Processing method, system and equipment for automatic dispensing process and medium

Abstract

The disclosure describes a processing method, system, device and medium for an automatic dispensing process, the processing method comprising: acquiring a monitoring video corresponding to prescription information in the automatic dispensing process, the prescription information comprising a prescription identifier for characterizing uniqueness of the prescription information, acquiring a video identifier matched with the monitoring video based on the monitoring video, the prescription information and the monitoring video are associated based on the video identifier, the monitoring video associated with the prescription information is segmented and intercepted to obtain a plurality of monitoring video segments, the plurality of monitoring video segments are in one-to-one correspondence with a plurality of medicine dispensing links in the automatic medicine dispensing process, and video segment identifiers matched with the monitoring video segments are obtained based on the monitoring video segments; and generating an identifier array based on the prescription identifier, the video identifier and the video segment identifier, and associating the identifier array to the prescription information. According to the method and the device, a plurality of medicine dispensing links in the automatic medicine dispensing process can be comprehensively monitored, and the monitoring video segments corresponding to the medicine dispensing links can be quickly retrieved according to the prescription information.

Description

Technical Field

[0001] The present disclosure generally relates to the field of medical device technology, and more particularly to a processing method, system, device and medium for an automated medication dispensing process. Background Art

[0002] In recent years, more and more dispensing systems have adopted automatic dispensing technology. The automatic dispensing system is a system that automatically picks up multiple drugs according to prescription information and automatically dispenses multiple drugs. Compared with the traditional manual dispensing method, the automatic dispensing system saves manpower and material resources to a great extent, improves the speed and accuracy of drug dispensing, effectively reduces various omissions in manual dispensing, and realizes the intelligence and informationization of medical drug dispensing.

[0003] In order to make the dispensing process traceable, it is usually necessary to take monitoring measures on the automatic dispensing system. In the prior art, cameras are usually used to monitor the dispensing process. When it is necessary to trace the dispensing process corresponding to a prescription or a certain dispensing link in the dispensing process, it is generally necessary to manually check the entire monitoring video to find the monitoring video segment corresponding to the required dispensing link.

[0004] However, when the above-mentioned prior art calls back the monitoring video, it is usually necessary to manually search for the monitoring video corresponding to the prescription and rely on manual verification of the monitoring video, which is inefficient and prone to errors. Summary of the invention

[0005] The present disclosure is proposed in view of the above-mentioned situation, and its purpose is to provide a processing method, system, equipment and medium for the automatic dispensing process, which can comprehensively monitor multiple dispensing links in the automatic dispensing process, and can quickly retrieve the monitoring video corresponding to the prescription information and the monitoring video segments corresponding to the multiple dispensing links according to the prescription information.

[0006] To this end, the first aspect of the present disclosure provides a processing method for an automatic dispensing process, which is a processing method for processing a surveillance video in the automatic dispensing process, comprising obtaining a surveillance video corresponding to prescription information in the automatic dispensing process, wherein the prescription information includes a prescription identifier for characterizing the uniqueness of the prescription information; obtaining a video identifier matching the surveillance video based on the surveillance video, wherein the video identifier includes the prescription identifier and a first time identifier for characterizing the monitoring moment of the surveillance video; associating the prescription information and the surveillance video based on the video identifier; segmenting the surveillance video associated with the prescription information to obtain a plurality of surveillance video segments, wherein the plurality of surveillance video segments correspond one-to-one to a plurality of dispensing links in the automatic dispensing process; obtaining a video segment identifier matching the surveillance video segment based on the surveillance video segment; generating an identifier array based on the prescription identifier, the video identifier, and the video segment identifier; and associating the identifier array to the prescription information.

[0007] In the first aspect of the present disclosure, by acquiring the monitoring video corresponding to the prescription information in the automatic dispensing process and associating the prescription information with the monitoring video, the prescription information and the monitoring video of the automatic dispensing process can be matched one by one; the monitoring video corresponding to the prescription information is segmented and intercepted, and the monitoring video segments corresponding to each dispensing link in the dispensing process can be obtained; and associating the identification array with the prescription information can make the prescription information correspond to the monitoring video and the multiple monitoring video segments respectively. In this case, the prescription information including the prescription identification can be used as a search condition to quickly locate the monitoring video segments corresponding to the multiple dispensing links, thereby realizing the visualization of each dispensing link in the automatic dispensing process, and facilitating the recording of each dispensing link in the dispensing process, thereby facilitating the backtracking and verification of the automatic dispensing process, improving the efficiency of backtracking and verification, and improving the transparency and credibility of the dispensing process.

[0008] In addition, in the processing method involved in the first aspect of the present disclosure, optionally, obtaining the monitoring video includes detecting whether the video service is turned on; in response to the video service being turned on, checking the number of cameras used to shoot the monitoring video; in response to the number of cameras meeting the preset condition and based on the prescription identification received for the first time, controlling the camera to start video monitoring of the automatic dispensing process; and based on the prescription identification received again, controlling the camera to end video monitoring of the automatic dispensing process. In this case, by detecting that the video service has been turned on and then monitoring, the monitoring video can be recorded, and the number of cameras turned on can be automatically controlled based on the monitoring requirements of each prescription information to monitor the automatic dispensing process from multiple positions, so that the automatic dispensing process can be monitored and recorded from multiple angles, which can improve the comprehensiveness of monitoring of multiple dispensing links in the automatic dispensing process, and can improve the flexibility of monitoring dispensing links corresponding to different prescription information. In addition, controlling the start and end of monitoring based on the prescription identification can make it easy to make at least one obtained monitoring video correspond to the prescription information.

[0009] In addition, in the processing method involved in the first aspect of the present disclosure, optionally, the number of the cameras is multiple, and the video identification also includes the camera position identification of the camera. In this case, multiple surveillance videos corresponding to the prescription information can be obtained based on the multiple cameras, and the camera positions used to shoot each surveillance video can be distinguished based on the camera position identification, and then the surveillance key areas of each surveillance video can be distinguished.

[0010] In addition, in the processing method involved in the first aspect of the present disclosure, optionally, obtaining the multiple monitoring video segments includes taking the starting moment of the automatic dispensing process corresponding to the prescription information as the first time marker, and obtaining the initial time period of each dispensing link based on the first time marker and the dispensing speed of each dispensing link; intercepting multiple initial pictures corresponding to the initial time period in the monitoring video, and obtaining at least one target picture based on the multiple initial pictures and at least one pre-stored picture, the pre-stored picture being a photo corresponding to the calibrated start moment or end moment of each dispensing link; obtaining the target time period of each dispensing link based on the target moment of the target picture, the target moment being the monitoring moment corresponding to the target picture; and intercepting the monitoring video in segments based on the target time period to obtain the multiple monitoring video segments. In this case, based on the first time mark and the dispensing speed of each dispensing link, the initial time period of each dispensing link, that is, the estimated time period, can be calculated. Then, multiple pictures are captured within the initial time period and the multiple initial pictures are compared with the pre-stored pictures. Since the pre-stored pictures are calibrated pictures, the accuracy of obtaining the target pictures can be improved based on the pre-stored pictures as the comparison basis, and then the accuracy of the starting time of each dispensing link can be improved, thereby improving the accuracy of the target time period of each dispensing link, that is, improving the accuracy of the judgment of the actual time period of each dispensing link, thereby improving the accuracy of intercepting the monitoring video segments corresponding to each dispensing link.

[0011] In addition, in the processing method involved in the first aspect of the present disclosure, optionally, obtaining the target time period includes comparing each of the initial pictures with the pre-stored pictures to obtain the similarity between each of the initial pictures and the pre-stored pictures; in response to the highest similarity and the similarity being not less than a preset threshold, taking the initial picture corresponding to the highest similarity and the similarity being not less than the preset threshold as the target picture and recording the target moment corresponding to the target picture; and obtaining the target time period based on the target moment. In this case, by taking the initial picture whose similarity to the pre-stored pictures is not less than the preset threshold and the highest similarity as the target picture, the accuracy of the target picture can be improved, thereby improving the accuracy of the target time period corresponding to each dispensing link of the prescription information, thereby, the monitoring video segments obtained by segmenting the monitoring video according to the target time period can accurately record the dispensing process of each dispensing link.

[0012] In addition, in the processing method involved in the first aspect of the present disclosure, optionally, at least one of the target images is used as a cover thumbnail of each of the monitoring video segments, and multiple monitoring video segments are thumbnailed to the same page. In this case, since the monitoring video segment uses the target image as a cover thumbnail, the monitoring video segment corresponding to each dispensing link can be quickly found by browsing the cover thumbnail, thereby improving the backtracking efficiency and verification efficiency of each dispensing link.

