Intelligent pharmacy system integrating identification, medicine dispensing and distribution

Abstract

The invention discloses an intelligent pharmacy system integrating identification, medicine dispensing and distribution, and the system comprises a medicine positioning module which distributes a unique identifier for a medicine, and deploys a sensor network to position the position of the medicine; the warehouse management module performs warehouse-in and inventory management on the medicines based on the unique identifier, and constructs a demand prediction model to predict medicine demands; the prescription identification module can scan the prescription image, generate a prescription text, extract key information of the prescription text and convert the key information into a structured data format for storage; the intelligent medicine dispensing module receives data of the prescription identification module and completes a medicine dispensing task in combination with the medicine positioning module; and the intelligent distribution module is used for calculating the shortest or fastest path from the starting point to the ending point based on a path algorithm, and calculating the most suitable obstacle avoidance path in the shortest or fastest path so as to complete medicine distribution. The intelligent pharmacy system integrating identification, medicine dispensing and distribution is realized, the labor cost is reduced, and the efficiency of medicine storage, classification and distribution is improved.

Description

Technical Field

[0001] The present invention relates to the field of smart medical technology, and in particular to an intelligent pharmacy system integrating identification, dispensing and delivery. Background Art

[0002] In the traditional hospital pharmacy dispensing process, the storage, classification, adjustment and distribution of medicines mainly rely on manual operation and simple electronic equipment. With the rapid development of medical technology and the trend of population aging, this method has exposed many drawbacks and is difficult to adapt to the increasing demand for current medical and health services. Its drawbacks are mainly manifested in:

[0003] 1. Manual inventory management: Drug purchase, storage, and expired drug disposal all require manual management and record keeping, which has high labor costs and is prone to errors or omissions.

[0004] 2. Manual dispensing: Pharmacists manually pick, measure and package drugs according to prescriptions. This process is time-consuming, labor-intensive and prone to errors.

[0005] 3. Paper records: Pharmacists rely on paper prescriptions and records during the dispensing process. On the one hand, this is inefficient; on the other hand, it lacks integration with other hospital information systems (such as HIS systems), making it impossible to update and share patient health data and drug inventory information in real time, which means that data updating and sharing are inconvenient.

[0006] 4. On-site queuing: Patients or their agents need to queue up at the hospital pharmacy to get their medicines, which increases patients’ waiting time and the risk of cross-infection.

[0007] With the development of smart healthcare, it is crucial to study an intelligent pharmacy system. Summary of the invention

[0008] The technical problem to be solved by the present invention is how to realize an intelligent pharmacy system integrating identification, dispensing and delivery.

[0009] In order to solve the above technical problems, the present invention provides an intelligent pharmacy system integrating identification, dispensing and delivery, comprising:

[0010] A drug location module that assigns unique identifiers to drugs to identify them and deploys a sensor network to locate where the drugs are distributed in the pharmacy;

[0011] A warehouse management module, which performs warehousing and inventory management of drugs based on the unique identifier, builds a demand forecasting model to predict drug demand and intelligently replenishes stocks;

[0012] A prescription recognition module, which can scan a prescription image and generate a prescription text, extract key information of the prescription text and convert it into a structured data format for storage;

[0013] An intelligent medicine dispensing module receives valid data from the prescription identification module and completes the medicine dispensing task in combination with data from the medicine positioning module; and

[0014] The intelligent delivery module calculates the shortest or fastest path from the starting point to the end point based on the path algorithm, and calculates the most suitable obstacle avoidance path in the shortest or fastest path to complete the drug delivery.

[0015] Furthermore, the system also includes a user interaction interface, which can query drug-related information and change the data of the warehouse management module.

[0016] Furthermore, the user interaction interface can display abnormal alarm information of the drug positioning module, the warehouse management module, the prescription identification module, the intelligent dispensing module and the intelligent distribution module.

[0017] Furthermore, the sensor network in the drug positioning module includes a plurality of sensor nodes, the sensor nodes are distributed in every corner of the pharmacy, and the sensor nodes communicate wirelessly with each other.

