Hospital hazardous chemical substance storage and use management and control system and method based on Internet of Things

Abstract

The invention discloses a hospital hazardous chemical substance storage and use management and control system and method based on the Internet of Things, which identify and record the pick-and-place of hazardous chemical substances and record the amount change of the hazardous chemical substances each time, do not need manual registration and inventory operation, and realize the traceability of the storage and use of the hazardous chemical substances. The system is suitable for full-process management and control of'storage-taking-use-storage 'of high-risk hazardous chemical substances such as anesthetic drugs, flammable and explosive reagents and highly toxic medical reagents in a hospital scene, integrates real-time data acquisition and digital twinborn risk assessment of an Internet of Things terminal, and realizes accurate tracing and safety early warning of the hospital hazardous chemical substances. The system comprises an Internet of Things terminal module, a hazardous chemical substance information acquisition module, a storage temperature analysis module, a normal monitoring analysis module, a storage risk analysis module, a digital twin modeling module and a storage management information output module.

Description

Technical Field

[0001] This invention relates to the field of hospital hazardous chemical safety management technology, specifically to an Internet of Things-based hospital hazardous chemical storage and management system and specific management methods. Background Technology

[0002] Hospital hazardous chemicals management is a core aspect of medical safety, involving anesthetic drugs, flammable and explosive reagents for disinfection, and highly toxic substances for pathological testing. Its control must meet the requirements of a medical scenario characterized by "full-process traceability, strict access control, and efficient emergency response." Existing technologies have the following shortcomings: (1) Data separation: In traditional management and control, "storage security" and "access traceability" belong to separate systems. Storage temperature monitoring and risk assessment are not linked to access operation data (such as operator identity and usage changes), resulting in incomplete risk analysis. (2) High dependence on manual intervention: Although some systems have introduced RFID or facial recognition, manual registration of usage and verification of remaining quantities are still required, which can easily lead to traceability gaps due to human error (such as deviations in recording the remaining quantities of anesthetic drugs after use). (3) The digital twin is disconnected from the Internet of Things: The existing digital twin risk assessment system does not access real-time data from Internet of Things terminals (such as the status of electronic locks on storage cabinets and the presence of hazardous chemicals), and cannot dynamically map the status of physical scenarios, resulting in delayed early warnings; (4) Poor adaptability to medical emergency: Hazardous chemicals need to be quickly retrieved in hospital emergency scenarios, but existing systems either have cumbersome emergency retrieval procedures or lack a traceability mechanism after an emergency, making it difficult to balance "emergency efficiency" and "safety control".

[0003] To address the aforementioned issues, this invention integrates the real-time data acquisition capabilities of IoT terminals with digital twin risk assessment technology to construct a control system covering the entire process of hazardous chemicals in hospitals, resolving problems such as data fragmentation, manual intervention, delayed early warning, and emergency adaptation. Summary of the Invention

[0004] This invention aims to overcome the aforementioned technical problems in the management of hazardous chemicals in existing technologies by providing an IoT-based hospital hazardous chemical storage and usage control system and method. This system identifies and records the retrieval and placement of hazardous chemicals, as well as each change in the amount of hazardous chemicals used, eliminating the need for manual registration and inventory checks, and achieving traceability of hazardous chemical storage and retrieval. It is applicable to the entire process of "storage-retrieval-use-return" management of high-risk hazardous chemicals such as anesthetic drugs, flammable and explosive reagents, and highly toxic medical reagents in hospital settings. It integrates real-time data collection from IoT terminals with digital twin risk assessment to achieve accurate traceability and safety early warning of hazardous chemicals in hospitals.