[0013] In addition, in the processing method involved in the first aspect of the present disclosure, optionally, the prescription information also includes search keywords for each dispensing link, and encryption is performed based on the prescription identifier, the video identifier, the second time identifier for representing the monitoring moment of the monitoring video segment, and a random number to obtain the video segment identifier corresponding to the prescription information. In this case, the monitoring video segment is indexed by the video segment identifier, and the monitoring video segment corresponding to the retrieved dispensing link can be quickly located by using the prescription information including the search keywords for each dispensing link as the search condition, that is, the monitoring video segment of the dispensing link that matches the keyword in the search condition can be obtained, thereby facilitating the retrieval of the monitoring video segments corresponding to each dispensing link of the prescription information. In addition, obtaining the video segment identifier by encryption can protect data security.

[0014] The second aspect of the present disclosure provides a monitoring system for an automatic medication dispensing process, which is a monitoring system for processing monitoring videos in the automatic medication dispensing process, including a recording end, a processing end and a service end; the recording end is configured to obtain a monitoring video corresponding to prescription information in the automatic medication dispensing process; the prescription information includes a prescription identifier for characterizing the uniqueness of the prescription information; the processing end is configured to obtain a video identifier matching the monitoring video based on the monitoring video, the video identifier including a first time identifier for characterizing the monitoring moment of the monitoring video and the prescription identifier; the processing end is configured to associate the prescription information and the monitoring video based on the video identifier, and segmentally intercept the monitoring video associated with the prescription information to obtain multiple monitoring video segments, and the multiple monitoring video segments correspond one-to-one to multiple medication dispensing links in the automatic medication dispensing process; the processing end is also configured to obtain a video segment identifier matching the monitoring video segment based on the monitoring video segment; and generate an identifier array based on the prescription identifier, the video identifier, and the video segment identifier; the service end is configured to associate the identifier array with the prescription information.

[0015] In the second aspect of the present disclosure, the monitoring system includes a recording end, a processing end, and a service end. In this case, the monitoring video corresponding to the prescription information in the automatic dispensing process can be obtained through the recording end, the prescription information and the monitoring video can be associated through the processing end and the monitoring video segments corresponding to each dispensing link in the dispensing process can be obtained, and the identification array can be associated with the prescription information through the service end so that the prescription information can correspond to the monitoring video and multiple monitoring video segments respectively, thereby reading and querying the prescription information, and the prescription information including the prescription identification can be used as a search condition to quickly locate the monitoring video segments corresponding to multiple dispensing links, and the processing end can provide functions such as video playback, pause, fast forward, and fast rewind, so as to facilitate the automatic dispensing process to be traced back and checked, improve the efficiency of tracing back and checking, and improve the transparency and credibility of the dispensing process.

[0016] A third aspect of the present disclosure provides an electronic device, the electronic device comprising a processor and a memory, the processor executing a program stored in the memory to implement the processing method involved in the first aspect of the present disclosure.

[0017] A fourth aspect of the present disclosure provides a computer-readable storage medium, wherein the computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed by a processor, the processing method involved in the first aspect of the present disclosure is implemented.

[0018] According to the present disclosure, a processing method, system, device and medium for the automatic dispensing process are provided, which can comprehensively monitor multiple dispensing links in the automatic dispensing process and quickly retrieve monitoring videos corresponding to prescription information and monitoring video segments corresponding to multiple dispensing links according to prescription information. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The present disclosure will now be explained in further detail, by way of example only, with reference to the accompanying drawings.

[0020] Figure 1 It is a schematic diagram showing an application scenario of the processing method involved in the example of the present disclosure.

[0021] Figure 2 is a flowchart showing a processing method involved in the example of the present disclosure.

[0022] Figure 3 is a flowchart showing the acquisition of surveillance video involved in the example of the present disclosure.

[0023] Figure 4 is an information flow diagram showing the monitoring system involved in the example of the present disclosure.

[0024] Figure 5 is a flow chart showing the process of ending video monitoring of an automatic medication dispensing process involved in an example of the present disclosure.

[0025] Figure 6 1 is a flowchart showing a first implementation of obtaining a plurality of surveillance video segments in a processing method according to an example of the present disclosure.

[0026] Figure 7 1 is a flowchart showing a second embodiment of the processing method of obtaining a plurality of surveillance video segments according to the example of the present disclosure.

[0027] Figure 8 is a structural block diagram showing a monitoring system for an automatic medication dispensing process involved in an example of the present disclosure. DETAILED DESCRIPTION

[0028] It should be noted that the terms "including" and "having" and any variations thereof in the present disclosure, such as a process, method, system, product or device that includes or has a series of steps or units, are not necessarily limited to those steps or units clearly listed, but may include or have other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0029] The present disclosure provides a processing method for an automatic dispensing process (hereinafter referred to as the processing method), which is a processing method for processing monitoring videos in the automatic dispensing process. Through the processing method provided by the present disclosure, the monitoring video segments corresponding to multiple dispensing links can be quickly located using prescription information including prescription identification as a search condition, thereby realizing the visualization of each dispensing link in the automatic dispensing process, facilitating the recording of each dispensing link in the dispensing process, thereby facilitating the backtracking and verification of the automatic dispensing process, improving the efficiency of backtracking and verification, and improving the transparency and credibility of the dispensing process.

[0030] The present disclosure also provides a monitoring system for the automatic dispensing process (hereinafter referred to as the monitoring system), which is a monitoring system for processing monitoring videos in the automatic dispensing process, including a recording end, a processing end, and a service end. Through the monitoring system provided by the present disclosure, prescription information can be read and queried, and the monitoring video segments corresponding to multiple dispensing links can be quickly located using the prescription information including the prescription identification as a search condition, and functions such as video playback, pause, fast forward, and fast rewind can be provided, so that the automatic dispensing process can be easily traced back and verified, the efficiency of tracing back and verification can be improved, and the transparency and credibility of the dispensing process can be improved.

[0031] The processing method for the automatic dispensing process involved in the present disclosure may also be referred to as a video processing method, a processing method, a monitoring video processing method of an automatic dispensing system, a monitoring video processing method of an automatic dispensing machine, a processing method of the dispensing process, a monitoring video processing method of the dispensing process, or a video management method of an automatic dispensing process, etc.

[0032] In some examples, the monitoring video and target image involved in the present disclosure may be in color. In some examples, the monitoring video and target image involved in the present disclosure may be in black and white. Thus, the processing method involved in the present disclosure can be applied to different types of cameras.

[0033] Hereinafter, the present disclosure will be described in detail with reference to the accompanying drawings. Figure 1 It is a schematic diagram showing an application scenario of the processing method involved in the example of the present disclosure.

[0034] In some examples, the processing methods disclosed herein can be applied to Figure 1 The monitoring system 10 shown. In some examples, the automatic dispensing system 20 can be a system that automatically calculates and dispenses the dosage and combination of drugs. In some examples, the monitoring system 10 can monitor the automatic dispensing system 20 to visualize each dispensing link in the automatic dispensing process, and can record each dispensing link in the dispensing process. This makes it easy to trace back and verify the automatic dispensing process, thereby improving the transparency and credibility of the dispensing process.

[0035] In some examples, the processing method can be applied to scenarios such as a hospital's intravenous preparation center, a scientific research institution, or a medical laboratory.

[0036] In some examples, when the automatic medication dispensing system 20 is used to prepare and manage drugs in the intravenous medication center of a hospital, the operation of the automatic medication dispensing system 20 can be monitored by the processing method involved in the present disclosure.

[0037] In some examples, in scientific research institutions or medical laboratories, an automatic dispensing system 20 is often used to prepare reagents or drugs, and the processing method involved in the present disclosure can be used to monitor the dispensing process.

[0038] In the present disclosure, the processing method is applied to the above-mentioned scenarios to backtrack and verify the automatic dispensing process. Further, according to the backtracking results, the operation of each dispensing link of the automatic dispensing system 20 in the dispensing process can be adaptively adjusted, thereby improving the accuracy of dispensing and the safety of drug management.

[0039] In some examples, for some special drugs (such as radioactive drugs), using the automatic drug dispensing system 20 to dispense drugs can reduce the contact of personnel with drugs, thereby improving the safety of the drug dispensing personnel.

[0040] However, the present disclosure is not limited thereto, and the processing method involved in the present disclosure can be applied to any scenario where the automatic dispensing process needs to be monitored and managed. Thus, the visualization of each dispensing link in the automatic dispensing process can be realized, and the monitoring video segments corresponding to each dispensing link in the dispensing process can be recorded, which can facilitate the backtracking and verification of the automatic dispensing process, thereby improving the accuracy of drug preparation and the safety of drug management.

