video of the designated equipment cargo compartment area to obtain the designated equipment cargo video image frame corresponding to each designated compartment area;

[0015] Step S22: performing image denoising processing frame by frame on the video image frames of designated equipment and cargo corresponding to each designated grid area, so as to obtain denoised video image frames of designated cargo corresponding to each designated grid area;

[0016] Step S23: performing frame-by-frame background recognition and cropping processing on the denoised image frames of the designated goods video corresponding to each designated grid area, so as to obtain the background cropped image frames of the designated goods video corresponding to each designated grid area;

[0017] Step S24: performing video cargo occlusion calibration and counting on the corresponding designated equipment cargo based on the corresponding designated cargo video background cropped image frames in each designated compartment area, and obtaining the corresponding designated cargo video frame counting results in each designated compartment area;

[0018] Step S25: performing a double counting verification according to the counting result of the RFID tag of the designated goods and the counting result of the video frame of the designated goods to obtain a double counting verification comparison result of the designated goods.

[0019] Further, step S23 includes the following steps:

[0020] Step S231: performing image identification and positioning of the farthest non-zero pixel point in the background direction frame by frame for the denoised image frames of the designated goods in each designated grid area, and obtaining the farthest non-zero pixel point position of each video image frame in each background direction in each designated grid area;

[0021] Step S232: Draw the maximum circumscribed rectangle of the designated goods for the farthest non-zero pixel point of each video image frame at each background position in each designated grid area, so as to generate the corresponding maximum circumscribed rectangle border line of the video image frame in each designated grid area;

[0022] Step S233: performing frame-by-frame circumscribed background cropping processing on the designated goods video denoising image frames corresponding to each designated grid area according to the maximum circumscribed rectangular border line of the video image frame corresponding to each designated grid area, so as to obtain the designated goods video background cropped image frames corresponding to each designated grid area.

[0023] Further, step S24 includes the following steps:

[0024] Step S241: Based on the corresponding designated cargo video background cropped image frames in each designated compartment area, the corresponding designated equipment cargo is identified and divided into designated cargo areas, and the designated cargo unobstructed partitions and designated cargo obstructed partitions corresponding to the video image frames in each designated compartment area are obtained;

[0025] Step S242: performing designated goods identification and counting on designated goods unobstructed partitions corresponding to the video image frames in each designated compartment area, and obtaining designated goods unobstructed counting results corresponding to each designated compartment area;

[0026] Step S243: calculating the cargo occlusion degree of the corresponding designated equipment cargo based on the designated cargo occluded partition corresponding to the video image frame in each designated compartment area, so as to obtain the designated cargo occlusion degree corresponding to the occluded partition in each designated compartment area;

[0027] Step S244: Compare and judge the corresponding occlusion degree of the designated goods according to the preset occlusion degree threshold. When the occlusion degree of the designated goods corresponding to the obscured partition in each designated grid area is less than the preset occlusion degree threshold, the unobstructed count result of the designated goods corresponding to the designated grid area is automatically increased by 1 to calibrate the video frame count result; when the occlusion degree of the designated goods corresponding to the obscured partition in each designated grid area is greater than or equal to the preset occlusion degree threshold, no calibration processing is performed until all obscured partitions are judged and the video frame count result of the designated goods corresponding to each designated grid area is obtained.

[0028] Further, step S243 includes the following steps:

[0029] Based on the blocked partitions of the designated goods corresponding to the video image frames in each designated grid area, the blocked areas of the corresponding designated equipment goods are measured frame by frame, and the sizes of the blocked areas of the designated goods corresponding to the blocked partitions in each designated grid area are obtained;

[0030] Based on the designated cargo obstructed partitions corresponding to the video image frames in each designated grid area, the corresponding designated equipment cargo is inversely calculated for the obstruction angle geometric relationship, so as to obtain the designated cargo obstruction angle corresponding to the obstructed partitions in each designated grid area;

[0031] Based on the designated cargo shielding area size and the designated cargo shielding angle corresponding to the shielded partition in each designated grid area, the cargo shielding degree calculation formula is used to calculate the cargo shielding degree of the corresponding designated cargo shielded partition to obtain the designated cargo shielding degree corresponding to the shielded partition in each designated grid area.

[0032] Furthermore, the calculation formula for the degree of obstruction of the cargo in the area is specifically as follows:

[0033] ;

[0034] In the formula, For the In the specified grid area The specified cargo occlusion degree corresponding to the occluded partition, For the In the specified compartment area The total area size of the area corresponding to the blocked partitions, For the In the specified grid area The size of the designated cargo blocking area corresponding to the blocked partition, For the In the specified compartment area The specified cargo occlusion angle corresponding to the occluded partition, For the In the specified compartment area The occlusion attenuation coefficient corresponding to the occluded partition is: For the In the specified compartment area The blocked partitions correspond to the distance between the specified goods and the observation point. is a small area element, It is the correction factor for the degree of obstruction of the specified cargo.

[0035] Further, step S3 includes the following steps:

[0036] Step S31: judging and analyzing the double counting verification and comparison results of the designated goods. If the double counting verification and comparison result of the designated goods is that the RFID tag count is equal to the video frame count, the side display screen of the equipment area is used to confirm that the corresponding designated compartment area count is consistent, so as to perform the corresponding equipment area positioning access operation;

[0037] Step S32: If the result of the double count verification and comparison of the designated goods is that the RFID tag count is greater than or less than the video frame count, the side display screen of the equipment area is used to confirm that the count of the corresponding designated compartment area is inconsistent, and an abnormal ratio evaluation calculation is performed based on the RFID tag count and the video frame count to obtain the abnormal ratio of the designated goods count in the compartment area;

[0038] Step S33: Based on the abnormal ratio of the goods count in the designated compartment area, the display screen on the side of the equipment area is used to perform a count abnormality reminder response review operation on the corresponding designated compartment area.

[0039] Further, step S33 includes the following steps:

[0040] If the abnormal ratio of the designated cargo count in the compartment area is positive, the display screen on the side of the equipment area is used to record and mark that the corresponding designated equipment cargo has a visual angle occlusion abnormality in the designated compartment area, so as to respond to the generation of the compartment LED abnormal flashing control instruction, and the compartment LED abnormal flashing control instruction is applied to the LED lights in the designated compartment area to flash and light up to remind the operator to perform the corresponding compartment designated cargo occlusion review operation;

[0041] If the abnormal ratio of the count of designated goods in the compartment area is negative, the side display screen of the equipment area will be used to record and mark the abnormal problem that the RFID tag of the corresponding designated equipment goods in the designated compartment area has not been read, in response to generating a compartment sound indication abnormality control instruction, and the compartment sound indication abnormality control instruction will be applied to the sound indicator in the designated compartment area to sound and remind the operator to perform the corresponding compartment designated goods RFID tag review operation.

[0042] Furthermore, the present invention also provides an equipment area positioning and identification system based on RFID technology, which is used to execute the equipment area positioning and identification method based on RFID technology as described above, and the equipment area positioning and identification system based on RFID technology includes:

[0043] The compartment positioning RFID tag counting module is used to attach an RFID tag to each piece of equipment cargo in the equipment area, and use the RFID reader to scan and read the RFID tags in the equipment area in real time to obtain the RFID tag identification data of the equipment area cargo; based on the RFID tag identification data of the equipment area cargo, the side display screen of the equipment area is used to perform compartment positioning, identification and counting of the designated equipment cargo corresponding to the user, so as to obtain the RFID tag counting results of the designated equipment cargo compartment area and the designated cargo corresponding to each designated compartment area;

[0044] The designated equipment cargo double counting verification module is used to use a video camera to capture the cargo status video of the designated equipment cargo compartment area to obtain the designated equipment cargo video image frames corresponding to each designated compartment area; based on the designated equipment cargo video image frames corresponding to each designated compartment area, the corresponding designated equipment cargo is subjected to video cargo occlusion calibration counting to obtain the designated cargo video frame counting results corresponding to each designated compartment area; double counting verification is performed according to the designated cargo RFID tag counting results and the designated cargo video frame counting results, thereby obtaining the designated cargo double counting verification comparison results;

[0045] The compartment area counting positioning reminder response module is used to perform positioning reminder response operations on the corresponding designated compartment area based on the double counting verification and comparison results of the designated goods using the side display screen of the equipment area.