[0005] This application discloses an Internet of Things-based hospital hazardous chemical storage and management system, the system comprising: The Internet of Things (IoT) terminal module is used to collect weight data, RFID tag information, operator identification information, temperature and humidity of storage cabinets, electronic lock status, and hazardous chemical presence status during the storage and retrieval of hazardous chemicals in hospitals, and generate IoT terminal data. The hazardous chemicals information acquisition module is used to receive data from the Internet of Things terminal, integrate basic information and historical data of hazardous chemicals, and generate a hazardous chemicals storage data archive. The storage temperature analysis module is used to analyze the target temperature range of hazardous chemicals based on the hazardous chemical storage data archive, compare the real-time temperature and humidity with the target temperature range, and generate a temperature adjustment signal or a normal monitoring signal. The normal monitoring and analysis module is used to receive the normal monitoring signals, determine the compliance of the storage method and the operation of taking out hazardous chemicals, and generate storage adjustment signals or risk monitoring signals. The storage risk analysis module is used to receive the risk monitoring signal, calculate the fire prevention score (F), the emergency plan score (Y) and the storage hazard index (Q), and generate an early warning signal, a continuous monitoring signal or a safety signal based on the comparison result of Q and the risk threshold (Qy). The digital twin modeling module is used to construct a 1:1 virtual model of the physical terminal based on the IoT terminal data, dynamically map the storage and use status of hazardous chemicals, simulate risk scenarios, and visualize the risk distribution. The storage management information output module is used to output the temperature regulation signal, storage regulation signal, risk signal and storage record, and to interface with the hospital system to realize data interaction and traceability query.

[0006] This application also provides a method for the storage and management of hazardous chemicals in hospitals based on the Internet of Things, characterized in that the method includes the following steps: Step S1: IoT terminal data collection. Through the storage and retrieval platform module and storage cabinet sub-module of the IoT terminal module, synchronously collect the entire process data of the hospital's hazardous chemicals "storage-retrieval-use-return": The storage and retrieval platform module records the initial weight, retrieval weight, and remaining balance of hazardous chemicals through the weighing platform, reads the RFID tag information of hazardous chemicals through the RFID identification module, verifies the identity of the operator through the facial recognition camera, and records the fingerprint and time of emergency retrieval through the forced unlock switch. The storage cabinet sub-module detects the presence of hazardous chemicals through an RFID sensor array, collects real-time temperature and humidity data of the storage area through temperature and humidity sensors, and records the unlocking / locking status through an electronic lock. All collected data is labeled as IoT terminal data and transmitted to the hazardous chemicals information acquisition module; Step S2: Hazardous chemical information integration. The hazardous chemical information acquisition module receives data from the IoT terminal and integrates basic information and historical data of hazardous chemicals. The basic information includes type, production time, expiration date, medical use, and storage temperature and humidity requirements. The historical data includes historical access records, temperature anomaly records, and risk warning records. Unstructured data (facial images) is converted into structured data (facial feature codes) and associated with structured data (weight, RFID number, electronic lock status) to generate a unique "hazardous chemical storage data file," which is then transmitted to the storage temperature analysis module. Step S3: Storage temperature analysis and adjustment. The storage temperature analysis module performs the following operations based on the hazardous chemical storage data archive: Extract normal and abnormal temperature ranges from historical data. If there is an intersection between the two, use the intersection as the target temperature range. If there is no intersection, use the minimum value of the abnormal temperature range as the lower limit and the maximum value of the normal temperature range as the upper limit to generate the target temperature range. Compare the real-time temperature and humidity transmitted by the storage cabinet module with the target temperature range: if the real-time temperature and humidity exceed the target range, generate a temperature adjustment signal and transmit it to the storage management information output module to control the adjustment of the refrigeration / ventilation equipment; if the real-time temperature and humidity meet the target range, generate a normal monitoring signal and transmit it to the normal monitoring and analysis module. Step S4: Compliance monitoring of storage and retrieval. The normal monitoring and analysis module receives normal monitoring signals and determines the compliance of storage methods and retrieval operations respectively. Storage method determination: Compare the hazardous chemical storage requirements with the actual zoning of the storage cabinet. If they do not match, a storage adjustment signal is generated, prompting the transfer to the corresponding zoning and transmitting the information to the storage management information output module. If they match, proceed to the retrieval operation determination. Access operation judgment: verify the operator's identity and permissions, access weight deviation, and unlocking process. If compliant, generate a risk monitoring signal and transmit it to the storage risk analysis module; if non-compliant, generate a storage adjustment signal, lock the electronic lock, trigger an alarm, and transmit it to the storage management information output module. Step S5: Storage Risk Calculation and Early Warning. The storage risk analysis module receives risk monitoring signals, calculates risks, and generates early warnings according to the following process: Calculate the fire protection score (F): Substitute the following factors into the formula: response time t1 of the protection system, maintenance interval t2, number of maintenance operations b, number of fire-fighting equipment a, preset proportional coefficient β, and IoT status correction factor γ. For a normal electronic lock, γ = 1.0; for an abnormal lock, γ = 0.6. The F value is obtained. Calculate the emergency plan score (Y): Substitute the scores Ln of the m emergency plans, the preset proportional coefficient θ, and the emergency adaptation factor δ into the formula. If δ is added within one hour of forced unlocking (δ=1.0), and not added (δ=0.5), then... The Y value is obtained; Calculate the storage hazard index (Q): Substitute the F value, Y value, quantity of hazardous chemicals C, storage time T, operational compliance factor λ (λ=1.0 for dual-person verification, λ=0.3 for single-person verification), weight anomaly factor μ (μ=1.0 for deviation ≤5%, μ=0.4 for deviation >20%), and preset coefficient η into the formula. The Q value is obtained. Risk assessment: Compare the Q value with the risk threshold Qy: If Q>Qy, generate an early warning signal; if Q≤Qy, monitor the change of Q value in 15-minute intervals. If the Q value increases, generate an early warning signal; if the Q value is stable, generate a safety signal. The warning signal or safety signal is transmitted to the storage management information output module and the digital twin modeling module; Step S6: Digital twin modeling and visualization. The digital twin modeling module constructs a 1:1 virtual model of the physical access station and storage cabinet based on real-time data from IoT terminals. Dynamic mapping: Synchronously update the on-site status of hazardous chemicals, temperature and humidity, electronic lock switches, and operator actions in the virtual model to ensure that the virtual model is consistent with the physical scene in real time; Risk simulation: Simulate scenarios such as abnormal temperature, loss of hazardous chemicals, and unauthorized use, and output the risk diffusion path; Visualization: The Q value of each storage area is marked with a heat map, allowing managers to click on the virtual model to view individual hazardous chemical storage data files.

