A ward multi-bed linkage intelligent intravenous fluid replacement system

Abstract

The present application relates to the technical field of intelligent nursing in smart hospital, and specifically discloses a multi-bed linkage intelligent intravenous fluid replacement system in ward, which comprises a liquid replacement host, a mobile chassis, a mechanical arm, a servo clamp, an infusion rod exchanger, a liquid carrying station, a self-adaptive floating docking mechanism, a pipeline pressure relief separation mechanism, a disinfectant spray head, a disinfectant bottle, an intelligent bedside cabinet, a display, a pressure sensor, a HIS hospital network module and a unified data scheduling hub; the liquid replacement host is installed on the upper part of the mobile chassis, and the mobile chassis realizes autonomous walking navigation in the whole machine ward. The present application is a one-to-N multi-bed linkage full-automatic intelligent drug replacement robot system, which forms a new technical solution scheme of full-process intelligentization, safety and low cost for the technical defects and clinical application pain points of the existing bedside infusion and drug replacement automation equipment, and has outstanding innovation value and clinical landing advantages in the field of intelligent nursing equipment.

Description

Technical Field

[0001] This invention relates to the field of intelligent nursing technology in smart hospitals, specifically to an intelligent intravenous fluid exchange system that links multiple beds in a ward. Background Technology

[0002] With the rapid advancement of digital nursing in smart hospitals, various intelligent infusion auxiliary devices have been widely applied in clinical practice. Infusion dressing changes are a basic nursing operation with extremely high frequency in inpatient wards. In the traditional model, this was entirely done manually by nursing staff. Nurses needed to travel between different beds to verify patient information, observe the remaining infusion volume, perform tube removal, disinfect the interface, and re-puncture and reconnect the entire procedure, which consumed a lot of nursing manpower. In scenarios with a large number of patients and infusion beds in the ward, nurses had a heavy workload and were prone to fatigue, which in turn led to nursing safety hazards such as dressing changes on the wrong bed, drug splashing, blood backflow into the tubing, and interface contamination.

[0003] Existing intelligent infusion devices are mainly divided into four categories, but all have significant technical defects and cannot achieve safe and fully automated bedside dressing changes. The existing related equipment mainly falls into four categories: First, medication dispensing robots in the intravenous compounding center, used only for pharmacy medication dispensing, unable to perform bedside dressing changes in wards; Second, medical logistics robots, used only for material transport, lacking mechanical actuation structures and unable to perform dressing changes; Third, intelligent infusion monitoring equipment, only possessing infusion monitoring and alarm functions, lacking active dressing change capabilities; Fourth, simple bedside mechanical devices, only capable of simple insertion and removal on a single bed, lacking tubing pressure relief structures, easily causing medication splashing, backflow, and contamination, and only supporting one-to-one operations, resulting in low equipment utilization and high costs. Existing technologies also have several shortcomings: lack of big data intelligent scheduling and multi-dimensional identity verification mechanisms, leading to high dressing change safety risks; lack of tubing pressure relief and adaptive docking structures, resulting in insufficient safety and stability of automated operations; lack of multi-bed collaborative operation modes, leading to high equipment costs and low utilization; and lack of a full-process data traceability and quality control system, making it difficult to meet the clinical and quality control requirements of smart nursing. Most existing automated bedside infusion devices on the market adopt a one-to-one configuration, with one device corresponding to one bed. Dozens of beds in a ward require dozens of devices, resulting in high hardware procurement and maintenance costs and significant resistance to hospital implementation. Furthermore, the simple mechanical structure of abruptly disconnecting the tubing can cause medication to splash out, create negative pressure leading to venous backflow, and expose the infusion interface to environmental contaminants, failing to meet aseptic infusion nursing procedures. Additionally, relying solely on voice verification for patient identification is prone to misinterpretation, posing a significant risk of medical errors such as incorrect medication changes or wrong bed assignments. Therefore, we propose a multi-bed, interconnected intelligent intravenous infusion system for wards. Summary of the Invention