[0041] Figure 2 is a flowchart showing a processing method involved in the example of the present disclosure.

[0042] For some examples, see Figure 2 The processing method may include obtaining a monitoring video corresponding to the prescription information during the automatic dispensing process (step S100), obtaining a video identifier matching the monitoring video based on the monitoring video (step S200), associating the prescription information and the monitoring video based on the video identifier (step S300), segmenting the monitoring video associated with the prescription information to obtain multiple monitoring video segments (step S400), obtaining a video segment identifier matching the monitoring video segment based on the monitoring video segment (step S500), generating an identifier array based on the prescription identifier, the video identifier, and the video segment identifier (step S600), and associating the identifier array with the prescription information (step S700). Therefore, the processing method disclosed in the present invention can facilitate recording of the dispensing process.

[0043] In some examples, in step S100, a surveillance video corresponding to the prescription information during the automatic dispensing process may be obtained. In some examples, the prescription information may include a prescription identification. In some examples, the prescription identification may be used to characterize the uniqueness of the prescription information. In this case, the content associated with the one-to-one corresponding prescription information can be retrieved through the prescription identification. In some examples, the prescription identification may be generated by encryption based on the prescription information.

[0044] In some examples, prescription information may also include medical vouchers from a medical system (e.g., a hospital management information system), search keywords for each dispensing link, batch, department, patient name, medication type, prescription time, creation time, prescription number, prescription status, doctor, bed number, medication information, log records, alarm records, videos, and pictures, etc. Thus, corresponding related content can be retrieved according to at least one element in the prescription information.

[0045] Figure 3 is a flowchart showing the acquisition of surveillance video involved in the example of the present disclosure. Figure 4 is an information flow diagram showing the monitoring system 10 involved in the example of the present disclosure.

[0046] For some examples, see Figure 3 , obtaining the monitoring video may include detecting whether the video service is turned on (step S110), checking the number of cameras in response to the video service being turned on (step S120), starting the video monitoring of the automatic dispensing process (step S130), and ending the video monitoring of the automatic dispensing process (step S140). In this case, by detecting that the video service has been turned on and then monitoring, the monitoring video can be recorded, and the number of cameras turned on can be automatically controlled based on the monitoring requirements of each prescription information to monitor the automatic dispensing process from multiple positions, so that the automatic dispensing process can be monitored and recorded from multiple angles, which can improve the comprehensiveness of monitoring multiple dispensing links in the automatic dispensing process, and can improve the flexibility of monitoring the dispensing links corresponding to different prescription information. In addition, controlling the start and end of monitoring based on the prescription identification can make it easier to make at least one obtained monitoring video correspond to the prescription information.

[0047] As described above, the processing method involved in the present disclosure can be applied to the monitoring system 10. In some examples, the monitoring system 10 can be used to process the monitoring video during the automatic dispensing process. Figure 1 and Figure 4 , the monitoring system 10 may include a recording end 102, a processing end 103, and a service end 104. In some examples, see Figure 4 The video recording end 102, the processing end 103 and the service end 104 can exchange information with each other to complete the monitoring of the automatic medication dispensing process and process the monitoring video. Thus, the automatic medication dispensing process can be traced back and checked.

[0048] See also Figure 3 In some examples, in step S110, the processing end 103 can be used to detect whether the video service is turned on. In some examples, the video service can be a service that monitors the automatic dispensing process and records the monitoring video. For example, the video service can include a monitoring service of multiple cameras. In some examples, it can be detected whether the video service is turned on before the automatic dispensing starts. In some examples, the processing end 103 can send a control instruction to the recording end 102, and the recording end 102 can turn on the video service after receiving the control instruction. In this case, by detecting that the video service has been turned on and then starting monitoring, it can be ensured that the monitoring video is recorded.

[0049] Continue to see Figure 3 In some examples, in step S120, the number of cameras may be checked in response to the video service being turned on. In some examples, the recording end 102 may include a camera. In some examples, the processing end 103 may be in communication with the recording end 102, and the processing end 103 may check the number of cameras. In some examples, the camera may be used to capture surveillance video.

[0050] In some examples, the monitoring video may be from a camera installed in the internal space of the automatic dispensing system 20. In this case, the monitoring video of each dispensing link of the dispensing operation in the internal space of the automatic dispensing system 20 can be obtained.

[0051] In some examples, the monitoring video may be from a camera installed outside the automatic dispensing system 20. In this case, being able to obtain the monitoring video outside the automatic dispensing system 20 can be beneficial for monitoring external operations (such as manual operations) on the automatic dispensing system 20.

[0052] In some examples, the monitoring video may come from cameras installed inside and outside the automatic dispensing system 20. In this case, the monitoring video of each dispensing link and the monitoring video of the external operation of the automatic dispensing system 20 can be obtained at the same time, which can improve the transparency and credibility of the dispensing process.

[0053] In some examples, the number of cameras that have been turned on can be checked. In this case, the number of surveillance videos can be obtained based on the number of cameras that have been turned on.

[0054] In some examples, the configuration file may include the number of cameras that need to be turned on corresponding to the prescription information. In some examples, the number of cameras that need to be turned on may be detected by checking the configuration file pre-stored in the server 104. Thus, the monitoring video can be obtained according to the monitoring requirements of each prescription information.

[0055] In some examples, the monitoring system 10 may perform IP (Internet Protocol) sniffing to check the number of cameras that are turned on. For example, the number of cameras that are connected to the network of the monitoring system 10 may be checked.

[0056] In some examples, the number of surveillance videos (i.e., the number of surveillance videos) may be the same as the number of cameras that have been turned on. In this case, on the premise of determining the number of cameras that have been turned on, it is possible to determine whether the surveillance system 10 is operating normally based on the number of surveillance videos finally obtained. For example, if the number of surveillance videos is the same as the number of cameras that have been turned on, the surveillance system 10 is operating normally; if the number of surveillance videos is different from the number of cameras that have been turned on, the surveillance system 10 is faulty.

[0057] In some examples, the number of cameras may be 1. Thus, a surveillance video can be obtained.

[0058] In some examples, the number of cameras may be multiple, such as 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or 16. In this case, multiple monitoring videos can be obtained, thereby improving the comprehensiveness of monitoring the automatic dispensing process. However, the present disclosure is not limited thereto, and in some examples, the number of cameras can be set according to monitoring requirements.

[0059] In some examples, the key areas monitored by the camera can be determined based on monitoring requirements.

[0060] In some examples, the monitoring key area may include the entire area where the automatic medication dispensing system 20 performs medication dispensing operations. In this case, the monitoring coverage can be increased.

[0061] In some examples, the monitoring key area may include a specific partial area where each dispensing link performs a dispensing operation. In this case, each dispensing link can be monitored with emphasis, which can improve the pertinence of the monitoring, thereby being able to monitor more operation details and facilitate verification.

[0062] In some examples, each medication dispensing link may include taking a medicine bottle, opening a lid, extracting liquid, shaking a bottle, taking a syringe, dispensing liquid, taking a medicine bag, injecting liquid medicine into a medicine bag, shaking a bottle, mixing liquid medicine, sealing a bag, labeling or dispensing medicine, etc. In some examples, the key monitoring area may include a specific area where medication dispensing operations are performed in a certain link, such as an area where liquid medicine is extracted in the liquid extraction link. In some examples, the key monitoring area may include areas where medication dispensing operations are performed in multiple medication dispensing links, such as the operation areas of taking a medicine bag and injecting liquid medicine into a medicine bag.

[0063] In some examples, the number of cameras may be the same as the number of dispensing links in the automatic dispensing process. In some examples, each camera may correspond to a key monitoring link of each dispensing link. Thus, the key monitoring area corresponding to each dispensing link can be monitored.

[0064] In some examples, the number of cameras may be greater than the number of drug dispensing links, thereby improving the comprehensiveness of monitoring multiple drug dispensing links in the automatic drug dispensing process.

[0065] In some examples, a camera may be disposed in the internal space of the automatic dispensing system 20. Thus, a monitoring video corresponding to multiple dispensing links may be obtained.

[0066] In some examples, multiple cameras may be arranged in the internal space of the automatic dispensing system 20. Thus, multiple monitoring videos of each dispensing link may be obtained.

[0067] In some examples, one medication dispensing link may correspond to one camera, thereby obtaining a single monitoring video corresponding to a single medication dispensing link.

[0068] In some examples, a dispensing link may correspond to multiple cameras. In this case, it is convenient to monitor and record a dispensing link from multiple angles, so that multiple monitoring videos corresponding to a single dispensing link can be obtained, thereby improving the accuracy of monitoring.