[0007] Step S7: Information output and traceability management. The storage management information output module performs the following operations: Signal output: Display temperature adjustment signals, store adjustment signals, and warning / safety signals on the nurse station screen and the administrator's PC. In case of abnormality, push alarm information to the administrator's mobile phone simultaneously. Data interaction: It interfaces with hospital systems and drug management systems to synchronize hazardous chemical inventory data and automatically triggers procurement requests when the remaining quantity falls below a threshold; Traceability query: Supports searching stored records by RFID number, operator, and time range, and exporting traceability reports in PDF format containing RFID number, operation information, weight changes, and risk warnings.

[0008] Therefore, the present invention can achieve the following technical effects in the management and control of hazardous chemicals: (1) The IoT terminal data of this system adopts IoT-based access stations and storage cabinets, integrating weighing, RFID and barcode three-source data fusion: the access station integrates a weighing module, RFID reader and barcode printer / scanner to simultaneously acquire reagent weight, electronic tag and barcode information, eliminating manual intervention. The storage cabinet is equipped with an RFID antenna array to monitor the status of hazardous chemicals in real time and link with the data of the access station, covering the entire path of "operation-temporary storage-return". Face recognition and dynamic access control: the access station is embedded with dual cameras to continuously verify the identity of personnel throughout the operation, and the access level is matched with the risk level of the reagent.

[0009] (2) Traditional risk assessment relies on single environmental parameters or human experience, failing to consider factors specific to medical scenarios such as operational compliance and emergency response. This solution innovatively introduces calculation models for fire prevention scores (F), emergency response scores (Y), and storage hazard index (Q), integrating medical scenario parameters such as IoT status correction factors (γ) and operational compliance factors (λ) to achieve dynamic risk assessment. By using risk thresholds adapted to the hospital's emergency response system, safety management shifts from post-event accountability to pre-event prevention, reducing the annual safety accident rate to zero. Attached Figure Description

[0010] Figure 1 This is a system logic block diagram of the present invention.