[0046] Beneficial effects of the present invention:

[0047] 1. The equipment area positioning and identification method based on RFID technology proposed in the present invention, compared with the prior art, has the beneficial effect that by adding RFID tags to each piece of equipment cargo in the equipment area, the automatic management of equipment cargo can be effectively realized. RFID (radio frequency identification) technology has the characteristics of non-contact, fast and efficient, making the identification and tracking of equipment cargo more convenient and accurate. Each RFID tag carries unique identification information, which can ensure that each piece of equipment cargo has a unique identity in the entire cargo management process, making the inventory management, allocation and use of the equipment area clear at a glance. Among them, RFID tags can store more abundant information, such as production date, shelf life, usage status, etc., to help managers to comprehensively monitor and manage equipment cargo. By using an RFID reader to scan and read the corresponding RFID tags in the equipment area in real time, the real-time status and information of the cargo in the equipment area can be obtained instantly. The automation of this process makes the traditional manual verification and recording methods obsolete, effectively reducing time and labor costs. Through high-frequency scanning, managers can grasp the quantity, name and storage location of equipment cargo in real time to ensure the accuracy and timeliness of information. At the same time, by using the equipment area side display screen to locate and count the designated equipment goods corresponding to the user based on the equipment area cargo RFID tag identification data, it is helpful to realize the accurate management and monitoring of equipment goods. Through this process, the management system can quickly and accurately count the specific number of equipment goods in each compartment area, reducing the errors and omissions in traditional manual counting. The automated counting function can ensure that accurate numbers are always maintained in inventory management, thereby reducing the phenomenon of excessive inventory or inventory shortages caused by information asymmetry. This real-time regional counting function enables managers to quickly identify areas that do not meet inventory standards and provides basic data guarantee for the subsequent double counting verification process. Then, by using a video camera to capture the cargo status video of the designated equipment cargo compartment area, the real-time status of the designated goods in each designated compartment area can be obtained. The key to this process is mainly reflected in the timeliness and comprehensiveness of the designated cargo information acquisition. Through continuous video monitoring, the changes in the designated cargo can be dynamically recorded, so that the subsequent image analysis can be more accurate and effective, and the intelligent level of medical cargo storage management can be improved. By performing video cargo occlusion calibration and counting on the corresponding designated equipment and cargo based on the corresponding designated equipment and cargo video image frames in each designated grid area, the cargo occlusion counting problem in complex environments can be effectively solved, which is reflected in the ability to realize dynamic monitoring of different angles and occlusion conditions to ensure that the designated cargo that does not meet the occlusion standards can be accurately counted. By analyzing the video frames, it is possible to determine which designated cargo is not counted due to occlusion and make corresponding corrections, which can improve the accuracy of the counting and solve the problem of equipment being blocked or difficult to identify.By performing double counting verification based on the counting results of the designated goods RFID tags and the counting results of the designated goods video frames, the accuracy and security of the management of designated goods can be greatly enhanced. The key to this step is that through the double verification mechanism, the errors caused by a single counting method can be effectively reduced and the reliability of the data can be improved. RFID technology has the ability to quickly identify and batch process, while video counting provides visual verification, which can better enhance the identification, positioning and management process of designated equipment. Finally, by judging and analyzing the double counting verification and comparison results of the designated goods after the previous verification and comparison, if the RFID tag count is consistent with the video frame count, the result is confirmed through the side display screen of the equipment area, which can ensure the credibility of the data. The key to this process is to eliminate the errors caused by a single counting method and improve management efficiency and decision-making accuracy. By confirming the consistency of the count in real time, managers can immediately perform the positioning and access operations of the equipment area, optimize the allocation and storage operations of goods, and reduce the risk of mis-access or omission. If the RFID tag count is inconsistent with the video frame count, the fact of the count inconsistency will be confirmed through the side display screen of the equipment area, and the count abnormality reminder response review operation will be carried out using the side display screen of the equipment area to quantify the count abnormality ratio and automatically issue an abnormal reminder based on its specific size. The operator can timely understand the current status of the cargo counting and conduct further verification. The key to this mechanism is that it significantly reduces the risk of human error, enhances the transparency of cargo management, and ensures the safety and availability of medical equipment cargo, thereby effectively solving abnormal problems such as failed barcode label scanning of cargo in the equipment area and inaccurate video recognition.

[0048] 2. The equipment area positioning and identification system based on RFID technology proposed in the present invention is composed of a compartment positioning RFID tag counting module, a designated equipment and cargo double counting verification module, and a compartment area counting and positioning reminder response module. It can realize any equipment area positioning and identification method based on RFID technology described in the present invention, and is used to combine the operations between computer programs running on each module to realize the equipment area positioning and identification method based on RFID technology. The internal structures of the system cooperate with each other, which can greatly reduce duplication of work and manpower investment, and can quickly and effectively provide a more accurate and efficient equipment area positioning and identification process based on RFID technology, thereby simplifying the operation process of the equipment area positioning and identification system based on RFID technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments thereof made with reference to the following drawings:

[0050] Figure 1A schematic diagram of the steps of the equipment area positioning and identification method based on RFID technology of the present invention;

[0051] Figure 2 for Figure 1 Detailed step flow diagram of step S1;

[0052] Figure 3 for Figure 1 Detailed step flow chart of step S2 in FIG. DETAILED DESCRIPTION

[0053] The technical method of the present invention is described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

[0054] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0055] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0056] To achieve this, please refer to Figures 1 to 3 The present invention provides an equipment area positioning and identification method based on RFID technology, the method comprising the following steps:

[0057] Step S1: by attaching an RFID tag to each piece of equipment cargo in the equipment area, and using an RFID reader to scan and read the RFID tags in the equipment area in real time, so as to obtain the RFID tag identification data of the equipment area cargo; based on the RFID tag identification data of the equipment area cargo, the side display screen of the equipment area is used to perform compartment positioning, identification and counting of the designated equipment cargo corresponding to the user, and obtain the RFID tag counting results of the designated equipment cargo compartment area and the designated cargo corresponding to each designated compartment area;

[0058] Step S2: Use a video camera to capture the cargo status video of the designated equipment cargo compartment area to obtain the designated equipment cargo video image frames corresponding to each designated compartment area; perform video cargo occlusion calibration counting on the corresponding designated equipment cargo based on the designated equipment cargo video image frames corresponding to each designated compartment area to obtain the designated cargo video frame counting results corresponding to each designated compartment area; perform double counting verification based on the designated cargo RFID tag counting results and the designated cargo video frame counting results to obtain the designated cargo double counting verification comparison results;

[0059] Step S3: Based on the double counting verification and comparison results of the designated goods, the side display screen of the equipment area is used to perform a positioning reminder response operation on the corresponding designated compartment area.