[0069] In some examples, one camera may be disposed in the external space of the automatic medication dispensing system 20. In some examples, a plurality of cameras may be disposed in the external space of the automatic medication dispensing system 20.

[0070] In some examples, multiple cameras may be provided inside and outside the automatic dispensing system 20. In this case, monitoring videos of each dispensing link and monitoring videos of external operations of the automatic dispensing system 20 can be obtained simultaneously, which can improve the transparency and credibility of the dispensing process.

[0071] In some examples, the number of cameras may be less than the number of medication dispensing steps.

[0072] Continue to see Figure 3 In some examples, in step S130, video monitoring of the automatic medication dispensing process may be initiated.

[0073] In some examples, the camera can be controlled to start video monitoring based on the prescription identification received for the first time. In this case, controlling the start of monitoring based on the prescription identification can facilitate making the at least one monitored video obtained correspond to the prescription information.

[0074] In some examples, the server 104 may generate a prescription identifier in advance before the automatic medication dispensing process begins. In some examples, the server 104 may transmit the prescription identifier to the processing terminal 103 .

[0075] In some examples, the automatic medication dispensing system 20 may transmit a start instruction to the processing end 103. The start instruction may represent an instruction to start medication dispensing. Thus, the processing end 103 can obtain the start time of the automatic medication dispensing process.

[0076] In some examples, when a dispensing process of the automatic dispensing system 20 starts, the processing end 103 can transmit the prescription identification to the recording end 102 .

[0077] In some examples, the recording end 102 may control the camera to start video monitoring based on the prescription identification received for the first time. In this case, controlling the start of video monitoring based on the prescription identification can make the at least one obtained monitoring video correspond to the prescription information.

[0078] In some examples, the recording end 102 may start recording of each camera and record the time when each camera starts recording, thereby obtaining the start time of each surveillance video.

[0079] In some examples, the time when each camera starts recording can be the same. In some examples, the time when each camera starts recording can be different. Thus, each camera can be controlled to start recording according to actual needs.

[0080] In some examples, the cameras may be controlled to start video monitoring of the automatic medication dispensing process in response to the number of cameras satisfying a preset condition and based on a prescription identification received for the first time.

[0081] In some examples, the preset condition can be determined based on the prescription information. In some examples, the preset condition can be that the number of cameras that need to be turned on meets the monitoring requirements corresponding to the prescription information. In some examples, each camera can be controlled at the same time so that the number of cameras turned on meets the preset condition. In this case, the number of cameras turned on can be automatically controlled based on the monitoring requirements of each prescription information to monitor the automatic dispensing process from multiple positions, thereby improving the comprehensiveness of monitoring multiple dispensing links in the automatic dispensing process.

[0082] Continue to see Figure 3 In some examples, in step S140, the video monitoring of the automatic medication dispensing process can be ended. In some examples, the camera can be controlled to end the video monitoring of the automatic medication dispensing process based on the prescription identification received again. In this case, controlling the end of monitoring based on the prescription identification can facilitate the correspondence between at least one acquired monitoring video and the prescription information. In some examples, the prescription identification received again can be the same as the prescription identification received for the first time. In this case, controlling the start and end of monitoring based on the prescription identification can facilitate the correspondence between at least one acquired monitoring video and the prescription information.

[0083] Figure 5 is a flow chart showing the process of ending video monitoring of an automatic medication dispensing process involved in an example of the present disclosure.

[0084] For some examples, see Figure 5 The end of the video monitoring of the automatic dispensing process may include the automatic dispensing system 20 transmitting an end instruction to the processing end 103 (step S1401), determining whether the working state is normal (step S1402), the processing end 103 receiving the automatic stop instruction of the automatic dispensing system 20 and transmitting the prescription identification to the recording end 102 again (step S1403), and the processing end 103 receiving the automatic stop instruction or manual stop instruction of the automatic dispensing system 20 and transmitting the prescription identification to the recording end 102 again (step S1404). Thus, the video monitoring can be ended.

[0085] In some examples, in step S1401, the automatic medication dispensing system 20 may transmit an end instruction to the processing terminal 103. Thus, the processing terminal 103 can obtain the end time of the automatic medication dispensing process.

[0086] In some examples, in step S1402, the automatic medication dispensing system 20 may determine whether the working status is normal, and if so, execute step S1403, and if not, execute step S1404.

[0087] In some examples, the end instruction may be an automatic stop instruction. In some examples, if the working state of the automatic medication dispensing system 20 is normal, the automatic stop instruction may be transmitted to the processing end 103 when the medication dispensing process ends.

[0088] In some examples, if the working state of the automatic dispensing system 20 is abnormal (i.e., a fault occurs), for example, the bottle cap of the medicine bottle is not opened and no manual stop is required, at the end of the dispensing process, the automatic dispensing system 20 can send an automatic stop command to the processing end 103.

[0089] In some examples, the end instruction may be a manual stop instruction. In some examples, if the working state of the automatic dispensing system 20 is abnormal (i.e., a fault occurs), such as when a medicine bottle is not taken, the wrong medicine is taken, and a manual stop is required, the automatic dispensing system 20 may send a manual stop instruction to the processing terminal 103 at the end of the dispensing process.

[0090] Continue to see Figure 5 In some examples, in step S1403, when the automatic dispensing system 20 is operating normally, the processing terminal 103 can receive an automatic stop instruction from the automatic dispensing system 20 and transmit the prescription identification to the recording terminal 102 again. Thus, the recording terminal 102 can obtain the end time of the automatic dispensing process.

[0091] Continue to see Figure 5 In some examples, in step S1404, when the automatic dispensing system 20 is not working properly, the processing end 103 may receive an automatic stop command from the automatic dispensing system 20 and retransmit the prescription identification to the recording end 102. In some examples, when the automatic dispensing system 20 is not working properly, the processing end 103 may receive a manual stop command from the automatic dispensing system 20 and retransmit the prescription identification to the recording end 102. Thus, the recording end 102 can obtain the end time of the automatic dispensing process.

[0092] In some examples, the video recording end 102 can control the camera to end the video monitoring of the automatic medication dispensing process based on the prescription identification received again. In this case, controlling the end of the video monitoring based on the prescription identification can make the at least one monitored video obtained correspond to the prescription information.

[0093] In some examples, the recording end 102 may end the recording of each camera and record the time when each camera ends the recording, thereby obtaining the end time of each surveillance video.

[0094] In some examples, the time when each camera ends recording can be the same. In some examples, the time when each camera ends recording can be different. Thus, each camera can be controlled to end recording according to actual needs.

[0095] In some examples, the recording end 102 can upload the monitoring video to the server 104 in real time. Thus, the timeliness of the monitoring video storage can be improved.

[0096] In some examples, the recording end 102 can monitor and record the faults of the automatic dispensing system 20, and the processing end 103 can associate the fault records with the prescription information and the monitoring video. In this way, the abnormal dispensing process can be recorded for easy tracing and verification.

[0097] Return to see Figure 2 In some examples, in step S200, a video identifier matching the surveillance video can be obtained based on the surveillance video. In some examples, the processing end 103 can obtain a video identifier generated at the server end 104. In some examples, the server end 104 can pre-generate a video identifier corresponding to the prescription information and matching the surveillance video according to the prescription information before the video surveillance begins.

[0098] In some examples, the video identifier may include a prescription identifier. In this case, the video identifier and the prescription information can have a corresponding relationship, so that the subsequent association of the video identifier and the prescription information can be facilitated.

[0099] In some examples, the video identifier may include a first time identifier, and the first time identifier may be used to characterize the monitoring time of the monitoring video. In this case, the information of the monitoring time of the monitoring video can be obtained through the video identifier.

[0100] In some examples, the video identifier may include a prescription identifier and a first time identifier. In this case, the surveillance video can be indexed by the video identifier, and the prescription identifier can be used to easily match the prescription information with the surveillance video of the automatic dispensing process, so that the surveillance video corresponding to the prescription information can be easily and quickly processed.

[0101] In some examples, the first time identifier may include time information of the surveillance video. In some examples, the first time identifier may include the start time of the surveillance video. In some examples, the first time identifier may also include the end time of the surveillance video.

[0102] In some examples, the first time mark may include the start time and the end time of the monitoring video. In some examples, the first time mark may include any monitoring time in the middle of the monitoring video. In some examples, the first time mark may include the start time of the automatic dispensing process corresponding to the prescription information.