[0011] Figure 2 This is a schematic diagram of the structure of the Internet of Things terminal module of the present invention.

[0012] Figure 3 This is a cross-sectional view of the storage cabinet of the Internet of Things terminal module of the present invention.

[0013] Figure 4 This is a schematic diagram of the control system of the IoT terminal module of the present invention.

[0014] The diagram is labeled as follows: 1. Storage and retrieval platform; 101. Main unit; 102. Weighing platform; 103. RFID identification module; 104. Electronic lock; 105. Label printer; 106. Shielding cover; 107. Barcode scanner; 108. Forced unlock switch; 109. Touch screen; 110. Face recognition camera; 2. Storage cabinet; 201. RFID sensor. Detailed Implementation

[0015] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0016] Example 1 like Figure 1 As shown in the figure, this application discloses an Internet of Things-based hospital hazardous chemical storage and management system, the system comprising: The IoT terminal module is used to collect weight data, RFID tag information, operator identification information, temperature and humidity of storage cabinets, electronic lock status, and hazardous chemical presence status during the storage and retrieval of hazardous chemicals in the hospital, and generate IoT terminal data.

[0017] The hazardous chemicals information acquisition module is used to receive data from the Internet of Things terminal, integrate basic information and historical data of hazardous chemicals, and generate a hazardous chemicals storage data archive.

[0018] The storage temperature analysis module is used to analyze the target temperature range of hazardous chemicals based on the hazardous chemical storage data archive, compare the real-time temperature and humidity with the target temperature range, and generate a temperature adjustment signal or a normal monitoring signal; the normal monitoring analysis module is used to receive the normal monitoring signal, determine the compliance of the hazardous chemical storage method and the compliance of the retrieval operation, and generate a storage adjustment signal or a risk monitoring signal.

[0019] The storage risk analysis module is used to receive the risk monitoring signal, calculate the fire prevention score (F), the emergency plan score (Y) and the storage hazard index (Q), and generate an early warning signal, a continuous monitoring signal or a safety signal based on the comparison result of Q and the risk threshold (Qy).

[0020] The digital twin modeling module is used to construct a 1:1 virtual model of the physical terminal based on the IoT terminal data, dynamically map the storage and use status of hazardous chemicals, simulate risk scenarios, and visualize the risk distribution.

[0021] The storage management information output module is used to output the temperature regulation signal, storage regulation signal, risk signal and storage record, and to interface with the hospital system to realize data interaction and traceability query.

[0022] like Figure 2 , Figure 3 , Figure 4 As shown, the IoT terminal module includes a storage and retrieval platform submodule and a storage cabinet submodule. The storage cabinet 2 has built-in storage space for storing hazardous chemicals, and the storage and retrieval platform 1 is used for pre-access scanning and registration of hazardous chemicals. The storage cabinet can be designed as an integrated unit or a separate unit from the storage and retrieval platform 1, depending on the requirements.

[0023] The storage station 1 is equipped with a host 101, a control panel connected to the host 101, a weighing platform 102, and an RFID identification module 103. The storage cabinet 2 is equipped with an RFID sensor 201 connected to the host 101.

[0024] The weighing platform 102 is located on the front panel of the storage and retrieval platform 1 and is used to weigh the hazardous chemicals being stored and retrieved. The weighing platform 102 is equipped with a weight sensor, which calculates the amount of hazardous chemicals used in each retrieval and storage by weighing and recording the weight of the hazardous chemicals, thereby realizing full-process tracking management and traceability of the corresponding hazardous chemical storage and usage.

[0025] The RFID identification module 103 is installed above the weighing platform 102 and is used to read and identify the RFID tags of hazardous chemicals when weighing them. The RFID sensor 201 is used to identify the RFID tags of hazardous chemicals inside the storage cabinet 2, thereby cooperating with the RFID identification module 103 to identify the hazardous chemical handling status.