[0004] The purpose of this invention is to provide a multi-bed linkage intelligent intravenous fluid exchange system for wards, addressing the shortcomings of existing intelligent infusion devices (categorized as medication dispensing robots, logistics robots, infusion monitoring equipment, and simple bedside mechanical devices) mentioned in the background section. These devices all suffer from significant technical deficiencies, failing to achieve safe and fully automated bedside medication exchange. Existing equipment generally lacks big data scheduling and multi-identity verification mechanisms, as well as tubing depressurization and adaptive docking structures. Most operate on a one-to-one basis with a single bed, resulting in low equipment utilization and high costs. Furthermore, traditional methods of forcibly removing tubing are prone to medication splashing, backflow, and interface contamination. Voice verification has low error tolerance and a high risk of error, and lacks a full-process quality control and traceability system, making it difficult to meet the needs of intelligent clinical nursing.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a multi-bed linkage intelligent intravenous fluid exchange system for wards, comprising a fluid exchange main unit and an intelligent bedside cabinet, and further comprising:

[0006] Medication replacement module, which replaces infusion bottles, is connected to the smart bedside table;

[0007] The docking module connects the liquid replacement unit to the smart bedside table. The docking module holds the empty IV bottle on the smart bedside table and the new IV bottle on the liquid replacement unit.

[0008] The disinfection module is installed between the medicine replacement module and the smart bedside table. The disinfection module disinfects the medicine replacement module.

[0009] The detection module is installed in the smart bedside table and detects the input status of the medicine in the infusion tubing.

[0010] The early warning module is installed on one side of the smart bedside table. The early warning module will send an alert to the dressing robot after the detection module sends an abnormal signal.

[0011] Furthermore, the disinfection module includes a disinfectant nozzle installed on the medication replacement module. The disinfectant nozzle is connected to the disinfectant bottle through a pipe. The disinfectant nozzle disinfects the infusion bottle opening where the infusion needle will be inserted after the infusion needle is removed from the medication replacement module and before the infusion needle is inserted.

[0012] Furthermore, the detection module includes a display installed on the smart bedside table and a liquid replacement host. A pressure sensor is installed on the infusion tubing, and the infusion signal detected by the pressure sensor is directly reflected on the display and the liquid replacement host.

[0013] Furthermore, the early warning module includes a HIS hospital intranet module, which is connected to a unified data scheduling center. When the pressure sensor detects an abnormality in the medication input, the unified data scheduling center, the HIS hospital intranet module, the medication replacement host, and each smart bedside cabinet form a one-to-N distributed collaborative operation architecture. A single medication replacement host can correspond to multiple smart bedside cabinets to complete the fully automated medication replacement operation for multiple beds in rotation.

[0014] Furthermore, the unified data scheduling center has a built-in automatic task scheduling system based on the hospital's HIS medical order big data, which can obtain medical order data, infusion duration data, patient bed information, and historical dressing change frequency big data from the HIS hospital intranet module.

[0015] Furthermore, the unified data scheduling center can automatically analyze the infusion progress in the ward, autonomously generate dressing change task queues, optimize the driving path of the mobile chassis, and allocate the rotation order of N beds, so as to realize the transformation of dressing change tasks from manual triggering to a big data prediction-driven operation mode.

[0016] Furthermore, the unified data scheduling center incorporates a four-dimensional data cross-verification mechanism for patient identity, which includes bedside table hardware ID encoding data, RFID radio frequency identification data, visual QR code scanning data, and HIS medical order backend data.

[0017] Furthermore, the unified data scheduling center has the functions of closed-loop data collection throughout the entire process, medical big data traceability, and early warning of nursing risks. It can collect whole machine operation data to generate quality control logs, and identify high-risk working conditions and output early warning prompts based on ward nursing data.