[0018] Furthermore, the drug positioning module calculates the locations of drugs distributed in the pharmacy through RSSI positioning algorithm and triangulation positioning algorithm, wherein:

[0019] The RSSI positioning algorithm estimates the distance between the drug and the sensor node by analyzing the change in the signal strength of the sensor node;

[0020] The triangulation positioning algorithm uses the signal arrival time difference or signal arrival angle of more than three sensor nodes to calculate the position of the drug in the pharmacy.

[0021] Furthermore, the warehouse management module realizes intelligent replenishment through the demand forecasting model combined with the replenishment strategy and the preset threshold.

[0022] Furthermore, the prescription recognition module includes a prescription recognition unit and a prescription parsing unit, wherein:

[0023] The prescription recognition unit includes scanning the prescription image using OCR technology, converting the prescription image into the editable prescription text, and removing redundant information in the prescription text, wherein the redundant information includes the header information of the prescription text and the hospital logo;

[0024] The prescription parsing unit includes extracting key information from the prescription text using NLP technology, and the key information includes drug type, name, dosage, frequency of use and duration of use.

[0025] Furthermore, the intelligent dispensing module includes a prescription verification unit, an automatic dispensing unit and a dispensing inspection unit, wherein:

[0026] The prescription verification unit includes checking the integrity and accuracy of the prescription information; the integrity of the prescription information includes checking the drug information, dosage and usage; the accuracy of the prescription information includes checking whether the drug name and dosage are consistent with the drug information recorded in the warehouse management module;

[0027] The automatic dispensing unit includes a dispensing robot, which reaches the location of the required medicine according to the valid data of the medicine positioning module and the prescription verification unit, and can grab the required medicine through a manipulator;

[0028] The medicine dispensing inspection unit includes a detection component and an image recognition component. The detection component detects the weight and shape characteristics of the medicines grasped by the robot in real time; the image recognition component can take pictures and identify the prepared medicines, and judge whether the type, quantity and dosage of the medicines grasped by the robot are consistent by comparing the information of the prescription verification unit and the recognition result of the image recognition component.

[0029] Furthermore, the intelligent distribution module includes a path planning unit, a distribution execution unit and a progress monitoring unit, wherein:

[0030] The path planning unit optimizes the path algorithm by combining real-time environmental factors, wherein the real-time factors include hospital traffic conditions, ward locations, and real-time weather;

[0031] The delivery execution unit includes a delivery robot, which uses a navigation algorithm to travel according to the data provided by the path planning unit. The delivery robot is also provided with a biometric authentication and authentication alarm mechanism to confirm the identity information of the person picking up the medicine;

[0032] The progress monitoring unit includes displaying delivery progress information on the user interaction interface, and the delivery progress information includes the real-time position, status, and remaining delivery time of the delivery robot.

[0033] Furthermore, the unique identifier is an RFID tag or a QR code.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] The present invention realizes an intelligent pharmacy system integrating identification, dispensing and distribution through a drug positioning module, a warehouse management module, a prescription identification module, an intelligent dispensing module, an intelligent delivery module and a user interaction interface, thereby reducing labor costs and improving the efficiency of drug storage, classification and distribution. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 The system block diagram disclosed in the embodiment of the present invention. DETAILED DESCRIPTION

[0037] In order to make the technical scheme and technical effect of the present invention clearer, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments.

[0038] The present invention aims to provide an intelligent pharmacy system integrating identification, dispensing and delivery. Figure 1 , mainly including drug positioning module, warehouse management module, prescription recognition module, intelligent dispensing module, intelligent distribution module and user interaction interface, which are mainly introduced as follows:

[0039] 1. Drug Positioning Module

[0040] 1.1. Drug Labeling

[0041] The drug positioning module assigns a unique identifier to the drug to identify the drug; preferably, the unique identifier is an RFID tag or a QR code, and a label printer is used to print the drug information on the RFID tag or QR code.