[0060] In the embodiment of the present invention, please refer to Figure 1 FIG. 1 is a schematic diagram of the steps of the equipment area positioning and identification method based on RFID technology of the present invention. In this example, the equipment area positioning and identification method based on RFID technology includes the following steps:

[0061] Step S1: by attaching an RFID tag to each piece of equipment cargo in the equipment area, and using an RFID reader to scan and read the RFID tags in the equipment area in real time, so as to obtain the RFID tag identification data of the equipment area cargo; based on the RFID tag identification data of the equipment area cargo, the side display screen of the equipment area is used to perform compartment positioning, identification and counting of the designated equipment cargo corresponding to the user, and obtain the RFID tag counting results of the designated equipment cargo compartment area and the designated cargo corresponding to each designated compartment area;

[0062] In an embodiment of the present invention, a corresponding RFID tag is attached to each piece of equipment and cargo in the corresponding medical equipment area in advance, so as to select a suitable type of RFID tag to ensure that it has sufficient storage capacity to record relevant information of the equipment and cargo, and to print the unique identification, name and other necessary information of the equipment and cargo on the RFID tag by using a label printer, and to firmly attach the tag to each piece of equipment and cargo using a special RFID adhesive or fixing tool to ensure that each piece of equipment and cargo has a unique RFID identification, and to scan and read the RFID tags of the corresponding equipment and cargo in the equipment area in real time by using an RFID reader / writer, so as to set the RFID reader / writer at a fixed position in the equipment area to ensure that it covers the RFID tag reading range of the entire area, and during the scanning process, the reader / writer interacts with the tag through wireless signals to obtain the data stored in the tag in real time, and the data includes information such as the name, quantity and storage compartment location of the equipment and cargo, thereby obtaining the RFID tag identification data of the equipment area cargo. At the same time, by combining the equipment cargo storage compartment position obtained by the previous scan and reading, the side display screen of the equipment area is used to locate and identify the storage compartment of the designated equipment cargo corresponding to the user, so as to extract its information by querying the storage compartment position related to the equipment cargo name input by the user in the database, and dynamically display the storage location and related details of the designated equipment cargo on the screen, such as the storage compartment number and the visual diagram of the area, and after confirming the compartment area of ​​the designated equipment cargo, the regional RFID tag count of the corresponding designated equipment cargo is performed based on the equipment cargo number in the area and the RFID tag identification data of the equipment area cargo, so as to configure the RFID reader to scan again in the designated area, collect the identification data of all RFID tags in the area, and automatically count the specific number of RFID tag designated cargo identified in the area, and compare it with the equipment cargo number stored in the database, and generate the specific count number of RFID tags corresponding to the designated cargo in each designated compartment area, so as to ensure the accuracy of the cargo inventory, and finally obtain the RFID tag counting result of the designated cargo corresponding to each designated compartment area.

[0063] Step S2: Use a video camera to capture the cargo status video of the designated equipment cargo compartment area to obtain the designated equipment cargo video image frames corresponding to each designated compartment area; perform video cargo occlusion calibration counting on the corresponding designated equipment cargo based on the designated equipment cargo video image frames corresponding to each designated compartment area to obtain the designated cargo video frame counting results corresponding to each designated compartment area; perform double counting verification based on the designated cargo RFID tag counting results and the designated cargo video frame counting results to obtain the designated cargo double counting verification comparison results;

[0064] In an embodiment of the present invention, a video camera in the cargo area is used to capture the status of designated cargo in the previously analyzed designated equipment cargo compartment area in real time, wherein the camera needs to be installed at an appropriate height and angle to ensure full coverage of each designated compartment area and to be able to clearly capture all equipment cargo. Shooting parameters such as frame rate and resolution are set by using video acquisition software to ensure that the captured image is clear and detailed. Video image frames are generated by periodic recording to form a dynamic view containing the status of all designated cargo, thereby obtaining the corresponding designated equipment cargo video image frames in each designated compartment area. By using an image processing algorithm to perform frame-by-frame denoising on each designated equipment and cargo video image frame for the captured video image frames, the noise caused by environmental factors (such as light changes and vibrations) is reduced, and frame-by-frame background recognition and cropping processing is performed based on the processed designated cargo video denoising image frames, so as to identify the background part in the video frame and separate it from the foreground (equipment and cargo) by using an image segmentation algorithm (such as background subtraction or color threshold method), and each frame of the video image is cropped to extract the area related to the equipment and cargo, and generate a background cropped image frame. This process ensures that only important cargo information is retained, reducing interference during analysis. At the same time, by combining The video image frames of the designated goods corresponding to each designated compartment area obtained after background cutting are calibrated and counted for the corresponding designated equipment goods in the designated compartment area, so as to identify and count the equipment goods visible in each frame by using image recognition technology, and to train the model to identify different types of equipment goods with the help of machine learning algorithms, and to calibrate the number of equipment goods that may be blocked, so as to ensure that the designated goods that are blocked or not seriously overlapped are accurately counted during counting, and the generated counting results reflect the suspected specific number of the corresponding designated goods in each designated compartment area, so as to obtain the video frame counting results of the designated goods corresponding to each designated compartment area. Then, by combining the video frame counting results of the designated goods obtained by video counting and the RFID tag counting results of the designated goods obtained by RFID tag counting, a double counting verification is performed, so as to verify the video counting results and the RFID counting results one by one through the data comparison algorithm to ensure the consistency of the two data. If inconsistency is found, the abnormality will be recorded and further analyzed to ensure the accuracy and reliability of the number of goods. Through this double verification process, the goods management of the equipment area is strengthened, the authenticity and validity of the inventory data are ensured, and finally the double counting verification and comparison results of the designated goods are obtained.

[0065] Step S3: Based on the double counting verification and comparison results of the designated goods, the side display screen of the equipment area is used to perform a positioning reminder response operation on the corresponding designated compartment area.

[0066] In an embodiment of the present invention, when judging the double counting verification and comparison results of the designated goods obtained by the previous quantitative calculation, the RFID tag count is compared with the video frame count. If the RFID tag count is equal to the video frame count, it means that the count is consistent. At this time, the counting consistency of the designated compartment area is confirmed to the operator by using the side display screen of the equipment area. In a specific implementation, the counting results can be displayed on the display screen in real time through the data display interface to ensure that the operator can quickly obtain information and perform the corresponding equipment area positioning access operation. If the double counting verification and comparison results show that the RFID tag count is greater than or less than the video frame count, it is necessary to confirm that the count of the designated compartment area is inconsistent. At this time, the side display screen of the equipment area will display a warning message of "count inconsistency". At the same time, the side display screen of the equipment area will perform an abnormal ratio evaluation calculation based on the RFID tag count and the video frame count. In a specific operation, the abnormal ratio is calculated using a formula, for example: ((RFID count - video frame count) / video frame count) * 100%, and the result will be displayed on the side display screen so that the operator can understand the current counting abnormality and judge its abnormal ratio. If the comparison judgment is a positive number, the state will be recorded and marked through the side display screen of the equipment area, and it will be pointed out that there is a visual angle occlusion abnormality in the designated compartment area. At this time, an LED abnormal flashing control instruction will be generated in response, and the instruction will be sent to the LED light in the designated compartment area. The LED light will flash at a predetermined frequency to clearly remind the operator that there is an occlusion problem. The operator can observe the flashing light and conduct the occlusion review of the designated goods in the compartment in time; if the comparison judgment is a negative number, the side display screen of the equipment area will be used to record and mark this abnormality, and it will be pointed out that there is an abnormality that the RFID tag is not read in the designated compartment area. At this time, a sound indication abnormal control instruction will be generated in response, and the instruction will be applied to the sound indicator in the designated compartment area. The sound indicator will emit a clear alarm to prompt the operator to conduct a review in time to ensure the accuracy and completeness of all goods.

[0067] Further, step S1 includes the following steps:

[0068] Step S11: attaching an RFID tag to each piece of equipment cargo in the equipment area to obtain an RFID-labeled equipment cargo;

[0069] Step S12: Use the RFID reader to scan and read the RFID tag corresponding to the RFID-identified equipment cargo in the equipment area in real time to obtain the RFID tag identification data of the equipment area cargo, wherein the RFID tag identification data of the equipment area cargo includes the equipment cargo name, the equipment cargo quantity and the equipment cargo storage compartment location;

[0070] Step S13: Based on the equipment cargo storage compartment position in the equipment area cargo RFID tag identification data, the equipment area side display screen is used to locate and identify the storage compartment of the designated equipment cargo corresponding to the user, and the designated equipment cargo compartment area is obtained;

[0071] Step S14: Based on the designated equipment cargo compartment area and the equipment cargo quantity in the equipment cargo area RFID tag identification data, regional RFID tag counting is performed on the corresponding designated equipment cargo to obtain the designated cargo RFID tag counting result corresponding to each designated compartment area.