[0026] Hazardous chemical containers are affixed with RFID tags, giving each container a unique identification tag. During the retrieval and storage process, not only is RFID identification performed on the retrieval station 1, but the RFID sensor 201 inside the storage cabinet 2 also ensures that the hazardous chemicals are stored in the storage cabinet 2 in a timely manner, preventing theft or loss of hazardous chemicals between the retrieval and storage registration operation and the actual storage operation.

[0027] Preferably, the storage and retrieval station further includes a face recognition camera, a label printer, a barcode scanner, and a forced unlock switch; the weighing platform has an accuracy of ±0.1g and is used to record the initial weight of the hazardous chemicals, the weight taken out, and the remaining weight after return; the face recognition camera is a dual-camera system that supports dual-person face verification; the forced unlock switch is a fingerprint unlock switch that automatically records the fingerprint and time after unlocking.

[0028] The control panel is a touch screen 109. A facial recognition camera 110 is located above the touch screen on the storage station 1. The facial recognition camera is connected to the host computer 101 and is used to capture and identify personnel handling hazardous materials. The touch screen allows for intuitive registration of hazardous materials retrieval and storage. Simultaneously, by capturing and identifying personnel handling hazardous materials, facial recognition enables personnel access management and traceability.

[0029] The front panel of the access station 1 is equipped with a label printer 105, which is used to print RFID tags. The front panel of the access station 1 has a label outlet corresponding to the label printer 105. A shielding plate 106 is provided on the side of the label outlet facing the RFID identification module 103. The shielding plate 106 is used to prevent the RFID identification module 103 from reading the printed RFID tags. During the RFID tag printing process, the RFID identification module 103 on the access station 1 may misidentify the tags, causing unnecessary errors. Therefore, an L-shaped metal shielding plate 106 is used to isolate the RFID identification module 103 and the label printer 105 to prevent misidentification and misoperation.

[0030] The storage station 1 is also equipped with a barcode scanner 107, which is used to identify QR codes or barcodes. The RFID tags printed by the label printer 105 have QR codes or barcodes attached. RFID for hazardous chemicals is mainly used in the storage and retrieval management of this solution. In other specific scenarios involving hazardous chemicals, identification may be performed by scanning barcodes or QR codes. The barcode scanner 107 in this solution enables the fusion of three data sources: weighing, RFID, and barcode, achieving unified identification of RFID tags and barcodes.

[0031] The access station 1 is equipped with a forced unlock switch 108, which is connected to the electronic lock 104 of the storage cabinet 2. This forced unlock switch 108 is used to unlock the electronic lock 104 of the storage cabinet 2 without the control of the host 101. The forced unlock switch 108 is a fingerprint unlock switch. In case of system failure or other emergencies where it is still necessary to open the storage cabinet 2, only authorized personnel are required. The fingerprint unlock switch can unlock the electronic lock 104 of the storage cabinet 1 without the control of the host 102.

[0032] The storage cabinet 2 is equipped with an electronic lock 104, which is connected to and controlled by the host 101. The host 101 adopts an industrial control computer or similar controller design to control and collect data from intelligent modules such as the control panel, weighing platform 102, RFID identification module 103 on the storage station 1, and RFID sensor 201 and electronic lock 104 in the storage cabinet. It is also equipped with a network communication module for communication with the upper control platform. Multiple RFID-based hazardous chemical management terminal devices can be deployed in scenarios such as hospitals to achieve full-process management of hazardous chemicals throughout the hospital.

[0033] Preferably, the storage cabinet also includes partitioned storage space and temperature and humidity sensors; the partitioned storage space is divided according to the risk level of hazardous chemicals, and each zone has an independent electronic lock; the RFID sensor array generates a loss warning if it does not identify a hazardous chemical RFID signal within 10 seconds.

[0034] The specific method by which the storage temperature analysis module generates the target temperature range is as follows: extract the normal temperature range and the abnormal temperature range from the historical data; if there is an intersection between the two, the intersection is used as the target temperature range; if there is no intersection, the minimum value of the abnormal temperature range is used as the lower limit and the maximum value of the normal temperature range is used as the upper limit to generate the target temperature range.