[0042] 1.2 Real-time positioning

[0043] Sensor network: The location of drugs is tracked in real time through the sensor network deployed in the pharmacy. The sensor network consists of multiple sensor nodes, which are distributed in various corners of the pharmacy. Each sensor node has wireless communication capabilities and can send the sensed drug information to the central processing system.

[0044] Positioning algorithm: The central processing system calculates the location of drugs in the pharmacy through RSSI positioning algorithm and triangulation positioning algorithm. Specifically, RSSI positioning algorithm estimates the distance between drugs and sensor nodes by analyzing the changes in the signal strength of sensor nodes; triangulation positioning algorithm calculates the location of drugs in the pharmacy by using the signal arrival time difference or signal arrival angle of more than three sensor nodes.

[0045] 1.3. Rapid positioning

[0046] Query request: Medical staff can enter the drug name, specification, manufacturer and other information on the system user interface to initiate a query request. The central processing system will perform fuzzy matching or exact matching based on this information to find the corresponding drug.

[0047] Location query: After receiving the query request, the system will use the previously established drug information database and real-time positioning data to query the location of the drug. After calculating the specific location of the drug through the positioning algorithm, the system will display the location information to the medical staff in a graphical or textual form, so that the medical staff can quickly find the required drugs according to the guidance provided by the system.

[0048] 2. Warehouse Management Module

[0049] By installing various sensors, RFID readers and other equipment in the pharmacy, the storage status, location information, temperature and humidity of drugs are collected in real time. The collected data is processed and analyzed to predict the changing trend of drug demand and provide a decision-making basis for drug inventory adjustment.

[0050] 2.1. Warehouse management

[0051] Equipment use: When drugs are put into storage, the staff will first operate the RFID reader or scanner to scan the RFID tag or QR code on the drug packaging to quickly read the information on the tag or QR code, such as drug name, batch, production date, expiration date, etc.

[0052] Algorithm application: Once the drug information is read, the system will use the RFID recognition algorithm or QR code parsing algorithm to convert the read raw information into a data format that the system can recognize and process.

[0053] Database update: The information of newly added drugs will be automatically compared with the existing data in the inventory database to ensure the accuracy and consistency of the data; if there is new drug information or changes in the information of existing drugs, such as batch changes, expiration date updates, etc., the system will update the inventory database in real time.

[0054] 2.2 Inventory Management

[0055] Sensor application: Temperature and humidity sensors, pressure sensors and other equipment will be installed in various corners and key locations of the warehouse. These sensors can monitor the storage environment of medicines in real time to ensure that the medicines are stored under appropriate conditions.

[0056] Data collection: Sensors continuously collect environmental data and transmit the data to the data processing center via wired or wireless means. This process ensures the real-time and integrity of the data.

[0057] Data analysis: In the data processing center, the central processing system will use statistical analysis and data mining technology to analyze the collected data in order to understand the storage status of the drugs, such as whether there are problems such as expiration, moisture, pressure, etc., and take corresponding measures accordingly.

[0058] 2.3 Demand Forecasting

[0059] Data collection: In addition to inventory data, the central processing system also collects historical sales data, market trends and other information on drugs, which is an important basis for predicting drug demand.

[0060] Forecasting model: The central processing system uses time series analysis and machine learning algorithms to build a demand forecasting model based on the collected data. The demand forecasting model can analyze the patterns and trends in historical data and predict future demand based on them.

[0061] Forecast results: Based on the forecast results output by the demand forecast model, the central processing system will provide decision-making basis for inventory adjustment. For example, if it is predicted that the demand for a certain drug will increase significantly, the system can increase the inventory of the drug in advance to ensure sufficient supply.

[0062] 2.4. Intelligent replenishment

[0063] Replenishment trigger: When the inventory of a drug falls below a preset threshold, the system automatically triggers the replenishment process. This threshold is set based on the forecast results and replenishment strategy output by the demand forecasting model.

[0064] Replenishment plan: The system will formulate a detailed replenishment plan based on demand forecast results and replenishment strategies. This plan includes the types of drugs that need to be replenished, quantity, replenishment time, etc.