[0018] This invention has at least the following beneficial effects:

[0019] This invention is a multi-bed linkage intelligent intravenous fluid change system for wards. Addressing the technical deficiencies and clinical application pain points of existing automated bedside infusion and dressing change equipment, it forms a novel technical solution that is intelligent, safe, and low-cost throughout the entire process, possessing outstanding innovative value and clinical application advantages in the field of smart nursing equipment. This invention is equipped with a HIS hospital intranet module and a unified data scheduling center, deeply integrating with the hospital's medical order big data. It can automatically analyze core data such as infusion duration, bed information, and dressing change frequency, autonomously predict the infusion progress in the ward, intelligently generate dressing change task queues, and optimize equipment travel paths and multi-bed operation sequences. This completely changes the traditional clinical operation mode of manually issuing and arranging dressing change tasks, eliminating the need for nurses to manually arrange each task, effectively streamlining nursing workflows, significantly freeing up ward nursing manpower, significantly reducing nurses' daily workload, and helping hospitals achieve intelligent and burden-reducing upgrades in nursing work. In terms of medical safety and prevention, this invention innovatively sets up a four-dimensional data cross-verification mechanism for patient identity, completely abandoning the inefficient and high-risk mode of traditional single voice verification. It integrates four types of data—equipment hardware coding, radio frequency identification, visual scanning, and back-end medical orders—for multiple cross-comparisons, achieving a three-in-one accurate verification of physical bed location, equipment connection, and patient medical order information. The dressing change mechanical action can only be initiated when the information is completely matched. From the dual dimensions of software logic and hardware recognition, it completely avoids the potential medical errors such as wrong bed, wrong medication, and wrong medication change, comprehensively improving the safety and standardization of bedside infusion treatment for patients. At the core mechanical operation level, this invention features a unique medical tubing pressure relief and separation mechanism, establishing a standardized operating logic of "pressure relief first, separation later." This overcomes the drawbacks of traditional equipment that forcibly pulls out tubing. It releases residual internal pressure before disconnecting the tubing and completes physical separation only after the tubing returns to normal pressure. This mechanically solves long-standing industry problems in automated clinical dressing changes, such as medication splashing, venous blood return from patients, and contamination of infusion interfaces. The entire operation strictly adheres to aseptic infusion nursing standards and meets the core requirements of hospital infection control. Simultaneously, the equipment is equipped with an adaptive floating docking mechanism. Through a conical coarse guide combined with a precise positioning pin hole floating composite structure, it can accommodate minor positioning deviations during the movement of the mobile chassis, achieving unmanned autonomous alignment, automatic correction, and locking connection. No manual alignment assistance from nursing staff is required, truly achieving fully unmanned autonomous dressing change operations. Furthermore, this invention breaks through the industry bottleneck of traditional infusion equipment operating on a one-to-one basis for a single bed. It innovatively adopts a one-to-N distributed collaborative operation architecture, where a single set of equipment can serve multiple beds in a ward in rotation. This greatly improves the overall utilization rate of intelligent dressing change equipment, effectively solves the problems of redundant configuration and resource waste of traditional equipment, and significantly reduces the hardware procurement, deployment, and subsequent maintenance costs of hospital smart ward transformation, making it more widely applicable.Simultaneously, the system can collect, record, store in the cloud, and trace the entire process of dressing changes, including equipment operating parameters, mechanical motion data, and safety verification data, in real time. This enables the construction of a comprehensive nursing big data quality control system, fully meeting the core business needs of smart hospitals in infection control, nursing quality assessment, and clinical research data accumulation. Overall, this invention achieves an integrated closed-loop design encompassing big data intelligent scheduling, multi-dimensional safety verification, multi-bed collaborative operation, and medical-specific mechanical structures. Compared to existing technologies, it possesses outstanding substantive features and significant technological advancements, combining high clinical applicability, technological novelty, and industrial promotion value. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of the overall structure of the present invention;

[0021] Figure 2 This is a schematic diagram of the pressure sensor structure of the present invention;

[0022] Figure 3 This is a schematic diagram of the infusion rod exchanger structure of the present invention;

[0023] Figure 4 This is a schematic diagram of the robotic arm structure of the present invention;

[0024] Figure 5 This is a schematic diagram of the adaptive floating docking mechanism of the present invention.