[0035] The formula for calculating the fire protection score (F) by the storage risk analysis module is as follows: Where t1 is the response time of the protection system, t2 is the maintenance interval of the protection system, b is the number of maintenance times of the protection system, a is the number of fire-fighting equipment, β is the preset proportional coefficient (value 1.0-1.5), and γ is the IoT status correction factor. When the electronic lock is normal, γ=1.0, and when the electronic lock is abnormally opened, γ=0.6.

[0036] The formula for calculating the contingency plan score (Y) by the storage risk analysis module is as follows: Where, Ln is the score of the nth emergency plan, ranging from 1 to 10 points; θ is the preset proportional coefficient, ranging from 0.8 to 1.2; δ is the emergency adaptation factor, with δ=1.0 if the data is added within 1 hour after forced unlocking, and δ=0.5 if the data is not added; and m is the total number of emergency plans.

[0037] The formula for calculating the storage risk index (Q) by the storage risk analysis module is as follows: Where C is the quantity of hazardous chemicals in the storage area; T is the storage time of hazardous chemicals; λ is the operation compliance factor, with λ=1.0 for double verification and λ=0.3 for single verification; μ is the weight anomaly factor, with μ=1.0 when the balance deviation is ≤5% and μ=0.4 when the deviation is >20%; η is the preset coefficient, with a value of 0.9-1.1.

[0038] The digital twin modeling module supports risk simulation, which can simulate scenarios such as abnormal temperature, loss of hazardous chemicals, and unauthorized use, output risk diffusion paths, and display the storage hazard index (Q) of each storage area in a heat map.

[0039] The storage management information output module can export a hazardous chemical storage traceability report in PDF format. The report includes RFID number, operator information, storage and retrieval time, weight change, and risk warning records.