[0072] As an embodiment of the present invention, refer to Figure 2 As shown, Figure 1 Detailed step flow diagram of step S1 in FIG. 1 , in this embodiment, step S1 includes the following steps:

[0073] Step S11: attaching an RFID tag to each piece of equipment cargo in the equipment area to obtain an RFID-labeled equipment cargo;

[0074] In an embodiment of the present invention, a corresponding RFID tag is attached to each piece of equipment in the corresponding medical equipment area in advance, and a suitable RFID tag type is selected to ensure that it has sufficient storage capacity to record relevant information of the equipment. The unique identification, name and other necessary information of the equipment are printed on the RFID tag by using a label printer, and the label is firmly attached to each piece of equipment using a special RFID adhesive or fixing tool to ensure that the label will not fall off or be damaged during daily operation and transportation. This process ensures that each piece of equipment has a unique RFID identification, and finally obtains RFID-labeled equipment.

[0075] Step S12: Use the RFID reader to scan and read the RFID tag corresponding to the RFID-identified equipment cargo in the equipment area in real time to obtain the RFID tag identification data of the equipment area cargo, wherein the RFID tag identification data of the equipment area cargo includes the equipment cargo name, the equipment cargo quantity and the equipment cargo storage compartment location;

[0076] In an embodiment of the present invention, an RFID reader is used to perform real-time scanning and reading of RFID tags of corresponding equipment goods in an equipment area, so that the RFID reader is set at a fixed position in the equipment area to ensure that it covers the RFID tag reading range of the entire area. During the scanning process, the reader interacts with the tag through a wireless signal to obtain data stored in the tag in real time. The data includes information such as the name, quantity and storage compartment location of the equipment goods, generates goods RFID tag identification data, and transmits it to a central database in real time to form a digital record for subsequent query and analysis, thereby ensuring the timeliness and accuracy of the information, and finally obtaining the equipment area cargo RFID tag identification data, including the equipment cargo name, equipment cargo quantity and equipment cargo storage compartment location.

[0077] Step S13: Based on the equipment cargo storage compartment position in the equipment area cargo RFID tag identification data, the equipment area side display screen is used to locate and identify the storage compartment of the designated equipment cargo corresponding to the user, and the designated equipment cargo compartment area is obtained;

[0078] In an embodiment of the present invention, the storage compartment location of the equipment and cargo obtained by the previous scan is combined to identify and display the storage compartment of the designated equipment and cargo corresponding to the user using the side display screen of the equipment area, so as to extract the information of the storage compartment location related to the equipment and cargo name input by the user by querying the database, and transmit the extracted information to the side display screen, and dynamically display the storage location and related details of the designated equipment and cargo on the screen, such as the storage compartment number and the visual diagram of the area. This process provides the user with clear navigation guidance, so that the user can quickly locate the required equipment and cargo in the equipment area, and finally obtain the designated equipment and cargo compartment area.

[0079] Step S14: Based on the designated equipment cargo compartment area and the equipment cargo quantity in the equipment cargo area RFID tag identification data, regional RFID tag counting is performed on the corresponding designated equipment cargo to obtain the designated cargo RFID tag counting result corresponding to each designated compartment area.

[0080] In an embodiment of the present invention, after confirming the compartment area of ​​the designated equipment goods, the regional RFID tag counting of the corresponding designated equipment goods is performed based on the number of equipment goods in the area and the RFID tag identification data of the equipment area goods, so as to configure the RFID reader to scan again in the designated area, collect the identification data of all RFID tags in the area, and automatically count the specific number of RFID tag designated goods identified in the area, and compare it with the number of equipment goods stored in the database, and generate the specific count number of RFID tags corresponding to the designated goods in each designated compartment area, so as to ensure the accuracy of the goods inventory, and finally obtain the RFID tag counting result corresponding to the designated goods in each designated compartment area.

[0081] Further, step S2 includes the following steps:

[0082] Step S21: using a video camera to capture the cargo status video of the designated equipment cargo compartment area to obtain the designated equipment cargo video image frame corresponding to each designated compartment area;

[0083] Step S22: performing image denoising processing frame by frame on the video image frames of designated equipment and cargo corresponding to each designated grid area, so as to obtain denoised video image frames of designated cargo corresponding to each designated grid area;

[0084] Step S23: performing frame-by-frame background recognition and cropping processing on the denoised image frames of the designated goods video corresponding to each designated grid area, so as to obtain the background cropped image frames of the designated goods video corresponding to each designated grid area;

[0085] Step S24: performing video cargo occlusion calibration and counting on the corresponding designated equipment cargo based on the corresponding designated cargo video background cropped image frames in each designated compartment area, and obtaining the corresponding designated cargo video frame counting results in each designated compartment area;

[0086] Step S25: performing a double counting verification according to the counting result of the RFID tag of the designated goods and the counting result of the video frame of the designated goods to obtain a double counting verification comparison result of the designated goods.

[0087] As an embodiment of the present invention, refer to Figure 3 As shown, Figure 1 Detailed step flow diagram of step S2 in FIG. 1 , in this embodiment, step S2 includes the following steps:

[0088] Step S21: using a video camera to capture the cargo status video of the designated equipment cargo compartment area to obtain the designated equipment cargo video image frame corresponding to each designated compartment area;

[0089] In an embodiment of the present invention, a video camera in the cargo area is used to capture the status of designated cargo in the previously analyzed designated equipment cargo compartment area in real time, wherein the camera needs to be installed at an appropriate height and angle to ensure full coverage of each designated compartment area and to be able to clearly capture all equipment cargo. Shooting parameters such as frame rate and resolution are set by using video acquisition software to ensure that the captured image is clear and detailed. Video image frames are generated by periodic recording to form a dynamic view containing the status of all designated cargo, and finally the designated equipment cargo video image frames corresponding to each designated compartment area are obtained.

[0090] Step S22: performing image denoising processing frame by frame on the video image frames of designated equipment and cargo corresponding to each designated grid area, so as to obtain denoised video image frames of designated cargo corresponding to each designated grid area;

[0091] In the embodiment of the present invention, by using an image processing algorithm to perform frame-by-frame denoising on each designated equipment and cargo video image frame for the captured video image frames, a special image processing tool (such as OpenCV) is used to implement the denoising algorithm, and a median filter or a Gaussian filter and other techniques are used to reduce the noise caused by environmental factors (such as light changes, vibrations). After each frame of the image is denoised, a denoised image frame with higher clarity is generated, ensuring that the subsequent analysis stage can more accurately identify and locate the equipment and cargo, and finally obtain the designated cargo video denoised image frame corresponding to each designated grid area.

[0092] Step S23: performing frame-by-frame background recognition and cropping processing on the denoised image frames of the designated goods video corresponding to each designated grid area, so as to obtain the background cropped image frames of the designated goods video corresponding to each designated grid area;

[0093] In the embodiment of the present invention, the background recognition and cropping process is performed frame by frame based on the processed denoised image frames of the designated cargo video, so that the background part and the foreground (equipment and cargo) in the video frame are identified and separated by using an image segmentation algorithm (such as background subtraction or color threshold method), and each frame of the video image is cropped to extract the area related to the equipment and cargo, and generate a background cropped image frame. This process ensures that only important cargo information is retained, reduces interference during analysis, and improves the accuracy of subsequent processing, and finally obtains the designated cargo video background cropped image frame corresponding to each designated grid area.

[0094] Step S24: performing video cargo occlusion calibration and counting on the corresponding designated equipment cargo based on the corresponding designated cargo video background cropped image frames in each designated compartment area, and obtaining the corresponding designated cargo video frame counting results in each designated compartment area;

[0095] In an embodiment of the present invention, by combining the corresponding designated equipment and cargo in each designated grid area obtained after background cropping, the corresponding designated equipment and cargo therein are calibrated and counted for video occlusion, so that the equipment and cargo visible in each frame are identified and counted by using image recognition technology, and with the help of machine learning algorithms, the model is trained to identify different types of equipment and cargo, and the number of equipment and cargo that may be occluded is calibrated to ensure that the designated cargo that is occluded or not seriously overlapped is accurately counted during counting, and the generated counting result reflects the suspected specific number of the corresponding designated cargo in each designated grid area, and finally the counting result of the designated cargo video frame corresponding to each designated grid area is obtained.