[0025] In the diagram: 1. Fluid changing host; 2. Mobile chassis; 3. Robotic arm; 4. Servo clamp; 5. Infusion rod exchanger; 6. Medicine carrying station; 7. Adaptive floating docking mechanism; 8. Pipeline pressure relief and separation mechanism; 9. Disinfectant nozzle; 10. Disinfectant bottle; 11. Smart bedside table; 12. Monitor; 13. Pressure sensor; 14. HIS hospital intranet module; 15. Unified data scheduling center. Detailed Implementation

[0026] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] Please see Figures 1 to 5This invention provides a technical solution: a multi-bed linkage intelligent intravenous fluid exchange system for wards, comprising a fluid exchange host 1, a mobile chassis 2, a robotic arm 3, a servo clamp 4, an infusion rod exchanger 5, a medication carrying station 6, an adaptive floating docking mechanism 7, a pipeline pressure relief and separation mechanism 8, a disinfectant nozzle 9, a disinfectant bottle 10, an intelligent bedside table 11, a display 12, a pressure sensor 13, a HIS hospital intranet module 14, and a unified data scheduling center 15. The mobile chassis 2 is an AGV autonomous walking chassis, integrating a navigation module, an obstacle avoidance module, and a drive wheel set. Carrying the fluid exchange host 1 above, it can autonomously navigate and move in the hospital ward corridors and around the beds, avoiding obstacles such as beds, carts, and people within the ward, and travel to the target intelligent bedside table 11 docking point according to the path instructions issued by the unified data scheduling center 15.

[0028] The fluid replacement host 1 is the main cabinet of the robot, which integrates a power supply unit, control motherboard, and infusion rod exchanger 5. A robotic arm 3 is installed on the outside of the cabinet. The fluid replacement host 1 can move with the mobile chassis 2, sequentially moving to the intelligent bedside cabinets 11 of different beds to complete the dressing change, realizing a multi-bed linkage intelligent intravenous fluid replacement system in the ward. The robotic arm 3 is a multi-degree-of-freedom medical robotic arm with multiple rotary joints and a servo gripper 4 at its end. The robotic arm 3 can drive the servo gripper 4 to perform a series of precise medical operations such as clamping, insertion / removal, rotation, and spraying within a spatial range. The servo gripper 4 is a servo motor-driven gripper. The servo motor performs closed-loop torque control, which can adjust the clamping force for different sizes of bottle stoppers and infusion rods, ensuring secure clamping without damaging the infusion tubing and consumables. The servo clamp 4 integrates a pipeline pressure relief and separation mechanism 8, which includes a pressure relief branch, an electrically controlled pressure relief valve, and a pressure acquisition path. The pressure relief branch is connected to the infusion pipeline. When the infusion pipeline needs to be disconnected, the electrically controlled pressure relief valve first opens the pressure relief branch to release the residual liquid pressure in the pipeline. The pressure sensor 13 acquires the pipeline pressure and confirms that the pipeline has returned to normal pressure. Then, the servo clamp 4 performs the action of pulling out the pipeline to avoid spraying, blood backflow, and contamination caused by hard pulling.

[0029] The liquid replacement host 1 is equipped with an infusion rod exchanger 5, which is a rotatable workstation structure. Multiple modular drug solution carrying stations 6 are set on the infusion rod exchanger 5. Each drug solution carrying station 6 is equipped with an automatic docking slot and an in-situ detection sensor. The in-situ detection sensor detects in real time whether an infusion rod is placed on the station and the status of the infusion rod. The drug solution carrying station 6 is divided into a liquid-filled station and a liquid-free station. The liquid-filled station stores infusion rods filled with new drug solution, while the liquid-free station is used to store empty infusion rods that have been used for infusion.