[0065] Replenishment execution: According to the replenishment plan, the system will send replenishment instructions to suppliers through the supply chain management system or external interface. At the same time, the system will monitor the replenishment progress and arrival status in real time to ensure that the drugs can arrive in time and be replenished to the inventory.

[0066] Through precise control of the above steps, the warehouse management module can automate and intelligently manage the entire process of drug warehousing, storage, demand forecasting and replenishment based on unique identification. This can not only improve warehouse efficiency and safety, but also reduce human errors and operating costs, providing strong support for the sustainable development of the drug supply chain.

[0067] 3. Prescription Recognition Module

[0068] 3.1 Prescription Identification Unit

[0069] OCR scanning: Use OCR technology to scan prescription images and convert them into editable prescription text.

[0070] Prescription text processing: Pre-process the prescription text generated by OCR to remove possible stains, scratches, shadows and other noise, and remove redundant information in the prescription text, including the header information of the prescription text and the hospital logo. Furthermore, through algorithm optimization and machine learning technology, the accuracy and efficiency of prescription text recognition are continuously improved.

[0071] 3.2 Prescription analysis unit

[0072] Natural Language Processing: Use NLP technology to extract key information from prescription texts. Specifically, key information includes drug type, name, dosage, frequency of use, and duration of use.

[0073] Information storage: The key information of the extracted prescription text is converted into a structured data format to facilitate computer storage and processing, and then the structured data is stored in a dedicated database to ensure data security and queryability.

[0074] 3.3 Prescription Review Unit

[0075] Review rules: Based on the medical knowledge base, formulate drug incompatibility rules to avoid adverse consequences caused by drug interactions. At the same time, set a safe dosage range for each drug to ensure that the prescribed dosage issued by the doctor is within a safe range.

[0076] Real-time review: The system automatically verifies the prescription in real time to check whether there are any incompatibility or excessive dosage, and provides real-time feedback of the review results to doctors or pharmacy staff to ensure that the prescription is compliant.

[0077] 3.4 Exception handling

[0078] Alarm mechanism: When an abnormal situation is detected, the system automatically issues an alarm and records the abnormal information.

[0079] Automatic contact: Automatically contact the doctor via SMS, email, etc. to inform the doctor of abnormal conditions. In an emergency, the system can automatically contact the pharmacist or medical expert for further review and processing.

[0080] 4. Intelligent medication module

[0081] 4.1 Prescription Verification Unit

[0082] Data interface: A stable and efficient data interface is established between the intelligent dispensing module and the prescription recognition module. This interface is responsible for receiving prescription information sent from the medical system or doctor's workstation in real time. Furthermore, the data interface supports data exchange in multiple formats to ensure that no matter where the prescription information comes from, it can be accurately transmitted to the dispensing system.

[0083] Information verification: Once the prescription information is received by the intelligent dispensing module, the system will immediately conduct strict verification on it. The verification process includes checking the completeness and accuracy of the prescription information. Specifically, the completeness of the prescription information includes checking the drug information, dosage, and usage, etc. The accuracy of the prescription information includes checking whether the drug name and dosage are consistent with the drug information recorded in the warehouse management module, etc. Any incomplete or incorrect information will result in the prescription being rejected to ensure the safety of the patient's medication.

[0084] 4.2. Automatic dispensing unit

[0085] Robot control: The automatic dispensing unit includes a dispensing robot. In the automatic dispensing process, the system controls the precise movement of the dispensing robot through the robot control algorithm. At the same time, the system will dynamically adjust the robot's working parameters according to the characteristics and needs of the medicine to achieve the best dispensing effect.

[0086] Drug grabbing: Based on the prescription information passed through the prescription verification unit, the dispensing robot reaches the location of the required drugs based on the valid data of the drug positioning module and the prescription verification unit, and can grab the required drugs through the manipulator.

[0087] 4.3. Medication inspection unit

[0088] Detection component: The detection component detects the weight and shape characteristics of the medicines grasped by the robot in real time to ensure the accuracy of grasping.