[0096] Step S25: performing a double counting verification according to the counting result of the RFID tag of the designated goods and the counting result of the video frame of the designated goods to obtain a double counting verification comparison result of the designated goods.

[0097] In the embodiment of the present invention, a double counting verification is performed by combining the video frame counting result of the designated goods obtained by video counting and the RFID tag counting result of the designated goods obtained by RFID tag counting, so that the video counting result and the RFID counting result are checked one by one through a data comparison algorithm to ensure the consistency of the two data. If inconsistency is found, the abnormality will be recorded and further analyzed to ensure the accuracy and reliability of the cargo quantity. Through this double verification process, the cargo management of the equipment area is strengthened, the authenticity and validity of the inventory data are ensured, and finally the double counting verification and comparison result of the designated cargo is obtained.

[0098] Further, step S23 includes the following steps:

[0099] Step S231: performing image identification and positioning of the farthest non-zero pixel point in the background direction frame by frame for the denoised image frames of the designated goods in each designated grid area, and obtaining the farthest non-zero pixel point position of each video image frame in each background direction in each designated grid area;

[0100] In an embodiment of the present invention, by processing the denoised video image frames frame by frame in each designated grid area, identifying the background position and the farthest non-zero pixel point in each frame, and analyzing the denoised image by using an edge detection algorithm in an image processing tool (such as OpenCV) to extract the non-zero pixel points in the background area, by traversing each frame, determining the coordinates of the farthest non-zero pixel point in each background position, and recording all the identified farthest non-zero pixel points to provide basic data for subsequent circumscribed rectangle drawing. This process ensures that the positions of equipment and cargo in different background positions are accurately captured, enhances the accuracy of subsequent image processing, and finally obtains the farthest non-zero pixel point position of each video image frame in each designated grid area at each background position.

[0101] Step S232: Draw the maximum circumscribed rectangle of the designated goods for the farthest non-zero pixel point of each video image frame at each background position in each designated grid area, so as to generate the corresponding maximum circumscribed rectangle border line of the video image frame in each designated grid area;

[0102] In an embodiment of the present invention, the maximum circumscribed rectangle of the designated goods is drawn based on the farthest non-zero pixel point previously identified. In each frame of the image, the coordinates of the farthest non-zero pixel point identified are firstly extracted, and then the circumscribed rectangular frame formed by these points is determined by using a geometric calculation method (such as a minimum circumscribed rectangle algorithm), and the rectangular frame is drawn on the original image by using an image processing tool to form a visual boundary line. The maximum circumscribed rectangular frame line of each frame of the image not only identifies the outline of the goods, but also provides a clear guide for the subsequent cutting process, ensuring the accurate positioning of the goods area, and finally drawing and generating the corresponding maximum circumscribed rectangular frame line of the video image frame in each designated grid area.

[0103] Step S233: performing frame-by-frame circumscribed background cropping processing on the designated goods video denoising image frames corresponding to each designated grid area according to the maximum circumscribed rectangular border line of the video image frame corresponding to each designated grid area, so as to obtain the designated goods video background cropped image frames corresponding to each designated grid area.

[0104] In an embodiment of the present invention, the circumscribed background of the designated cargo video denoising image frames corresponding to each designated grid area is cropped frame by frame in combination with the previously generated maximum circumscribed rectangular border lines of the video image frames corresponding to each designated grid area, so that the circumscribed rectangular area of ​​each frame image is cropped by using image processing software, and only the designated cargo area image in the area is retained, and the corresponding background area image is cropped. By setting the cropping frame, the image content in the rectangular frame is automatically cropped to generate a background cropped image frame. This process ensures that only the target equipment cargo is included in the final image, removes the background clutter information, and finally obtains the designated cargo video background cropped image frames corresponding to each designated grid area.

[0105] Further, step S24 includes the following steps:

[0106] Step S241: Based on the corresponding designated cargo video background cropped image frames in each designated compartment area, the corresponding designated equipment cargo is identified and divided into designated cargo areas, and the designated cargo unobstructed partitions and designated cargo obstructed partitions corresponding to the video image frames in each designated compartment area are obtained;

[0107] In the embodiment of the present invention, cargo area recognition and division are performed on the video background cropped image frames obtained after background cropping in each designated grid area, and each frame of the image is processed by using an image segmentation algorithm (such as K-means clustering or region growing method) to divide the image into two areas, namely, unobstructed and obstructed areas. For the unobstructed area, morphological processing is applied to extract clear cargo boundaries to ensure that the recognition result is accurate. For the obstructed area, pixel density analysis is performed to identify the parts with a higher degree of occlusion, and finally, unobstructed partitions of designated cargo and obstructed partitions of designated cargo corresponding to the video image frames in each designated grid area are obtained.

[0108] Step S242: performing designated goods identification and counting on designated goods unobstructed partitions corresponding to the video image frames in each designated compartment area, and obtaining designated goods unobstructed counting results corresponding to each designated compartment area;

[0109] In an embodiment of the present invention, designated goods are identified and counted in unobstructed partitions identified in video image frames in each designated compartment area, so as to use a deep learning model (such as YOLO or SSD) for target detection and accurately identify the specific quantity of unobstructed goods. The model needs to be trained with a previously collected training data set to improve its recognition accuracy. After the recognition is completed, the number of goods in each unobstructed partition is counted to generate a corresponding unobstructed counting result, and finally the corresponding designated goods unobstructed counting result in each designated compartment area is obtained.

[0110] Step S243: calculating the cargo occlusion degree of the corresponding designated equipment cargo based on the designated cargo occluded partition corresponding to the video image frame in each designated compartment area, so as to obtain the designated cargo occlusion degree corresponding to the occluded partition in each designated compartment area;

[0111] In an embodiment of the present invention, a statistical calculation is performed on the occlusion degree of designated equipment and cargo for the occluded partitions in the video image frames within each designated grid area, so that the pixels of the occluded area are counted by using an image analysis tool, and the ratio of the total number of pixels covered by it to the total number of pixels of cargo is calculated. With the help of an edge detection algorithm, the boundary features of the occluded object are analyzed, the specific value of the occlusion degree is determined, and the occlusion degree of each occluded partition is recorded for subsequent comparison and judgment with a threshold value. Finally, a quantitative calculation is performed to obtain the occlusion degree of designated cargo corresponding to the occluded partition in each designated grid area.

[0112] Step S244: Compare and judge the corresponding occlusion degree of the designated goods according to the preset occlusion degree threshold. When the occlusion degree of the designated goods corresponding to the obscured partition in each designated grid area is less than the preset occlusion degree threshold, the unobstructed count result of the designated goods corresponding to the designated grid area is automatically increased by 1 to calibrate the video frame count result; when the occlusion degree of the designated goods corresponding to the obscured partition in each designated grid area is greater than or equal to the preset occlusion degree threshold, no calibration processing is performed until all obscured partitions are judged and the video frame count result of the designated goods corresponding to each designated grid area is obtained.

[0113] In the embodiment of the present invention, a preset occlusion degree threshold is used to compare and judge the occlusion degree of the designated goods obtained by the corresponding quantitative calculation. If it is found that the occlusion degree of the occluded partition is less than the preset threshold, the corresponding unoccluded count result is automatically increased by 1, thereby calibrating the video frame count result; conversely, if the occlusion degree is greater than or equal to the threshold, no calibration processing is performed. This process is executed in a loop until the occlusion degree of all occluded partitions is judged, thereby obtaining the corresponding goods video frame count result, ensuring the accuracy and reliability of the data, and finally obtaining the corresponding designated goods video frame count result in each designated grid area.