[0103] In some examples, the video identifier may also include a camera position identifier. In some examples, the camera position identifier may represent the uniqueness of the camera installation location. In some examples, the server 104 may generate a video identifier including a camera position identifier based on the number of cameras and transmit it to the processing terminal 103. The number of cameras may be multiple. In this case, multiple surveillance videos corresponding to the prescription information can be obtained based on multiple cameras, and the camera positions used to shoot each surveillance video can be distinguished based on the camera position identifier, thereby distinguishing the key surveillance areas of each surveillance video.

[0104] In some examples, the video identifier may be encrypted, thereby protecting data security.

[0105] See also Figure 2 In some examples, in step S300, the prescription information and the surveillance video may be associated. In some examples, the prescription information and the surveillance video may be associated based on a video identifier. In some examples, the video identifier may include a prescription identifier. In other words, the video identifier may have a corresponding relationship with the prescription information. In some examples, the file of the surveillance video may be named with the video identifier. In this case, the prescription information and the surveillance video may be associated through the video identifier, the prescription information and the surveillance video of the automatic dispensing process may be matched one-to-one, and the surveillance video corresponding to the prescription information may be retrieved conveniently according to the prescription information.

[0106] See also Figure 2 In some examples, in step S400, the monitoring video associated with the prescription information may be segmented to obtain multiple monitoring video segments. In some examples, the multiple monitoring video segments may correspond to multiple dispensing links in the automatic dispensing process. Thus, the monitoring video segments corresponding to each dispensing link in the dispensing process can be obtained, which can facilitate the retrieval of the monitoring video segments corresponding to each dispensing link according to the prescription information.

[0107] In some examples, multiple medication dispensing links corresponding to the key monitoring areas of multiple monitoring videos can be determined and segmented.

[0108] In some examples, a surveillance video (i.e., a single surveillance video) may be obtained. The single surveillance video may be segmented and intercepted according to the multiple dispensing links corresponding to the single surveillance video. In some examples, multiple surveillance videos may be obtained. The multiple surveillance videos may be segmented and intercepted according to the multiple dispensing links corresponding to the multiple surveillance videos.

[0109] In some examples, a single surveillance video may correspond to multiple drug dispensing links. In some examples, a single drug dispensing link may correspond to multiple surveillance videos. In some examples, the surveillance video segment corresponding to a single drug dispensing link may come from multiple surveillance videos used for segmented interception.

[0110] In some examples, the processing end 103 may obtain multiple monitoring video segments. Specifically, the processing end 103 may obtain multiple monitoring video segments corresponding to multiple drug dispensing links.

[0111] Figure 6 1 is a flowchart showing a first implementation of obtaining a plurality of surveillance video segments in a processing method according to an example of the present disclosure.

[0112] For some examples, see Figure 6 Obtaining multiple monitoring video segments may include obtaining an initial time period for dispensing medicine in each dispensing link based on a first time mark and a dispensing speed of each dispensing link (step S410), intercepting multiple initial images corresponding to the initial time period in the monitoring video (step S420), obtaining at least one target image based on the multiple initial images and at least one pre-stored image (step S430), obtaining a target time period for each dispensing link based on a target moment of the target image (step S440), and segmentally intercepting the monitoring video based on the target time period to obtain multiple monitoring video segments (step S450). In this case, based on the first time mark and the dispensing speed of each dispensing link, the initial time period of each dispensing link, that is, the estimated time period, can be calculated. Then, multiple pictures are captured within the initial time period and the multiple initial pictures are compared with the pre-stored pictures. Since the pre-stored pictures are calibrated pictures, the accuracy of the target pictures can be improved based on the pre-stored pictures as the comparison basis, and then the accuracy of the starting time of each dispensing link can be improved, thereby improving the accuracy of the target time period of each dispensing link, that is, improving the accuracy of the judgment of the actual time period of each dispensing link, thereby improving the accuracy of the surveillance video segments corresponding to each dispensing link.

[0113] See also Figure 6In some examples, in step S410, the initial time period of each dispensing link can be obtained based on the first time mark and the dispensing speed of each dispensing link. In some examples, the start time of the automatic dispensing process corresponding to the prescription information can be used as the first time mark. In this case, the initial time period of each dispensing link, that is, the estimated time period, can be calculated based on the first time mark and the dispensing speed of each dispensing link.

[0114] In some examples, the dispensing speed of each dispensing link can be calculated based on the moving speed of the dispensing equipment (such as a robot) in the automatic dispensing system 20 and the path it needs to pass.

[0115] In other examples, the dispensing speed of each dispensing link can be calculated from the start time of each dispensing link corresponding to the previous prescription information in the automatic dispensing process. For example, the dispensing speed of the dispensing link can be calculated based on the time interval between the start time of the dispensing link corresponding to the previous prescription information and the start time of the next dispensing link.

[0116] Continue to see Figure 6 In some examples, in step S420, multiple initial pictures corresponding to the initial time period in the surveillance video may be captured. For example, multiple initial pictures of the surveillance sub-video in the surveillance video corresponding to the initial time period may be captured. Thus, multiple initial pictures to be processed may be obtained. In some examples, the surveillance sub-video may be a part of the surveillance video used to capture multiple initial pictures.

[0117] In some examples, the initial time period may be the time period of the surveillance video used to capture the initial image, that is, the time period of the surveillance sub-video. This facilitates determining the start or end time of each dispensing link. In some examples, the start time of the next dispensing link may be the end time of the previous dispensing link.

[0118] In some examples, the initial time period may be the entire time interval corresponding to each dispensing link, that is, the estimated target time period. In some examples, the initial time period may be determined based on the preset time interval corresponding to each dispensing link. In some examples, the preset time interval corresponding to the dispensing link may be the entire time interval of each dispensing link corresponding to the previous prescription information. For example, the preset time interval corresponding to the dispensing link may be the entire time interval of each dispensing link corresponding to the previous prescription information.

[0119] In some examples, the number of initial pictures may be 1. In some examples, the initial picture may be the first frame of the estimated monitoring video segment (i.e., the entire monitoring video interval of each dispensing link). In this case, the start time of the dispensing link can be determined based on 1 initial picture.

[0120] In some examples, the initial picture may be a picture of the last frame of the estimated surveillance video segment. In this case, the end time of the dispensing link can be determined based on one initial picture.

[0121] In some examples, the number of initial pictures may be multiple, such as 2, 3, 4, 5, 10, 100, etc., which is not limited here and can be determined according to actual needs. In this case, the entire time interval of the dispensing link can be determined based on multiple initial pictures.

[0122] Continue to see Figure 6 In some examples, in step S430, at least one target picture can be obtained based on multiple initial pictures and at least one pre-stored picture.

[0123] In some examples, the target image may be an image used to characterize the monitoring focus of the monitoring video segment. In some examples, the monitoring focus of the monitoring video segment may include the monitoring focus area corresponding to the monitoring video segment. In some examples, the target image may be a key point image characterizing the operation characteristics of each dispensing link in each monitoring video segment. In this case, by browsing the target image, the information of the corresponding monitoring video segment can be quickly obtained.

[0124] In some examples, key point pictures may include: pictures of taking medicine bottles, pictures of opening lids, pictures of extracting liquid, pictures of shaking bottles, pictures of taking syringes, pictures of preparing liquids, pictures of taking medicine bags, pictures of injecting medicine into medicine bags, pictures of shaking bottles, pictures of mixing medicine liquids, pictures of sealing bags, pictures of labeling, and pictures of dispensing medicine, etc.

[0125] In some examples, the target picture may be a picture at the start time of the surveillance video segment. In some examples, the target picture may be a picture at the end time of the surveillance video segment. In some examples, the target picture may include pictures at the start time and the end time of the surveillance video segment.

[0126] In some examples, the pre-stored picture may be a calibrated picture. In this case, since the pre-stored picture is a calibrated picture, the accuracy of the target picture can be improved based on the pre-stored picture as a reference for comparison.

[0127] In some examples, the pre-stored pictures may be pictures corresponding to the start time of each medication dispensing link that has been calibrated. In some examples, the pre-stored pictures may be pictures corresponding to the end time of each medication dispensing link that has been calibrated. In some examples, the pre-stored pictures may be pictures corresponding to the start time and end time of each medication dispensing link that has been calibrated.

[0128] In some examples, the pre-stored images may be calibrated images that characterize the operational characteristics of each dispensing link. In some examples, the method of calibrating the pre-stored images may include manual calibration and machine learning algorithm calibration. In some examples, the pre-stored images may be target images of each dispensing link corresponding to the previous prescription information. For example, the pre-stored images may be target images of each dispensing link corresponding to the previous prescription information.

[0129] In some examples, the number of pre-stored pictures may be 1.