[0030] The rotation of the infusion rod exchanger 5 can switch between liquid-filled and liquid-free workstations, providing the robotic arm 3 with materials for transferring between old and new infusion rods. The adaptive floating docking mechanism 7 is located at the base of the robotic arm 3. It consists of a tapered coarse guide sleeve and a spring-loaded, floating precision positioning pin hole. When the liquid replacement host 1 approaches the smart bedside table 11 via the mobile chassis 2, there may be a slight millimeter-level deviation in navigation and positioning. The tapered coarse guide sleeve first contacts the docking post on the smart bedside table 11. The pressure relief branch of the pipeline depressurization and separation mechanism 8 is connected to the downstream section of the bottle stopper puncturer via a three-way valve assembly. The other end of the pressure relief branch is connected to a waste liquid collection bag (capacity not less than 50mL). The electrically controlled pressure relief valve is driven by a PWM signal from the control motherboard (recommended duty cycle 30%~50%), with an opening duration set to 3~5 seconds. The pressure sensor 13 monitors the pipeline pressure in real time. When the pressure value drops to within 5mmH₂O, it is determined to be atmospheric pressure. The control motherboard outputs an unlocking signal, and the servo clamp 4 can then perform the pipeline separation action. The pressure relief branch of the pipeline depressurization and separation mechanism 8 is connected to the downstream section of the bottle stopper puncturer via a three-way valve assembly. The other end of the pipeline is connected to a waste liquid collection bag (capacity not less than 50mL); the electrically controlled pressure relief valve is driven by a PWM signal from the control motherboard (duty cycle recommended 30%~50%), and the opening time is set to 3~5 seconds; the pressure sensor 13 monitors the pipeline pressure in real time. When the pressure value drops to within 5mmH, it is determined to be atmospheric pressure, and the control motherboard outputs an unlock signal, allowing the servo clamp 4 to perform the pipeline separation action. The bottom front end of the liquid replacement host 1 is equipped with 2~4 conical coarse guide sleeves, corresponding to the smart bedside table. 11. Two to four docking posts are set on the side, and the cone angle of the inner wall of the guide sleeve is 15° to 30°. When the liquid replacement host 1 is driven into position, the conical guide sleeve 101 first contacts the conical surface of the docking post 201 to complete the coarse guidance. Subsequently, the floating pin hole 102 automatically corrects and locks under the action of spring preload (0.5 to 2N recommended) to perform the initial guidance. The floating pin hole further corrects the deviation and automatically completes the alignment and locking. There is no need for manual adjustment, so as to realize the reliable physical connection between the robot and the smart bedside table 11.

[0031] The disinfectant nozzle 9 is positioned on the servo clamp 4 and is connected to the disinfectant bottle 10 via a flexible tube. The disinfectant bottle 10 stores medical interface disinfectant. After the infusion tubing is separated by the servo clamp 4, the robotic arm 3 rotates to position the disinfectant nozzle 9 so that it is aimed at the infusion bottle connector and sprays disinfectant to disinfect the interface. After a short period of stillness to allow the disinfectant to dry, the infusion tubing is then inserted into the bottle stopper to ensure the interface is sterile.

[0032] Each infusion bed in the ward is equipped with a smart bedside table 11. The smart bedside table 11 is equipped with a display 12 and a pressure sensor 13. The display 12 shows patient information, medication change progress, and nursing alerts. The pressure sensor 13 monitors real-time pressure changes within the infusion tubing, and the collected data is transmitted back to the unified data dispatch center 15. The smart bedside table 11 has a built-in hardware ID encoding chip and also integrates an RFID identification module and a QR code identification module for identity information collection and verification.

[0033] The Unified Data Scheduling Center 15 is the core of the system's software scheduling. It connects to the HIS hospital intranet module 14 via network communication and wirelessly connects to each fluid changing host 1 and all smart bedside cabinets 11 in the ward. The Unified Data Scheduling Center 15 integrates four major software functional modules: an automatic task scheduling module based on HIS medical order big data, a four-dimensional data cross-validation patient identity verification module, a closed-loop data acquisition and medical big data traceability module for the entire process of mechanical motion, and a multi-bed ward nursing big data analysis and early warning module. The automatic task scheduling module based on HIS medical order big data: The system reads inpatient medical orders, infusion drug information, estimated infusion duration, bed number, and historical dressing change frequency from HIS hospital intranet module 14; The system continuously calculates the remaining infusion progress of each bed, predicts dressing change time nodes, and automatically generates dressing change task queues; Based on the distribution of beds in the ward, the current position of the robot, and the ward access conditions, it autonomously plans the driving path of the mobile chassis 2, automatically allocates the order of operations for each bed, and does not require nurses to manually create tasks. The dressing change work is started by big data prediction.