[0089] Image recognition component: The image recognition component can take pictures and identify the prepared medicines, and determine whether the type, quantity and dosage of the medicines grabbed by the robot are consistent by comparing the information of the prescription verification unit and the recognition result of the image recognition component.

[0090] Abnormal handling: If the dispensing inspection unit finds any abnormality during the inspection process, such as missing medicine, wrong dosage, etc., the system will immediately stop the dispensing process and sound an alarm. At the same time, the system will automatically record the abnormal information and notify relevant personnel to handle it, so as to ensure that the error is discovered and corrected at the first time to avoid any unnecessary risks to patients.

[0091] The intelligent dispensing module receives valid data from the prescription recognition module and completes the dispensing task in combination with the data from the drug positioning module.

[0092] 5. Intelligent delivery module

[0093] 5.1 Path Planning Unit

[0094] 5.1.1 Path Planning

[0095] The path planning unit optimizes the path algorithm by combining real-time environmental factors. The system will continuously receive data from various sensors and update the path planning in real time to ensure maximum delivery efficiency. Among them, real-time factors include hospital traffic conditions, ward locations, and real-time weather; the path algorithm can use the Dijkstra algorithm, which can calculate the shortest or fastest path from the starting point to the end point based on map information, such as road networks, sidewalks, etc. The specific setting methods of the path include the following:

[0096] Parameter setting: In the Dijkstra algorithm, the weights of different paths are set according to actual needs. For example, the weight of stairs may be higher than that of flat ground because going up and down stairs requires more time or energy consumption.

[0097] Distance weight: Set weights directly based on physical distances such as corridor length, number of staircases, etc.

[0098] Time weights: Dynamic time weights can be set to take into account elevator waiting time, corridor congestion, etc. For example, during peak hours, the weight of corridors may be increased.

[0099] Special condition weights: For example, some areas may be off-limits to the robot, or some areas may be inaccessible at certain times, such as cleaning time, and these need to be reflected in the weights.

[0100] Algorithm execution: The starting point and the end point are input into the algorithm, and the algorithm will gradually calculate the shortest or fastest path from the starting point to the end point based on the set weights and map information.

[0101] 5.1.2 Path Optimization

[0102] In path planning, various real-time factors must also be considered, such as traffic conditions (crowd congestion, etc.), ward location (to ensure that the medicine can be delivered to the patient on time), and weather conditions (such as rainy and snowy weather may affect the robot's driving speed). The system will continuously receive data from various sensors and update the path planning in real time to ensure maximum delivery efficiency, including the following:

[0103] Real-time data collection: Sensors are deployed in the hospital, such as crowd density sensors and elevator status sensors, to collect data in real time.

[0104] Video surveillance: Analyze crowd flow and predict congestion trends through video surveillance.

[0105] Historical data: Use historical data (such as daily delivery records, passenger flow statistics, etc.) to estimate future traffic conditions.

[0106] Dynamic weight adjustment: On the one hand, the weight of the edge is adjusted according to real-time data. For example, if a corridor is congested, the weight of the corridor can be temporarily increased. On the other hand, the impact of different time periods is taken into account. For example, morning is the peak time for doctors to make rounds and patients to receive treatment, and the corridors and elevators may be more congested. At this time, the weight needs to be adjusted accordingly.

[0107] Path replanning: Based on the weight adjustment and when a significant change in the environment is detected (such as elevator failure, emergency evacuation, etc.), the system should immediately trigger the path replanning plan. In addition, during the delivery process, the system can also regularly check whether a better path appears, and if so, consider whether to adjust the path.

[0108] 5.2. Delivery Execution Unit

[0109] The delivery execution unit includes a delivery robot, which uses a navigation algorithm to drive according to the data provided by the path planning unit. The delivery robot is equipped with a variety of sensors, such as lidar, ultrasonic sensors, etc., to improve the accuracy and reliability of obstacle detection. Specifically:

[0110] Robot navigation: After the path planning is completed, the delivery robot needs to navigate according to the planned path, using advanced navigation algorithms, such as SLAM (Simultaneous Localization and Mapping) technology, to control the robot's direction and speed, ensuring that the robot accurately follows the predetermined route. At the same time, during the driving process, the robot can also adjust its driving strategy in real time according to changes in the surrounding environment, such as new obstacles or road changes.