[0040] Example 2 This embodiment provides a method for the storage and management of hazardous chemicals in hospitals based on the Internet of Things, building upon Embodiment 1. The method includes the following steps: Step S1: IoT terminal data collection. Through the storage and retrieval platform module and storage cabinet sub-module of the IoT terminal module, synchronously collect the entire process data of the hospital's hazardous chemicals "storage-retrieval-use-return": The storage and retrieval platform module records the initial weight, retrieval weight, and remaining balance of hazardous chemicals through the weighing platform, reads the RFID tag information of hazardous chemicals through the RFID identification module, verifies the identity of the operator through the facial recognition camera, and records the fingerprint and time of emergency retrieval through the forced unlock switch. The storage cabinet sub-module detects the presence of hazardous chemicals through an RFID sensor array, collects real-time temperature and humidity data of the storage area through temperature and humidity sensors, and records the unlocking / locking status through an electronic lock. All collected data is labeled as IoT terminal data and transmitted to the hazardous chemicals information acquisition module; Step S2: Hazardous chemical information integration. The hazardous chemical information acquisition module receives data from the IoT terminal and integrates basic information and historical data of hazardous chemicals. The basic information includes type, production time, expiration date, medical use, and storage temperature and humidity requirements. The historical data includes historical access records, temperature anomaly records, and risk warning records. Unstructured data (facial images) is converted into structured data (facial feature codes) and associated with structured data (weight, RFID number, electronic lock status) to generate a unique "hazardous chemical storage data file," which is then transmitted to the storage temperature analysis module. Step S3: Storage temperature analysis and adjustment. The storage temperature analysis module performs the following operations based on the hazardous chemical storage data archive: Extract normal and abnormal temperature ranges from historical data. If there is an intersection between the two, use the intersection as the target temperature range. If there is no intersection, use the minimum value of the abnormal temperature range as the lower limit and the maximum value of the normal temperature range as the upper limit to generate the target temperature range. Compare the real-time temperature and humidity transmitted by the storage cabinet module with the target temperature range: if the real-time temperature and humidity exceed the target range, generate a temperature adjustment signal and transmit it to the storage management information output module to control the adjustment of the refrigeration / ventilation equipment; if the real-time temperature and humidity meet the target range, generate a normal monitoring signal and transmit it to the normal monitoring and analysis module. Step S4: Compliance monitoring of storage and retrieval. The normal monitoring and analysis module receives normal monitoring signals and determines the compliance of storage methods and retrieval operations respectively. Storage method determination: Compare the hazardous chemical storage requirements with the actual zoning of the storage cabinet. If they do not match, a storage adjustment signal is generated, prompting the transfer to the corresponding zoning and transmitting the information to the storage management information output module. If they match, proceed to the retrieval operation determination. Access operation judgment: verify the operator's identity and permissions, access weight deviation, and unlocking process. If compliant, generate a risk monitoring signal and transmit it to the storage risk analysis module; if non-compliant, generate a storage adjustment signal, lock the electronic lock, trigger an alarm, and transmit it to the storage management information output module. Step S5: Storage Risk Calculation and Early Warning. The storage risk analysis module receives risk monitoring signals, calculates risks, and generates early warnings according to the following process: Calculate the fire protection score (F): Substitute the following factors into the formula: response time t1 of the protection system, maintenance interval t2, number of maintenance operations b, number of fire-fighting equipment a, preset proportional coefficient β, and IoT status correction factor γ. For a normal electronic lock, γ = 1.0; for an abnormal lock, γ = 0.6. The F value is obtained. Calculate the emergency plan score (Y): Substitute the scores Ln of the m emergency plans, the preset proportional coefficient θ, and the emergency adaptation factor δ into the formula. If δ is added within one hour of forced unlocking (δ=1.0), and not added (δ=0.5), then... The Y value is obtained; Calculate the storage hazard index (Q): Substitute the F value, Y value, quantity of hazardous chemicals C, storage time T, operational compliance factor λ (λ=1.0 for dual-person verification, λ=0.3 for single-person verification), weight anomaly factor μ (μ=1.0 for deviation ≤5%, μ=0.4 for deviation >20%), and preset coefficient η into the formula. The Q value is obtained. Risk assessment: Compare the Q value with the risk threshold Qy: If Q>Qy, generate an early warning signal; if Q≤Qy, monitor the change of Q value in 15-minute intervals. If the Q value increases, generate an early warning signal; if the Q value is stable, generate a safety signal. The warning signal or safety signal is transmitted to the storage management information output module and the digital twin modeling module; Step S6: Digital twin modeling and visualization. The digital twin modeling module constructs a 1:1 virtual model of the physical access station and storage cabinet based on real-time data from IoT terminals. Dynamic mapping: Synchronously update the on-site status of hazardous chemicals, temperature and humidity, electronic lock switches, and operator actions in the virtual model to ensure that the virtual model is consistent with the physical scene in real time; Risk simulation: Simulate scenarios such as abnormal temperature, loss of hazardous chemicals, and unauthorized use, and output the risk diffusion path; Visualization: The Q value of each storage area is marked with a heat map, allowing managers to click on the virtual model to view individual hazardous chemical storage data files.

[0041] Step S7: Information output and traceability management. The storage management information output module performs the following operations: Signal output: Display temperature adjustment signals, store adjustment signals, and warning / safety signals on the nurse station screen and the administrator's PC. In case of abnormality, push alarm information to the administrator's mobile phone simultaneously. Data interaction: It interfaces with hospital systems and drug management systems to synchronize hazardous chemical inventory data and automatically triggers procurement requests when the remaining quantity falls below a threshold; Traceability query: Supports searching stored records by RFID number, operator, and time range, and exporting traceability reports in PDF format containing RFID number, operation information, weight changes, and risk warnings.

[0042] Further, in step S1, the label printer of the access table sub-unit prints a composite label containing an RFID chip and a QR code. The shielding cover plate on the side of the label outlet prevents the RFID identification module from misreading the newly printed label. The QR code is scanned by the QR code scanner to associate with the hospital HIS system number, realizing the three-source data fusion verification of "RFID - barcode - weight".