[0130] In some examples, the number of pre-stored pictures may be multiple, such as 2, 3, 4, 5, 10, 100, etc., which is not limited here and can be determined according to actual needs. In this case, when multiple pre-stored pictures are used as a comparison basis, the accuracy and reliability of obtaining the target picture can be improved.

[0131] In some examples, each initial image can be compared with a pre-stored image to obtain a similarity between each initial image and the pre-stored image. In some examples, a single dispensing link can have a corresponding plurality of initial images. In some examples, each initial image can be compared with a corresponding pre-stored image to obtain a similarity between each initial image and the pre-stored image. In some examples, the method for obtaining the similarity between each initial image and the pre-stored image can include a machine learning algorithm.

[0132] In some examples, in response to the highest similarity, the initial picture corresponding to the highest similarity can be used as the target picture. In some examples, in response to the similarity being not less than a preset threshold, the initial picture corresponding to the similarity not less than a preset threshold can be used as the target picture.

[0133] In some examples, the target image may be selected in response to the highest similarity and the similarity being not less than a preset threshold. In some examples, the initial image corresponding to the highest similarity and the similarity being not less than the preset threshold may be used as the target image. In this case, by using the initial image with the highest similarity and the similarity being not less than the preset threshold as the target image, the accuracy of obtaining the target image can be improved.

[0134] In some examples, the target image may be the one with the highest similarity among multiple initial images whose similarity is not less than a preset threshold. In some examples, the target image may be the one with the highest similarity among multiple initial images. In some examples, the target image may be the one with the highest similarity among multiple initial images whose similarity is not less than a preset threshold and whose corresponding monitoring time is closest to the starting time.

[0135] In some examples, the preset threshold of similarity may be 1.

[0136] In some examples, there may be multiple preset thresholds for similarity, such as 2, 3, 4 or others. In this case, different preset thresholds can be used to select target images according to actual needs.

[0137] In some examples, the preset threshold of similarity can be a threshold automatically set by the monitoring system 10 before starting recording, such as 70%, 75%, 80%, 85% or 90%, etc. In some examples, the preset threshold of similarity can be a threshold manually set before starting recording, such as 70%, 75%, 80%, 85% or 90%, etc.

[0138] In some examples, if no initial image meets the preset threshold of similarity, the initial time period can be automatically reselected and the initial image can be selected. Further, if no initial image meets the preset threshold of similarity, the automatic dispensing system 20 can issue a prompt. In some examples, in response to the automatic dispensing system 20 issuing a prompt, the initial image can be selected manually.

[0139] In some examples, the number of target images may be 1. In some examples, the start time of the medication dispensing process may be determined based on 1 target image. In some examples, the end time of the medication dispensing process may be determined based on 1 target image.

[0140] In some examples, the number of target images may be multiple, such as 2, 3, 4, 5, 10, 100, etc., which is not limited here. In this case, the entire time interval of the dispensing link can be determined based on multiple target images.

[0141] In some examples, the target time corresponding to the target image may be recorded. In some examples, the target time may be the monitoring time corresponding to the target image.

[0142] Continue to see Figure 6 In some examples, in step S440, the target time period can be obtained based on the target moment, that is, the target time period of each dispensing link can be obtained based on the target moment of multiple target images. In this case, when the pre-stored images are used as the basis for comparison, the accuracy of obtaining the target images can be improved, and then the accuracy of obtaining the start time of each dispensing link can be improved, thereby improving the accuracy of obtaining the target time period of each dispensing link, that is, improving the accuracy of judging the actual time period of each dispensing link.

[0143] Continue to see Figure 6 In some examples, in step S450, the monitoring video may be segmented based on the target time period to obtain multiple monitoring video segments. In some examples, the multiple monitoring video segments correspond to multiple dispensing links in the automatic dispensing process.

[0144] In some examples, multiple drug dispensing steps may include taking a medicine bottle, opening a lid, extracting liquid, shaking a bottle, taking a syringe, preparing liquid, taking a medicine bag, injecting liquid medicine into a medicine bag, shaking a bottle, mixing liquid medicine, sealing a bag, labeling or dispensing medicine, etc.

[0145] In some examples, a second time marker may be generated to characterize the monitoring moment of the monitoring video segment. In some examples, the second time marker may include time information of the monitoring video segment.

[0146] In some examples, the second time identifier may include the start time of the monitoring video segment. In some examples, the second time identifier may include the end time of the monitoring video segment. In some examples, the second time identifier may include the start time and the end time of the monitoring video segment. In some examples, the second time identifier may include any monitoring time in the middle of the monitoring video segment. In some examples, the second time identifier may include the start time of the dispensing link corresponding to the monitoring video segment. In some examples, the second time identifier may include at least one target time determined based on at least one target picture corresponding to each monitoring video segment.

[0147] In some examples, at least one target image may be used as a cover thumbnail of each surveillance video segment. For example, an image at the start time of the surveillance video segment may be used as a cover thumbnail of the surveillance video segment.

[0148] In some examples, the picture at the end of the surveillance video segment can be used as the cover thumbnail of the surveillance video segment. In some examples, multiple target pictures can be spliced ​​into the cover thumbnail of the surveillance video segment. In some examples, the pictures at the start and end of the surveillance video segment can be spliced ​​into the cover thumbnail of the surveillance video segment.

[0149] In some examples, multiple surveillance video segments can be thumbnailed to the same page. In this case, since the surveillance video segment uses the target image as the cover thumbnail, the surveillance video segment corresponding to each dispensing link can be quickly found by browsing the cover thumbnail, thereby improving the efficiency of tracing back and checking each dispensing link.

[0150] In some examples, the processing end 103 can generate corresponding target images based on the surveillance video. In some examples, the processing end 103 can use at least one target image as a cover thumbnail of each surveillance video segment. In some examples, the processing end 103 can thumbnail multiple surveillance video segments to the same page. In some examples, the processing end 103 can upload multiple surveillance video segments and at least one target image corresponding thereto to the server 104.

[0151] Figure 71 is a flowchart showing a second embodiment of the processing method of obtaining a plurality of surveillance video segments according to the example of the present disclosure.

[0152] For some examples, see Figure 7 , the multiple monitoring video segments may include obtaining the initial time period for dispensing in each dispensing link based on the first time mark, the re-dispensing time of the automatic dispensing system 20 and the dispensing speed of each dispensing link (step S401), intercepting multiple initial pictures corresponding to the initial time period in the monitoring video (step S402), obtaining at least one target picture based on the multiple initial pictures and at least one pre-stored picture (step S403), obtaining the target time period of each dispensing link based on the target time of the target picture (step S404), and segmenting the monitoring video based on the target time period to obtain multiple monitoring video segments (step S405).

[0153] In some examples, in step S401, the initial time period for dispensing medication at each dispensing link may be obtained based on the first time mark, the re-dispensing time of the automatic dispensing system 20, and the dispensing speed of each dispensing link.

[0154] In some examples, when the automatic dispensing system 20 fails, if the automatic dispensing system 20 can resume re-dispensing, the re-dispensing time can be recorded and transmitted to the processing end 103. In some examples, the processing end 103 can recalculate the dispensing speed of each dispensing link based on the start time of the automatic dispensing process and the re-dispensing time of the automatic dispensing system 20.

[0155] In other examples, when the automatic dispensing system 20 fails, if the automatic dispensing system 20 cannot be restored to re-dispense, it can be manually stopped, and the time of manual stop is recorded and transmitted to the processing end 103. In some examples, the processing end 103 can recalculate the dispensing speed of each dispensing link based on the start time of the automatic dispensing process and the time of manual stop of the automatic dispensing system 20.

[0156] In some examples, the start time or end time of each medication dispensing session may be manually determined.

[0157] In some examples, step S402 may be the same as step S420. In some examples, step S403 may be the same as step S430. In some examples, step S404 may be the same as step S440. In some examples, step S405 may be the same as step S450.

[0158] Return to see Figure 2In some examples, in step S500, a video segment identifier matching the surveillance video segment may be obtained based on the surveillance video segment. In some examples, the video segment identifier may be used to characterize the uniqueness of the surveillance video segment.

[0159] In some examples, the video identifier may be encrypted. In some examples, the video segment identifier may include a prescription identifier, a video identifier, and a second time identifier. In this case, when the video identifier has been encrypted, the video segment identifier including the prescription identifier can associate the video segment identifier with the prescription information, facilitating associating the video segment identifier with the prescription information.

[0160] In some examples, the video segment identifier may include a prescription identifier and a second time identifier. In this case, the video segment identifier can be related to the prescription information, which facilitates associating the video segment identifier with the prescription information.