[0111] Obstacle avoidance algorithm: It adopts an efficient obstacle avoidance algorithm, which can detect obstacles around the robot in real time and calculate the most suitable obstacle avoidance path. In addition, the robot is equipped with a variety of sensors, such as lidar, ultrasonic sensors, etc., to improve the accuracy and reliability of obstacle detection.

[0112] 5.3 Progress Monitoring Unit

[0113] GPS positioning: By installing a GPS module on the delivery robot, the system can receive signals from the satellite in real time and calculate the exact location of the delivery robot. It can understand the delivery progress of the delivery robot at any time and adjust it when necessary.

[0114] Real-time monitoring: Real-time monitoring technology is used to display the delivery progress information of the delivery robot. The robot's location, status, remaining time and other information can be displayed in real time on the user interaction interface. Preferably, users can also check the delivery progress at any time through mobile phones or other terminal devices, and interact with the delivery robot, such as canceling orders, changing delivery addresses, etc. In addition, in order to solve the drug safety problem of the delivery robot during delivery, the delivery robot can be equipped with a biometric authentication and authentication alarm mechanism to confirm the identity information of the person picking up the drug, and timely alarm when there is an abnormal authentication process or mechanical damage.

[0115] The intelligent delivery module calculates the shortest or fastest path from the starting point to the end point based on the path algorithm, and calculates the most suitable obstacle avoidance path in the shortest or fastest path to complete the drug delivery.

[0116] 6. User Interface

[0117] The user interaction interface can query drug-related information and change the data of the warehouse management module; it can display abnormal alarm information of the drug positioning module, warehouse management module, prescription identification module, intelligent dispensing module and intelligent distribution module.

[0118] 6.1. Information Query: Medical staff can query based on various conditions such as drug name keywords, type, manufacturer, etc. to ensure rapid location of required drugs. At the same time, the system needs to ensure real-time update of drug inventory and location information so that medical staff can obtain the most accurate data. In addition to text information, the system can also provide a graphical display of drugs, such as photos of drugs, maps of storage locations, etc., to help medical staff understand the drug situation more intuitively.

[0119] 6.2. Instruction issuance: A concise and clear instruction interface can ensure that medical staff can easily select drugs, enter quantities, select target locations and other key information. The system should be able to automatically detect errors in instructions, such as insufficient drug inventory, non-existence of the target location, etc., and give clear error prompts to avoid misoperation. Before issuing instructions, the system should require medical staff to conduct a second confirmation to ensure the accuracy of the instructions.

[0120] 6.3. Progress monitoring: According to the different stages of the medication dispensing process, such as drug selection, quantity verification, and delivery, the system can display the progress of each stage separately, so that medical staff can have a clearer understanding of the entire process. If an abnormality occurs at a certain stage, such as delivery delays, missing drugs, etc., the system should be able to immediately remind medical staff for timely processing.

[0121] 6.4. Voice interaction: Supports voice interaction function, medical staff can easily complete the medication dispensing operation through voice commands.

[0122] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent pharmacy system integrating identification, dispensing and delivery. It is characterized in that include: A drug location module that assigns unique identifiers to drugs to identify them and deploys a sensor network to locate where the drugs are distributed in the pharmacy; A warehouse management module, which performs warehousing and inventory management of drugs based on the unique identifier, builds a demand forecasting model to predict drug demand and intelligently replenishes stocks; A prescription recognition module, which can scan a prescription image and generate a prescription text, extract key information of the prescription text and convert it into a structured data format for storage; An intelligent medicine dispensing module receives valid data from the prescription identification module and completes the medicine dispensing task in combination with data from the medicine positioning module; as well as The intelligent delivery module calculates the shortest or fastest path from the starting point to the end point based on the path algorithm, and calculates the most suitable obstacle avoidance path in the shortest or fastest path to complete the drug delivery.