[0034] The four-dimensional data cross-referencing patient identity verification module reads four types of data sources: the first is the hardware ID code of the smart bedside table 11; the second is the patient's wristband information read by the RFID radio frequency identification of the smart bedside table 11; the third is the patient's QR code information read by visual QR code scanning; and the fourth is the patient information from the medical order backend transmitted by the HIS hospital intranet module 14. The system must cross-compare these four data items. Only after the physical bed hardware code, patient identity information, and medical order information all match will an unlock signal be output, unlocking all mechanical actions of the robotic arm 3 and servo gripper 4. If any data comparison fails, the system will directly lock all mechanical operations and output an alarm message to the monitor 12 and the nurse station terminal, completely avoiding the major medical error risks of wrong bed dressing changes and wrong medication.

[0035] The module for closed-loop data acquisition and medical big data traceability of the entire mechanical motion process: The unified data scheduling center 15 receives real-time operational data from the entire equipment, including data from the material in-situ sensor at the drug delivery station 6, clamping torque data from the servo clamp 4, pressure relief process data from the pipeline depressurization and separation mechanism 8, docking deviation displacement data from the adaptive floating docking mechanism 7, and locking status data from each locking mechanism. Every dressing change, from robot start-up, docking with the bedside table, identity verification, pressure relief, tube removal, disinfection, insertion, to completion of the procedure, is recorded and stored, automatically generating a nursing quality control log. Hospital administrators can retrieve the complete record of each dressing change at any time for infection control verification, nursing quality statistical analysis, adverse event tracing, and simultaneously accumulate real-world ward infusion operation big data for clinical research. Multi-bed ward nursing big data analysis and early warning module: The unified data scheduling center 15 continuously summarizes the data reported by each smart bedside cabinet 11, including the frequency of patient calls, abnormal infusion line pressure, bedside interaction behavior, and duration of each dressing change cycle; it constructs a big data database of infusion nursing for the entire ward; the system algorithm automatically identifies high-frequency dressing change beds, critically ill and high-risk patients, abnormal infusion flow rate, abnormal line pressure, and other conditions, generating early warnings of nursing risks. The warning information is pushed to the nurse station and the display 12 of the corresponding smart bedside cabinet 11 to remind nursing staff to pay close attention and improve the level of intelligent nursing management in the entire ward.

[0036] The workflow of this invention:

[0037] S1. The unified data scheduling center 15 continuously reads the infusion order data of all inpatients in the ward from the HIS hospital intranet module 14, calculates the infusion progress of each bed, predicts the beds where the infusion is about to end, automatically generates a dressing change task queue, and plans the driving path of the mobile chassis 2. The system can intelligently control the infusion speed. The robotic arm servo clamp integrates the infusion tubing flow rate adjustment component. Combined with the tubing pressure and flow data collected by the pressure sensor 13, it matches the infusion drip rate requirements in the HIS order and automatically adjusts the flow cross-sectional area of ​​the infusion tubing to accurately match the infusion speed set by the order. At the same time, it supports nurses to manually modify the infusion flow rate parameters on the monitor 12 and the nurse station terminal. The system verifies the flow rate parameters in real time. When the safety threshold is exceeded, an audible alarm is immediately sounded and the speed adjustment action is locked.

[0038] S2, the mobile chassis 2 drives the liquid replacement host 1 to the location of the smart bedside table 11 corresponding to the target hospital bed.