[0114] Further, step S243 includes the following steps:

[0115] Based on the blocked partitions of the designated goods corresponding to the video image frames in each designated grid area, the blocked areas of the corresponding designated equipment goods are measured frame by frame, and the sizes of the blocked areas of the designated goods corresponding to the blocked partitions in each designated grid area are obtained;

[0116] In an embodiment of the present invention, the occluded area is measured frame by frame for each occluded partition in the video image frame in each designated grid area, so as to extract the outline of the occluded area by using an image segmentation algorithm (such as threshold segmentation or watershed algorithm), and the number of valid pixels in the occluded area is calculated by using an image processing tool (such as OpenCV), which is then converted into an actual occluded area. By converting the area value with a preset pixel area unit, the size of the designated cargo occlusion area corresponding to each occluded partition is obtained. This process ensures that the occlusion status of the cargo in each area is accurately reflected, and finally the size of the designated cargo occlusion area corresponding to the occluded partition in each designated grid area is obtained.

[0117] Preferably, based on the designated cargo obstructed partitions corresponding to the video image frames in each designated compartment area, the corresponding designated equipment cargo is inversely calculated for the obstruction angle geometric relationship, so as to obtain the designated cargo obstruction angle corresponding to the obstructed partitions in each designated compartment area;

[0118] In an embodiment of the present invention, after completing the measurement of the occlusion area, the geometric relationship of the occlusion angle of the occluded partition is inversely calculated based on the video image frames in each designated grid area, so as to analyze the contour of each occluded area, extract key feature points (such as the vertices of the contour), and use geometric principles to calculate the relative position and posture of the occluded object based on these feature points, thereby deducing its occlusion angle. The angle between adjacent feature points can be calculated with the help of trigonometric functions, and then the occlusion angle corresponding to each occluded partition can be obtained, and finally the designated cargo occlusion angle corresponding to the occluded partition in each designated grid area can be obtained.

[0119] Preferably, based on the size of the designated cargo obstruction area corresponding to the obstructed partition in each designated compartment area and the designated cargo obstruction angle, the cargo obstruction degree of the corresponding designated cargo obstructed partition is calculated using the regional cargo obstruction degree calculation formula to obtain the designated cargo obstruction degree corresponding to the obstructed partition in each designated compartment area.

[0120] In an embodiment of the present invention, a suitable regional cargo obstruction degree calculation formula is constructed by combining the total area size of the area corresponding to the obscured partition, the size of the designated cargo obstruction area corresponding to the obscured partition, the designated cargo obstruction angle corresponding to the obscured partition, the obstruction attenuation coefficient corresponding to the obscured partition, the distance between the designated cargo and the observation point corresponding to the obscured partition, the small area element and related parameters. The cargo obstruction degree of the corresponding designated cargo obscured partition is calculated, and the obstruction area and the obstruction angle are substituted into the formula to calculate the obstruction degree value. The influence of the two can be balanced by the set weight factor to ensure the accuracy and rationality of the calculation, and finally the designated cargo obstruction degree corresponding to the obscured partition in each designated grid area is obtained.

[0121] Furthermore, the calculation formula for the degree of obstruction of the cargo in the area is specifically as follows:

[0122] ;

[0123] In the formula, For the In the specified grid area The specified cargo occlusion degree corresponding to the occluded partition, For the In the specified grid area The total area size of the area corresponding to the blocked partitions, For the In the specified grid area The size of the designated cargo blocking area corresponding to the blocked partition, For the In the specified grid area The specified cargo occlusion angle corresponding to the occluded partition, For the In the specified grid area The occlusion attenuation coefficient corresponding to the occluded partition is: For the In the specified grid area The blocked partitions correspond to the distance between the specified goods and the observation point. is a small area element, It is the correction factor for the degree of obstruction of the specified cargo.

[0124] The present invention obtains a regional cargo obstruction degree calculation formula by using a specific mathematical model and verifying it, which is used to calculate the cargo obstruction degree of the corresponding designated cargo obstructed partition. The regional cargo obstruction degree calculation formula can realize the quantitative evaluation of the obstruction degree of the designated cargo in a specific area. The numeralization of the obstruction degree makes it possible to intuitively compare the obstruction conditions of different areas and different cargoes, thereby providing a basis for subsequent analysis and decision-making. The calculation formula contains multiple parameters, such as obstruction area, obstruction angle, obstruction attenuation coefficient, distance and correction coefficient. The introduction of these parameters makes the calculation of the obstruction degree more comprehensive and can reflect the influence of different factors on the obstruction degree: the obstruction area directly affects the visibility, and the larger the area, the higher the obstruction degree is usually; the obstruction angle affects the appearance of the observed object, and a larger obstruction angle will lead to a more obvious obstruction effect; the obstruction attenuation coefficient takes into account the influence of factors such as light and material on visibility, and can more realistically simulate the obstruction effect; and the distance between the object and the observation point will affect the clarity and obstruction degree of observation. Secondly, in the formula Represents the total area of ​​a specified area, so that a detailed analysis can be performed on a specific area, which is crucial for optimizing cargo management in complex environments, especially in warehousing and logistics centers, and can help managers evaluate cargo layout and visibility in different areas. In addition, the introduction of a correction factor can effectively adjust the calculation results to make them closer to reality. Assessments based on the degree of occlusion can help optimize the storage and display strategies of goods. For example, if the degree of occlusion in a certain area is high, it is necessary to adjust the placement or position of the goods to improve their visibility and accessibility, which is important for improving logistics efficiency and reducing the time to find goods. Through systematic quantitative analysis of the degree of occlusion, managers can make more reasonable decisions based on the data. For example, whether the shelves need to be rearranged, whether lighting needs to be increased, whether certain goods need to be re-labeled, etc. In summary, this formula fully takes into account the first In the specified grid area The specified cargo occlusion degree corresponding to the occluded partition , No. In the specified grid area The total area size of the area corresponding to the blocked partitions , No. In the specified compartment area The size of the specified cargo blocking area corresponding to the blocked partition , No. In the specified compartment area The specified cargo blocking angle corresponding to the blocked partition , No. In the specified compartment area The occlusion attenuation coefficient corresponding to the occluded partition , No. In the specified compartment area The distance between the blocked partition and the observation point corresponds to the specified cargo , small area elements , specify the correction factor for the degree of obstruction caused by the cargo , according to In the specified compartment area The specified cargo occlusion degree corresponding to the occluded partition The correlation between the above parameters constitutes a functional relationship , this formula can realize the calculation process of the cargo occlusion degree of the corresponding designated cargo occlusion partition, and at the same time, the correction coefficient of the cargo occlusion degree is specified The introduction of can be adjusted according to the errors that occur in the calculation process, thereby improving the accuracy and applicability of the calculation formula for the regional cargo obstruction degree.

[0125] Further, step S3 includes the following steps:

[0126] Step S31: judging and analyzing the double counting verification and comparison results of the designated goods. If the double counting verification and comparison result of the designated goods is that the RFID tag count is equal to the video frame count, the side display screen of the equipment area is used to confirm that the corresponding designated compartment area count is consistent, so as to perform the corresponding equipment area positioning access operation;

[0127] In the embodiment of the present invention, when judging the double counting verification and comparison result of the designated goods obtained by the previous quantitative calculation, the RFID tag count is compared with the video frame count. If the RFID tag count is equal to the video frame count, it means that the count is consistent. At this time, the counting consistency of the designated compartment area is confirmed to the operator by using the side display screen of the equipment area. In a specific implementation, the counting result can be displayed on the display screen in real time through the data display interface, ensuring that the operator can quickly obtain information and perform the corresponding equipment area positioning and access operations, ensuring the smooth progress of subsequent operations.

[0128] Step S32: If the result of the double count verification and comparison of the designated goods is that the RFID tag count is greater than or less than the video frame count, the side display screen of the equipment area is used to confirm that the count of the corresponding designated compartment area is inconsistent, and an abnormal ratio evaluation calculation is performed based on the RFID tag count and the video frame count to obtain the abnormal ratio of the designated goods count in the compartment area;

[0129] In an embodiment of the present invention, if the double counting verification comparison result shows that the RFID tag count is greater than or less than the video frame count, it is necessary to confirm that the count of the designated compartment area is inconsistent. At this time, the side display screen of the equipment area will display a warning message of "count inconsistency". At the same time, the side display screen of the equipment area will perform an abnormal ratio evaluation calculation based on the RFID tag count and the video frame count. In specific operations, the abnormal ratio is calculated using a formula, for example: (RFID count - video frame count) / video frame count) * 100%, and the result is displayed on the side display screen so that the operator can understand the current counting abnormality and facilitate subsequent processing, and finally obtain the abnormal ratio of the designated cargo count in the compartment area.