2. The intelligent pharmacy system integrating identification, dispensing and delivery according to claim 1, It is characterized in that The system also includes a user interaction interface, which can query drug-related information and modify the data of the warehouse management module.

3. The intelligent pharmacy system integrating identification, dispensing and delivery according to claim 2, It is characterized in that The user interaction interface can display abnormal alarm information of the drug positioning module, the warehouse management module, the prescription identification module, the intelligent dispensing module and the intelligent distribution module.

4. The intelligent pharmacy system integrating identification, dispensing and delivery according to claim 1, It is characterized in that The sensor network in the drug positioning module includes a plurality of sensor nodes, the sensor nodes are distributed in every corner of the pharmacy, and the sensor nodes communicate wirelessly with each other.

5. The intelligent pharmacy system integrating identification, dispensing and delivery according to claim 4, It is characterized in that The drug positioning module calculates the location of drugs in the pharmacy through RSSI positioning algorithm and triangulation positioning algorithm, where: The RSSI positioning algorithm estimates the distance between the drug and the sensor node by analyzing the change in the signal strength of the sensor node; The triangulation positioning algorithm uses the signal arrival time difference or signal arrival angle of more than three sensor nodes to calculate the position of the drug in the pharmacy.

6. The intelligent pharmacy system integrating identification, dispensing and delivery according to claim 1, It is characterized in that The warehouse management module realizes intelligent replenishment through the demand forecasting model combined with replenishment strategy and preset thresholds.

7. The intelligent pharmacy system integrating identification, dispensing and delivery according to claim 1, It is characterized in that The prescription recognition module includes a prescription recognition unit and a prescription parsing unit, wherein: The prescription recognition unit includes scanning the prescription image using OCR technology, converting the prescription image into the editable prescription text, and removing redundant information in the prescription text, wherein the redundant information includes the header information of the prescription text and the hospital logo; The prescription parsing unit includes extracting key information from the prescription text using NLP technology, and the key information includes drug type, name, dosage, frequency of use and duration of use.

8. The intelligent pharmacy system integrating identification, dispensing and delivery according to claim 1, It is characterized in that The intelligent dispensing module includes a prescription verification unit, an automatic dispensing unit and a dispensing inspection unit, wherein: The prescription verification unit includes checking the integrity and accuracy of the prescription information; the integrity of the prescription information includes checking the drug information, dosage and usage; the accuracy of the prescription information includes checking whether the drug name and dosage are consistent with the drug information recorded in the warehouse management module; The automatic dispensing unit includes a dispensing robot, which reaches the location of the required medicine according to the valid data of the medicine positioning module and the prescription verification unit, and can grab the required medicine through a manipulator; The medicine dispensing inspection unit includes a detection component and an image recognition component. The detection component detects the weight and shape characteristics of the medicines grasped by the robot in real time; the image recognition component can take pictures and identify the prepared medicines, and judge whether the type, quantity and dosage of the medicines grasped by the robot are consistent by comparing the information of the prescription verification unit and the recognition result of the image recognition component.

9. The intelligent pharmacy system integrating identification, dispensing and delivery according to claim 2, It is characterized in that The intelligent distribution module includes a path planning unit, a distribution execution unit and a progress monitoring unit, wherein: The path planning unit optimizes the path algorithm by combining real-time environmental factors, wherein the real-time factors include hospital traffic conditions, ward locations, and real-time weather; The delivery execution unit includes a delivery robot, which uses a navigation algorithm to travel according to the data provided by the path planning unit. The delivery robot is also provided with a biometric authentication and authentication alarm mechanism to confirm the identity information of the person picking up the medicine; The progress monitoring unit includes displaying delivery progress information on the user interaction interface, and the delivery progress information includes the real-time position, status, and remaining delivery time of the delivery robot.

10. The intelligent pharmacy system integrating identification, dispensing and delivery according to claim 1, It is characterized in that The unique identifier is an RFID tag or a QR code.

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