[0039] S3. The liquid replacement host 1 approaches the smart bedside table 11 and uses the adaptive floating docking mechanism 7 to complete the automatic alignment and locking connection between the robot body and the smart bedside table 11.

[0040] S4. The system initiates four-dimensional data cross-verification of patient identity; reads the hardware ID code of the smart bedside table 11, obtains patient identity information through RFID and visual QR code, and cross-compares it with the HIS medical order backend data; after all comparisons are correct, the system unlocks the robotic arm 3 and servo clamp 4; if the verification fails, an alarm is triggered, and all mechanical operations are terminated.

[0041] S5. After unlocking, the robotic arm 3 drives the servo clamp 4 to move to the infusion rod position, and the servo clamp 4 holds the bottle stopper puncture device assembly; the pipeline pressure relief separation mechanism 8 is activated, first opening the pressure relief branch, and the pressure sensor 13 monitors the pipeline pressure in real time, waiting for the internal pressure of the infusion pipeline to be completely released and become normal pressure.

[0042] S6. After confirming the normal pressure of the pipeline, the servo clamp 4 performs a separation action to pull the old bottle stopper puncturist out of the infusion bottle mouth, and the robotic arm 3 places the removed empty infusion rod into the empty station of the drug liquid carrying station 6.

[0043] S7, the infusion rod exchanger 5 rotates the workstation plate, the liquid carrying workstation 6 switches the workstation position, and rotates the liquid-containing workstation with the new liquid infusion rod to the material-collecting position of the robotic arm 3.

[0044] S8. The robotic arm 3 drives the servo clamp 4 to grab the new bottle stopper puncture device assembly on the liquid station; rotate the robotic arm 3, align the disinfectant spray head 9 next to the servo clamp 4 with the connector area of ​​the infusion bottle to be inserted, start the disinfectant spray head 9, spray disinfectant to disinfect the interface, and let it stand for the preset disinfection time.

[0045] S9. After disinfection is completed, the servo clamp 4 drives the bottle stopper puncture device to align with the infusion bottle opening and complete the insertion, establishing a new infusion pathway; the pressure sensor 13 detects the pressure of the infusion pathway to confirm that the infusion pathway is established normally.

[0046] S10. The entire dressing change operation is completed, and the adaptive floating docking mechanism 7 is released from its lock. The mobile chassis 2 drives the liquid replacement host 1 to detach from the current smart bedside table 11. The mobile chassis 2 is equipped with a ward inspection module, which can automatically carry out ward inspections according to a preset ward route during dressing change tasks. It is equipped with a vision acquisition component to collect the ward environment and the status of the surrounding beds, and transmit the ward images back to the nurse station to assist nurses in remotely observing the patients in the ward. It can conduct timed cyclic inspections or receive instructions from the nurse station to start fixed-point inspection tasks. During the inspection, it does not disturb the patients' rest and can automatically avoid people and obstacles in the ward. The unified data scheduling center 15 saves and archives all data of this dressing change process to generate a quality control log. The system reads the task queue to determine whether there are still beds to be dressed. If there are, the mobile chassis 2 moves to the next target smart bedside table 11 and repeats the entire dressing change process, realizing a single robot to perform one-to-many operations for multiple beds. Equipped with material transportation capabilities, the liquid replacement main unit cabinet features an openable and closable material storage compartment. It can undertake transportation tasks issued by the nurse station, enabling the transfer of examination reports, oral medications, and small medical consumables within the ward. It receives delivery destinations from the unified data scheduling center 15, autonomously navigates to the corresponding bed or nurse workstation, and sends a delivery signal to the HIS hospital intranet module after completing the material delivery. It supports mixed scheduling of dressing change tasks and material transportation tasks, and rationally plans task priorities.