[0161] In some examples, the video identifier may not be encrypted. In some examples, the video identifier may include a prescription identifier. In some examples, the video segment identifier may include a video identifier and a second time identifier. In this case, the video segment identifier can be associated with the prescription information, which facilitates associating the video segment identifier with the prescription information.

[0162] In some examples, the video segment identifier may be a picture identifier of a target picture corresponding to the monitoring video segment. In some examples, the picture identifier may be used to characterize the uniqueness of the target picture. In some examples, the video segment identifier may be used to name a file of the monitoring video segment. In some examples, the video segment identifier may be used to name a file of the target picture. Thus, an index may be established for the target picture, so that the corresponding target picture may be retrieved according to the prescription information.

[0163] In some examples, the processing end 103 may generate a video segment identifier based on the prescription identifier, the video identifier, and the second time identifier.

[0164] As described above, the prescription information may include search keywords for each dispensing link. In some examples, the search keywords for each dispensing link may include taking a medicine bottle, opening a lid, extracting liquid, shaking a bottle, taking a syringe, preparing liquid, taking a medicine bag, injecting liquid medicine into a medicine bag, shaking a bottle, mixing liquid medicine, sealing a bag, labeling or dispensing medicine, etc. In some examples, the search keywords for each dispensing link may be determined based on specific prescription information. In this case, by using the prescription information including the search keywords for each dispensing link as a search condition, the surveillance video segment corresponding to the retrieved dispensing link can be quickly located.

[0165] In some examples, the video identifier may be encrypted. In some examples, encryption may be performed based on the prescription identifier, the video identifier, the second time identifier, and the random number to obtain a video segment identifier corresponding to the prescription information. In some examples, the second time identifier may be used to characterize the monitoring moment of the monitoring video segment. In this case, when the video identifier has been encrypted, encrypting the video segment identifier based on the prescription identifier can make the video segment identifier related to the prescription information, which is convenient for associating the video segment identifier with the prescription information. In addition, by indexing the monitoring video segment through the video segment identifier, it is convenient to retrieve the monitoring video segments corresponding to each dispensing link of the prescription information. When the prescription information also includes the search keywords of each dispensing link, the prescription information including the search keywords of each dispensing link is used as the search condition to quickly locate the monitoring video segment corresponding to the retrieved dispensing link, that is, the monitoring video segment of the dispensing link matching the keywords in the search condition can be obtained, thereby facilitating the retrieval of the monitoring video segments corresponding to each dispensing link of the prescription information. In addition, obtaining the video segment identifier through encryption can protect data security.

[0166] In some examples, the video identifier may not be encrypted. In some examples, the video identifier may include a prescription identifier. In some examples, encryption may be performed based on the video identifier, the second time identifier, and the random number to obtain a video segment identifier. In some examples, the video segment identifier may correspond to the prescription information. In this case, the video segment identifier can be related to the prescription information, so as to facilitate associating the video segment identifier with the prescription information.

[0167] In some examples, the video identifier and the video segment identifier may be encrypted. In some examples, in step S600, an identifier array may be generated based on the prescription identifier, the video identifier, and the video segment identifier. In this case, when the video identifier and the video segment identifier have been encrypted, generating the identifier array based on the prescription identifier can make the identifier array related to the prescription information, facilitating associating the identifier array with the prescription information.

[0168] In some examples, the video identifier and the video segment identifier may not be encrypted. In some examples, the video identifier may include a prescription identifier. In some examples, the video segment identifier may include a prescription identifier.

[0169] In some examples, in step S600, an identification array may be generated based on the video identification and the video segment identification. In this case, when the video identification and the video segment identification are not encrypted, the identification array can be associated with the prescription information, which facilitates associating the identification array with the prescription information.

[0170] In some examples, the processing end 103 may generate an identification array and transmit the identification array to the service end 104 .

[0171] In some examples, in step S700, the identification array can be associated with the prescription information. In this case, the prescription information can be made to correspond to the monitoring video and multiple monitoring video segments respectively, and the monitoring video segments corresponding to multiple dispensing links can be quickly located using the prescription information as a search condition, thereby realizing the visualization of each dispensing link in the automatic dispensing process, and facilitating the recording of each dispensing link in the dispensing process, thereby facilitating the backtracking and verification of the automatic dispensing process, improving the efficiency of the backtracking and verification, and improving the transparency and credibility of the dispensing process.

[0172] In some examples, the server 104 may mount the identification array after the data of the prescription information, that is, associate the identification array with the prescription information.

[0173] In some examples, the monitoring system 10 may include a recording end 102 , a processing end 103 , and a service end 104 .

[0174] In some examples, the video recording terminal 102 may be configured to obtain a surveillance video corresponding to the prescription information during the automatic dispensing process. In some examples, the prescription information may include a unique prescription identifier for characterizing the prescription information.

[0175] In some examples, the video recording end 102 may include a camera or other video acquisition device. In this case, the video recording end 102 can obtain the monitoring video corresponding to the prescription information during the automatic dispensing process for storage.

[0176] In some examples, the video recording end 102 may include video recording software, so that the camera or other image acquisition device of the video recording end 102 can be controlled by the video recording software.

[0177] In some examples, the processing end 103 may be configured to obtain a video identifier that matches the surveillance video based on the surveillance video. In some examples, the video identifier may include a first time identifier and a prescription identifier for representing the surveillance moment of the surveillance video.

[0178] In some examples, the processing end 103 can be configured to associate the prescription information with the surveillance video based on the video identifier, and segment the surveillance video associated with the prescription information to obtain multiple surveillance video segments. In some examples, the multiple surveillance video segments can correspond one-to-one to multiple dispensing links in the automatic dispensing process.

[0179] In some examples, the processing end 103 may include a host computer and host computer software. In some examples, the host computer may be a computer for implementing the functions of the processing end 103. In some examples, the host computer software may be software for implementing the functions of the processing end 103. In some examples, the host computer software may be stored and run on the host computer 104.

[0180] In some examples, the processing end 103 may also be configured to obtain a video segment identifier that matches the surveillance video segment based on the surveillance video segment.

[0181] In some examples, the processing end 103 may generate an identification array based on the prescription identification, the video identification, and the video segment identification.

[0182] In some examples, the processing end 103 may transmit data such as monitoring video segments, video segment identifiers, target images, and identifier arrays to the server end 104 .

[0183] In some examples, the processing end 103 can read data on the service end 104 .

[0184] In some examples, the processing end 103 can read and query the prescription information. In some examples, after the service end 104 associates the identification array with the prescription information, the processing end 103 can use the prescription information including the prescription identification as a search condition to quickly locate the monitoring video segments corresponding to multiple dispensing links. In some examples, the processing end 103 can provide functions such as video playback, pause, fast forward, and fast rewind. This can facilitate the backtracking and verification of the automatic dispensing process, and can improve the transparency and credibility of the dispensing process.

[0185] In some examples, the processing end 103 can be connected to an external information system, such as a hospital information system, a cloud storage center, or a cloud computing center, thereby enabling data transmission and sharing.

[0186] In some examples, the processing end 103 can identify and verify the drugs in the surveillance video through image processing technology, thereby further improving the safety of drug dispensing.

[0187] In some examples, the server 104 may be configured to associate the identification array with the prescription information, thereby enabling the prescription information to correspond to the surveillance video and the plurality of surveillance video segments, respectively.

[0188] In some examples, the server 104 may include one or more servers, such as 1, 2, 3, 4, 5, 10, etc., which are not limited here, and the number of servers can be configured according to actual needs.

[0189] In some examples, server 104 may include video recording software.

[0190] In some examples, the server 104 may include a data storage device, such as a mobile hard disk, an optical disk, or a memory card.

[0191] In some examples, the server 104 may store data such as prescription information, configuration files, surveillance videos, video identifiers, surveillance video segments, video segment identifiers, target images or identifier arrays.

[0192] In some examples, the server 104 may generate a video identifier. In some examples, the server 104 may generate a video identifier according to the number of cameras and transmit the video identifier to the processing end 103 .

[0193] In some examples, the server 104 may encrypt the prescription information to generate a corresponding prescription identifier, thereby protecting data security.

[0194] Figure 8 1 is a block diagram showing a monitoring system 10 for an automatic medication dispensing process according to an example of the present disclosure.

[0195] For some examples, see Figure 8 , the monitoring system 10 may further include a sensor module 801 .