[0130] Step S33: Based on the abnormal ratio of the goods count in the designated compartment area, the display screen on the side of the equipment area is used to perform a count abnormality reminder response review operation on the corresponding designated compartment area.

[0131] In an embodiment of the present invention, if the comparison and judgment shows that the abnormal ratio of the count of designated goods in the compartment area is a positive number, the state will be recorded and marked through the side display screen of the equipment area, and it will be pointed out that there is an abnormal problem of visual angle occlusion in the designated compartment area. At this time, an LED abnormal flashing control instruction will be generated in response, and the instruction will be sent to the LED light in the designated compartment area. The LED light will flash at a predetermined frequency to clearly remind the operator that there is an occlusion problem. The operator can observe the flashing light and promptly perform the occlusion review of the designated goods in the compartment; and if the comparison and judgment shows that the abnormal ratio of the count of designated goods in the compartment area is a negative number, the side display screen of the equipment area will be used to record and mark this abnormal situation, and it will be pointed out that there is an abnormal problem that the RFID tag is not read in the designated compartment area. At this time, a sound indication abnormal control instruction will be generated in response, and the instruction will be applied to the sound indicator in the designated compartment area. The sound indicator will emit a clear alarm sound to prompt the operator to perform the review operation in time to ensure the accuracy and completeness of all goods.

[0132] Further, step S33 includes the following steps:

[0133] If the abnormal ratio of the designated cargo count in the compartment area is positive, the display screen on the side of the equipment area is used to record and mark that the corresponding designated equipment cargo has a visual angle occlusion abnormality in the designated compartment area, so as to respond to the generation of the compartment LED abnormal flashing control instruction, and the compartment LED abnormal flashing control instruction is applied to the LED lights in the designated compartment area to flash and light up to remind the operator to perform the corresponding compartment designated cargo occlusion review operation;

[0134] In an embodiment of the present invention, if the comparison determines that the abnormal ratio of the count of designated goods in the compartment area is a positive number, the system will record and mark the status through the side display screen of the equipment area, indicating that there is an abnormal viewing angle occlusion problem in the designated compartment area. At this time, the system responds by generating an LED abnormal flashing control instruction, and the instruction is sent to the LED light in the designated compartment area. The LED light will flash at a predetermined frequency to clearly remind the operator that there is an occlusion problem. The operator can observe the flashing light and promptly perform the occlusion review of the designated goods in the compartment to ensure that the obstructed goods can be accurately identified during the inspection process, so as to take necessary measures to clean or adjust them.

[0135] Preferably, if the abnormal ratio of the count of designated goods in the compartment area is a negative number, the side display screen of the equipment area is used to record and mark the abnormal problem that the RFID tag of the corresponding designated equipment goods in the designated compartment area has not been read, so as to respond to the generation of a compartment sound indication abnormality control instruction, and the compartment sound indication abnormality control instruction is applied to the sound indicator in the designated compartment area to sound and remind the operator to perform the corresponding compartment designated goods RFID tag review operation.

[0136] In an embodiment of the present invention, if the comparison and judgment shows that the abnormal ratio of the count of designated goods in the compartment area is negative, the system will use the display screen on the side of the equipment area to record and mark this abnormal situation, and point out that there is an abnormal problem that the RFID tag has not been read in the designated compartment area. At this time, the system responds by generating a sound indication abnormal control instruction, and applies the instruction to the sound indicator in the designated compartment area. The sound indicator will emit a clear alarm sound to prompt the operator to conduct a review operation in time. Through this sound reminder, the operator can quickly identify the RFID tag reading problem, and then perform manual inspection or rescan to ensure the accuracy and completeness of all goods.

[0137] Furthermore, the present invention also provides an equipment area positioning and identification system based on RFID technology, which is used to execute the equipment area positioning and identification method based on RFID technology as described above, and the equipment area positioning and identification system based on RFID technology includes:

[0138] The compartment positioning RFID tag counting module is used to attach an RFID tag to each piece of equipment cargo in the equipment area, and use the RFID reader to scan and read the RFID tags in the equipment area in real time to obtain the RFID tag identification data of the equipment area cargo; based on the RFID tag identification data of the equipment area cargo, the side display screen of the equipment area is used to perform compartment positioning, identification and counting of the designated equipment cargo corresponding to the user, so as to obtain the RFID tag counting results of the designated equipment cargo compartment area and the designated cargo corresponding to each designated compartment area;

[0139] The designated equipment cargo double counting verification module is used to use a video camera to capture the cargo status video of the designated equipment cargo compartment area to obtain the designated equipment cargo video image frames corresponding to each designated compartment area; based on the designated equipment cargo video image frames corresponding to each designated compartment area, the corresponding designated equipment cargo is subjected to video cargo occlusion calibration counting to obtain the designated cargo video frame counting results corresponding to each designated compartment area; double counting verification is performed according to the designated cargo RFID tag counting results and the designated cargo video frame counting results, thereby obtaining the designated cargo double counting verification comparison results;

[0140] The compartment area counting positioning reminder response module is used to perform positioning reminder response operations on the corresponding designated compartment area based on the double counting verification and comparison results of the designated goods using the side display screen of the equipment area.