[0047] S11. The system continuously performs big data analysis on multi-bed nursing care, identifies high-risk conditions and outputs early warnings. When all task queues are completed, the fluid replacement host 1 returns to the charging point to standby, waiting for the next batch of dressing change tasks to be triggered. The mobile chassis 2 is equipped with an intelligent environmental detection function, integrating a water leakage sensor and a smoke sensor. The robot can detect water leakage, seepage, smoke, and fire hazards in the ward in real time during its movement. When water leakage or excessive smoke is detected, a local audible alarm is immediately triggered, and the alarm location and detection data are uploaded to the unified data dispatch center and the nurse station to prompt staff to deal with environmental safety hazards in a timely manner.

[0048] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0049] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A multi-bed linkage intelligent intravenous fluid exchange system for wards, characterized in that, include: The liquid replacement unit (1) and the smart bedside table (11) also include: A medication replacement module for replacing infusion bottles, the medication replacement module being connected to a smart bedside table (11); A docking module is connected between the liquid replacement host (1) and the smart bedside table (11). The docking module holds the empty drip bottle on the smart bedside table (11) and the new drip bottle of the liquid replacement host. The disinfection module is installed between the medicine replacement module and the smart bedside table (11), and the disinfection module disinfects the medicine replacement module. The detection module is installed in the smart bedside table (11) and detects the input status of the medicine in the infusion pipeline; The early warning module is installed on one side of the smart bedside table (11). The early warning module sends an early warning to the dressing robot after the detection module sends an abnormal signal.

2. The multi-bed linkage intelligent intravenous fluid exchange system for wards according to claim 1, characterized in that: The disinfection module includes a disinfection nozzle (9) installed on the medicine replacement module. The disinfection nozzle (9) is connected to the disinfection bottle (10) through a pipe. The disinfection nozzle (9) disinfects the surface of the infusion needle and the infusion bottle where the infusion needle is to be inserted after the infusion needle is removed from the medicine replacement module and before the infusion needle is inserted.

3. The intelligent intravenous fluid exchange system for multiple beds in a ward according to claim 1, characterized in that: The detection module includes a display (12) installed on the liquid replacement host (11), and a pressure sensor (13) installed on the infusion pipeline. The infusion signal detected by the pressure sensor (13) is directly reflected on the display (12) and the liquid replacement host (1).

4. The intelligent intravenous fluid exchange system for multiple beds in a ward according to claim 1, characterized in that: The early warning module includes a HIS hospital intranet module (14), which is connected to a unified data scheduling center (15). When the pressure sensor (13) detects an abnormality in the drug input, the unified data scheduling center (15), the HIS hospital intranet module (14), the liquid replacement host (1), and each smart bedside table (11) form a one-to-N distributed collaborative operation architecture. A single liquid replacement host (1) can correspond to multiple smart bedside tables (11) to complete the fully automatic drug replacement operation for multiple beds in rotation.

5. The intelligent intravenous fluid exchange system for multiple beds in a ward according to claim 1, characterized in that: The unified data scheduling center (15) is equipped with an automatic task scheduling system based on the hospital HIS medical order big data. It can obtain big data such as medical order data, infusion duration data, patient bed information, and historical dressing frequency from the HIS hospital intranet module (14).

6. The intelligent intravenous fluid exchange system for multiple beds in a ward according to claim 1, characterized in that: The unified data scheduling center (15) can automatically analyze the infusion progress in the ward, autonomously generate a dressing change task queue, optimize the driving path of the mobile chassis (2), and allocate the rotation operation sequence of N beds, so as to realize the dressing change task from manual triggering to big data prediction-driven operation mode.

7. The intelligent intravenous fluid exchange system for multiple beds in a ward according to claim 1, characterized in that: The unified data scheduling center (15) has a built-in four-dimensional data cross-verification mechanism for patient identity. The four-dimensional data includes bedside table hardware ID encoding data, RFID radio frequency identification data, visual QR code scanning data, and HIS medical order background data.

8. The intelligent intravenous fluid exchange system for multiple beds in a ward according to claim 1, characterized in that: The unified data scheduling center (15) has the functions of closed-loop data collection throughout the process, medical big data tracing, and early warning of nursing risks. It can collect whole machine operation data to generate quality control logs, and identify high-risk working conditions and output early warning prompts based on ward nursing data.

Images