[0196] In some examples, the sensor module 801 can detect abnormal situations and alarm. Abnormal situations may include, for example, the bottle cap of the medicine bottle is not opened, the medicine bottle is not taken, and the wrong medicine is taken. Thus, it is possible to assist in monitoring the automatic dispensing system 20. In some examples, the processing end 103 can process the alarm record transmitted by the sensor module 801 and upload it to the service end 104. In some examples, the processing end 103 can quickly retrieve the alarm record of the corresponding dispensing link according to the prescription information. In this case, it is easy to trace back and verify the automatic dispensing process, thereby improving the efficiency of tracing back and verification, and then improving the transparency and credibility of the dispensing process.

[0197] For some examples, see Figure 8 , the monitoring system 10 may further include a router 802 .

[0198] In some examples, router 802 can perform IP sniffing to check the number of cameras.

[0199] The example of the present disclosure also discloses an electronic device, including a processor and a memory. The processor executes a program stored in the memory to implement one or more steps in the above processing method.

[0200] The examples of the present disclosure also disclose a computer-readable storage medium, which can store at least one instruction, and when the at least one instruction is executed by a processor, one or more steps in the above-mentioned processing method are implemented.

[0201] The present disclosure relates to a processing method for an automatic dispensing process, which is used to process a monitoring video in the automatic dispensing process. Wherein step S100 can obtain a monitoring video corresponding to the prescription information in the automatic dispensing process. Step S200 can obtain a video identifier that matches the monitoring video. Step S300 can associate the prescription information and the monitoring video. In this way, the prescription information and the monitoring video of the automatic dispensing process can be matched one by one. Step S400 can obtain multiple monitoring video segments that correspond one by one to multiple dispensing links in the automatic dispensing process. Step S500 can obtain a video segment identifier that matches the monitoring video segment. In this case, indexing the monitoring video segment through the video segment identifier can facilitate the retrieval of the monitoring video segments corresponding to each dispensing link of the prescription information. Step S600 can generate an identifier array based on the prescription identifier, the video identifier, and the video segment identifier. Step S700 can associate the identifier array with the prescription information. In this way, the prescription information can correspond to the monitoring video and the multiple monitoring video segments respectively.

[0202] Through the processing method provided by the present invention, it is possible to quickly locate the monitoring video segments corresponding to multiple dispensing links by using prescription information including prescription identification as a search condition, thereby realizing the visualization of each dispensing link in the automatic dispensing process, and facilitating the recording of each dispensing link in the dispensing process. Therefore, it is possible to facilitate the backtracking and verification of the automatic dispensing process, which can improve the efficiency of backtracking and verification, and improve the transparency and credibility of the dispensing process.

[0203] The monitoring system 10 involved in the present disclosure includes a recording end 102, a processing end 103 and a service end 104. The recording end 102 can obtain the monitoring video corresponding to the prescription information in the automatic dispensing process. The processing end 103 can obtain the video identifier matching the monitoring video based on the monitoring video, associate the prescription information and the monitoring video based on the video identifier, and segment the monitoring video associated with the prescription information to obtain multiple monitoring video segments, obtain the video segment identifier matching the monitoring video segment based on the monitoring video segment, and generate an identifier array based on the prescription identifier, the video identifier, and the video segment identifier. The server 104 can associate the identifier array with the prescription information.

[0204] Through the monitoring system 10 involved in the present disclosure, it is possible to record monitoring videos corresponding to prescription information, read and query prescription information, and quickly locate monitoring video segments corresponding to multiple dispensing links using prescription information including prescription identification as a search condition. The processing end 103 can provide functions such as video playback, pause, fast forward, and fast rewind, thereby facilitating the backtracking and verification of the automatic dispensing process, and improving the transparency and credibility of the dispensing process.

[0205] Various methods and techniques described above provide many ways to realize the present disclosure. Of course, it should be understood that it is not necessary to realize all the described goals or advantages according to any specific example described in the present disclosure. Therefore, for example, those skilled in the art will recognize that the method described in the present disclosure can be realized in a way that realizes or optimizes an advantage or a group of advantages as taught by the present disclosure, without realizing other goals or advantages that the present disclosure may teach or inspire. In addition, those skilled in the art will recognize the applicability of various features from different examples. Similarly, the various elements, features and steps discussed above and other known equivalents of each such element, feature or step can be mixed and matched by those of ordinary skill in the art to perform the method according to the principle described in the present disclosure.

Claims

1. A processing method for an automatic dispensing process is a processing method for processing a monitoring video in an automatic dispensing process, characterized in that: include: Acquire a monitoring video corresponding to prescription information during the automatic dispensing process, wherein the prescription information includes a prescription identifier for uniquely representing the prescription information; Acquire a video identifier that matches the surveillance video based on the surveillance video, the video identifier including the prescription identifier and a first time identifier for representing a surveillance moment of the surveillance video; Associating the prescription information with the surveillance video based on the video identifier; Segmentally intercepting the monitoring video associated with the prescription information to obtain a plurality of monitoring video segments, wherein the plurality of monitoring video segments correspond one to one to a plurality of dispensing links in the automatic dispensing process; Acquire a video segment identifier that matches the surveillance video segment based on the surveillance video segment; Generate an identification array based on the prescription identification, the video identification and the video segment identification; and The identification array is associated with the prescription information.

2. The processing method for automatic medication dispensing process according to claim 1, characterized in that: Acquiring the surveillance video includes: Check whether the video service is turned on; In response to the video service being turned on, checking the number of cameras used to capture the surveillance video; In response to the number of the cameras satisfying a preset condition and based on the prescription identification received for the first time, controlling the cameras to start video monitoring of the automatic medication dispensing process; and Based on the prescription identification received again, the camera is controlled to end the video monitoring of the automatic medication dispensing process.

3. The processing method for automatic medication dispensing process according to claim 2, characterized in that: There are multiple cameras, and the video identifier also includes the camera position identifier of the camera.

4. The processing method for automatic medication dispensing process according to claim 1, characterized in that: Obtaining the multiple surveillance video segments includes: Based on the start time of the automatic dispensing process corresponding to the prescription information as the first time mark, the initial time period of each dispensing link is obtained based on the first time mark and the dispensing speed of each dispensing link; Intercepting a plurality of initial pictures corresponding to the initial time period in the monitoring video, and obtaining at least one target picture based on the plurality of initial pictures and at least one pre-stored picture, wherein the pre-stored picture is a picture corresponding to the start time or end time of each of the dispensing links that has been calibrated; Obtaining the target time period of each dispensing link based on the target time of the target image, wherein the target time is the monitoring time corresponding to the target image; and The surveillance video is segmented and intercepted based on the target time period to obtain the plurality of surveillance video segments.

5. The processing method for automatic medication dispensing process according to claim 4, characterized in that: Obtaining the target time period includes: Comparing each of the initial images with the pre-stored images to obtain a similarity between each of the initial images and the pre-stored images; In response to the similarity being the highest and being not less than a preset threshold, taking the initial picture corresponding to the similarity being the highest and being not less than a preset threshold as the target picture and recording the target moment corresponding to the target picture; and The target time period is obtained based on the target time.

6. The processing method for automatic medication dispensing process according to claim 4 or 5, characterized in that: At least one of the target images is used as a cover thumbnail of each of the surveillance video segments, and multiple surveillance video segments are thumbnailed to the same page.

7. The processing method for automatic medication dispensing process according to claim 1, characterized in that: The prescription information also includes search keywords for each dispensing link, which are encrypted based on the prescription identifier, the video identifier, a second time identifier for representing the monitoring moment of the monitoring video segment, and a random number to obtain the video segment identifier corresponding to the prescription information.

8. A system for automatic medication dispensing process, which is a monitoring system for processing monitoring video during the automatic medication dispensing process, characterized in that: Including recording end, processing end and service end; The video recording end is configured to obtain monitoring video corresponding to the prescription information during the automatic medication dispensing process; The prescription information includes a unique prescription identifier for characterizing the prescription information; The processing end is configured to obtain a video identifier matching the surveillance video based on the surveillance video, wherein the video identifier includes a first time identifier for representing a monitoring moment of the surveillance video and the prescription identifier; The processing end is configured to associate the prescription information with the monitoring video based on the video identifier, and segmentally intercept the monitoring video associated with the prescription information to obtain a plurality of monitoring video segments, wherein the plurality of monitoring video segments correspond one-to-one to a plurality of dispensing links in the automatic dispensing process; The processing end is further configured to obtain a video segment identifier matching the surveillance video segment based on the surveillance video segment, and generate an identifier array based on the prescription identifier, the video identifier, and the video segment identifier; The server is configured to associate the identification array with the prescription information.

9. An electronic device, characterized in that: The electronic device comprises a processor and a memory, and the processor executes a program stored in the memory to implement the processing method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed by a processor, the processing method according to any one of claims 1 to 7 is implemented.

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