[0141] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0142] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A method for equipment area positioning and identification based on RFID technology, characterized in that: The following steps are involved: Step S1: by attaching an RFID tag to each piece of equipment cargo in the equipment area, and using an RFID reader to scan and read the RFID tags in the equipment area in real time, so as to obtain the RFID tag identification data of the equipment area cargo; based on the RFID tag identification data of the equipment area cargo, the side display screen of the equipment area is used to perform compartment positioning, identification and counting of the designated equipment cargo corresponding to the user, and obtain the RFID tag counting results of the designated equipment cargo compartment area and the designated cargo corresponding to each designated compartment area; Step S2: Use a video camera to capture the cargo status video of the designated equipment cargo compartment area to obtain the designated equipment cargo video image frames corresponding to each designated compartment area; perform video cargo occlusion calibration counting on the corresponding designated equipment cargo based on the designated equipment cargo video image frames corresponding to each designated compartment area to obtain the designated cargo video frame counting result corresponding to each designated compartment area; perform double counting verification according to the designated cargo RFID tag counting result and the designated cargo video frame counting result to obtain the designated cargo double counting verification comparison result. Step S2 includes the following steps: Step S21: using a video camera to capture the cargo status video of the designated equipment cargo compartment area to obtain the designated equipment cargo video image frame corresponding to each designated compartment area; Step S22: performing image denoising processing frame by frame on the video image frames of designated equipment and cargo corresponding to each designated grid area, so as to obtain denoised video image frames of designated cargo corresponding to each designated grid area; Step S23: performing frame-by-frame background recognition and cropping processing on the denoised image frames of the designated goods video corresponding to each designated grid area, so as to obtain the background cropped image frames of the designated goods video corresponding to each designated grid area; Step S24: Based on the corresponding designated cargo video background cropped image frames in each designated compartment area, video cargo occlusion calibration counting is performed on the corresponding designated equipment cargo to obtain the corresponding designated cargo video frame counting results in each designated compartment area. Step S24 includes the following steps: Step S241: Based on the corresponding designated cargo video background cropped image frames in each designated compartment area, the corresponding designated equipment cargo is identified and divided into designated cargo areas, and the designated cargo unobstructed partitions and designated cargo obstructed partitions corresponding to the video image frames in each designated compartment area are obtained; Step S242: performing designated goods identification and counting on designated goods unobstructed partitions corresponding to the video image frames in each designated compartment area, and obtaining designated goods unobstructed counting results corresponding to each designated compartment area; Step S243: Based on the designated cargo obstructed partitions corresponding to the video image frames in each designated compartment area, the cargo obstruction degree of the corresponding designated equipment cargo is calculated to obtain the designated cargo obstruction degree corresponding to the obstructed partitions in each designated compartment area. Step S243 includes the following steps: Based on the blocked partitions of the designated goods corresponding to the video image frames in each designated grid area, the blocked areas of the corresponding designated equipment goods are measured frame by frame, and the sizes of the blocked areas of the designated goods corresponding to the blocked partitions in each designated grid area are obtained; Based on the designated cargo obstructed partitions corresponding to the video image frames in each designated grid area, the corresponding designated equipment cargo is inversely calculated for the obstruction angle geometric relationship, so as to obtain the designated cargo obstruction angle corresponding to the obstructed partitions in each designated grid area; Based on the designated cargo shielding area size and designated cargo shielding angle corresponding to the shielded partition in each designated compartment area, the cargo shielding degree calculation formula is used to calculate the cargo shielding degree of the corresponding designated cargo shielded partition to obtain the designated cargo shielding degree corresponding to the shielded partition in each designated compartment area. The specific formula for calculating the cargo shielding degree is: ； In the formula, For the In the specified grid area The specified cargo occlusion degree corresponding to the occluded partition, For the In the specified compartment area The total area size of the area corresponding to the blocked partitions, For the In the specified grid area The size of the designated cargo blocking area corresponding to the blocked partition, For the In the specified grid area The specified cargo occlusion angle corresponding to the occluded partition, For the In the specified grid area The occlusion attenuation coefficient corresponding to the occluded partition is: For the In the specified grid area The blocked partitions correspond to the distance between the specified goods and the observation point. is a small area element, It is the correction factor for the degree of obstruction of the specified cargo; Step S244: comparing and judging the corresponding occlusion degree of the designated goods according to the preset occlusion degree threshold, when the occlusion degree of the designated goods corresponding to the occluded partition in each designated compartment area is less than the preset occlusion degree threshold, the unoccluded count result of the designated goods corresponding to the designated compartment area is automatically added by 1 to calibrate the video frame count result; when the occlusion degree of the designated goods corresponding to the occluded partition in each designated compartment area is greater than or equal to the preset occlusion degree threshold, no calibration processing is performed until all the occluded partitions are judged, and the video frame count result of the designated goods corresponding to each designated compartment area is obtained; Step S25: performing a double counting verification based on the counting result of the RFID tag of the designated goods and the counting result of the video frame of the designated goods to obtain a double counting verification comparison result of the designated goods; Step S3: Based on the double counting verification and comparison results of the designated goods, the side display screen of the equipment area is used to perform a positioning reminder response operation on the corresponding designated compartment area.

2. The equipment area positioning and identification method based on RFID technology according to claim 1 is characterized in that: Step S1 includes the following steps: Step S11: attaching an RFID tag to each piece of equipment cargo in the equipment area to obtain an RFID-labeled equipment cargo; Step S12: Use the RFID reader to scan and read the RFID tag corresponding to the RFID-identified equipment cargo in the equipment area in real time to obtain the RFID tag identification data of the equipment area cargo, wherein the RFID tag identification data of the equipment area cargo includes the equipment cargo name, the equipment cargo quantity and the equipment cargo storage compartment location; Step S13: Based on the equipment cargo storage compartment position in the equipment area cargo RFID tag identification data, the equipment area side display screen is used to locate and identify the storage compartment of the designated equipment cargo corresponding to the user, and the designated equipment cargo compartment area is obtained; Step S14: Based on the designated equipment cargo compartment area and the equipment cargo quantity in the equipment cargo area RFID tag identification data, regional RFID tag counting is performed on the corresponding designated equipment cargo to obtain the designated cargo RFID tag counting result corresponding to each designated compartment area.

3. The equipment area positioning and identification method based on RFID technology according to claim 1 is characterized in that: Step S23 includes the following steps: Step S231: performing image identification and positioning of the farthest non-zero pixel point in the background direction frame by frame for the denoised image frames of the designated goods in each designated grid area, and obtaining the farthest non-zero pixel point position of each video image frame in each background direction in each designated grid area; Step S232: Draw the maximum circumscribed rectangle of the designated goods for the farthest non-zero pixel point of each video image frame at each background position in each designated grid area, so as to generate the corresponding maximum circumscribed rectangle border line of the video image frame in each designated grid area; Step S233: performing frame-by-frame circumscribed background cropping processing on the designated goods video denoising image frames corresponding to each designated grid area according to the maximum circumscribed rectangular border line of the video image frame corresponding to each designated grid area, so as to obtain the designated goods video background cropped image frames corresponding to each designated grid area.

4. The equipment area positioning and identification method based on RFID technology according to claim 1 is characterized in that: Step S3 includes the following steps: Step S31: judging and analyzing the double counting verification and comparison results of the designated goods. If the double counting verification and comparison result of the designated goods is that the RFID tag count is equal to the video frame count, the side display screen of the equipment area is used to confirm that the corresponding designated compartment area count is consistent, so as to perform the corresponding equipment area positioning access operation; Step S32: If the result of the double count verification and comparison of the designated goods is that the RFID tag count is greater than or less than the video frame count, the side display screen of the equipment area is used to confirm that the count of the corresponding designated compartment area is inconsistent, and an abnormal ratio evaluation calculation is performed based on the RFID tag count and the video frame count to obtain the abnormal ratio of the designated goods count in the compartment area; Step S33: Based on the abnormal ratio of the goods count in the designated compartment area, the display screen on the side of the equipment area is used to perform a count abnormality reminder response review operation on the corresponding designated compartment area.

5. The equipment area positioning and identification method based on RFID technology according to claim 4 is characterized in that: Step S33 includes the following steps: If the abnormal ratio of the designated cargo count in the compartment area is positive, the display screen on the side of the equipment area is used to record and mark that the corresponding designated equipment cargo has a visual angle occlusion abnormality in the designated compartment area, so as to respond to the generation of the compartment LED abnormal flashing control instruction, and the compartment LED abnormal flashing control instruction is applied to the LED lights in the designated compartment area to flash and light up to remind the operator to perform the corresponding compartment designated cargo occlusion review operation; If the abnormal ratio of the count of designated goods in the compartment area is negative, the side display screen of the equipment area will be used to record and mark the abnormal problem that the RFID tag of the corresponding designated equipment goods in the designated compartment area has not been read, in response to generating a compartment sound indication abnormality control instruction, and the compartment sound indication abnormality control instruction will be applied to the sound indicator in the designated compartment area to sound and remind the operator to perform the corresponding compartment designated goods RFID tag review operation.

6. An equipment area positioning and identification system based on RFID technology, characterized in that: Used to execute the equipment area positioning and identification method based on RFID technology as claimed in claim 1, the equipment area positioning and identification system based on RFID technology includes: The compartment positioning RFID tag counting module is used to attach an RFID tag to each piece of equipment cargo in the equipment area, and use the RFID reader to scan and read the RFID tags in the equipment area in real time to obtain the RFID tag identification data of the equipment area cargo; based on the RFID tag identification data of the equipment area cargo, the side display screen of the equipment area is used to perform compartment positioning, identification and counting of the designated equipment cargo corresponding to the user, so as to obtain the RFID tag counting results of the designated equipment cargo compartment area and the designated cargo corresponding to each designated compartment area; The designated equipment cargo double counting verification module is used to use a video camera to capture the cargo status video of the designated equipment cargo compartment area to obtain the designated equipment cargo video image frames corresponding to each designated compartment area; based on the designated equipment cargo video image frames corresponding to each designated compartment area, the corresponding designated equipment cargo is subjected to video cargo occlusion calibration counting to obtain the designated cargo video frame counting results corresponding to each designated compartment area; double counting verification is performed according to the designated cargo RFID tag counting results and the designated cargo video frame counting results, thereby obtaining the designated cargo double counting verification comparison results; The compartment area counting positioning reminder response module is used to perform positioning reminder response operations on the corresponding designated compartment area based on the double counting verification and comparison results of the designated goods using the side display screen of the equipment area.

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