[0043] Further, in step S5, if an emergency access scenario that triggers forced unlocking occurs, the system automatically generates an "Emergency Access Temporary Record" and triggers a supplementary recording reminder within 1 hour. After the administrator supplements the usage purpose and quantity, the emergency adaptation factor δ returns to 1.0, and the stored hazard index Q value is recalculated and the risk signal is updated.

[0044] The following takes the implementation scenario of hospital anesthetic drug control as an example to illustrate the application effect of this solution: (1) Inbound of anesthetic drugs: The operator passes double-person face verification at the access table, and the label printer prints an anesthetic drug label containing an RFID chip and a QR code, which is pasted on the drug package. The drug is placed on the weighing table, and the initial weight (such as 100 ml) is recorded. The RFID identification module reads the label information, and the QR code scanner scans the QR code to associate with the HIS system number. The hazardous chemical information acquisition unit integrates the above data with the basic drug information (batch number, expiration date, storage temperature 2 - 8°C) to generate a storage and usage data file. The RFID sensor of the storage cabinet confirms that the drug has been returned to the anesthetic drug area, the electronic lock is automatically locked, and the temperature and humidity sensor starts to monitor the regional temperature.

[0045] (2)取用(常规场景): The anesthesiologist and nurse pass double-person face verification at the access table, and the RFID identification module reads the drug label to confirm that the permissions match. The electronic lock of the storage cabinet is unlocked. After the doctor takes the drug (such as 20 ml), the remaining drug is put back on the weighing table, and the remaining amount (80 ml) is recorded. The normal monitoring and analysis unit judges the operation rules of the console (double-person verification, weight deviation of 20 ml conforms to the medical usage amount) and generates a risk monitoring signal. The storage risk analysis unit calculates Q value F = 85, Y = 90, C = 1, T = 7 days, λ = 1.0, μ = 1.0, η = 1.0, Q = (85 + 90) × 1 × 1.0 / (2 × 7 × 1.0) × 1.0 ≈ 12.5), Q < Qy (50), and generates a safety signal. The digital twin model updates the drug remaining amount and operation records, and the storage management information output unit synchronizes the data.

[0046] (3) Emergency access to anesthetic drugs: In an emergency situation, the administrator opens the storage cabinet through the forced unlocking switch (fingerprint verification) of the access console to obtain anesthetic drugs; The Internet of Things terminal unit automatically records the unlocking time and the administrator's fingerprint, generating a "temporary record of emergency access"; The storage risk analysis unit calculates the Q value γ = 0.6, δ = 0.5, Q = (85×0.6 + 90×0.5)×1×0.3 / (2×7×1.0)×1.0 ≈ 3.8). Although Q < Qy, it triggers an "emergency traceability reminder"; Two hours later, the administrator supplements the emergency usage record (dosage 15ml, remaining amount 85ml), δ returns to 1.0, and the Q value is updated to 11.8, and the safety signal continues.

[0047] (4) Temperature anomaly warning: The temperature and humidity sensor in the storage cabinet detects that the temperature has risen to 9°C and transmits the data to the storage temperature analysis unit; The storage temperature analysis unit compares the target temperature range (2 - 8°C), generates a temperature adjustment signal, and controls the refrigeration equipment to cool down; The digital twin model marks the temperature anomaly in this area in red, and the storage management information output unit pushes the warning to the administrator's mobile phone; After the temperature drops to 7°C, the temperature adjustment signal terminates, and the digital twin model resumes the green marking.

[0048] In summary, the application of this solution has the following technical effects in terms of full-process closed-loop traceability, operation efficiency, decision-making scientificity, etc. compared with traditional and existing hospital hazardous chemical control methods: In the existing technology, the storage monitoring and usage records of hospital hazardous chemicals mostly belong to independent systems, and environmental data such as temperature and humidity are disconnected from information such as operators and dosage changes, resulting in incomplete risk analysis. Although some platforms have achieved full-life-cycle control, they have not achieved the deep integration of systems unique to medical scenarios. This solution collects full-process data of "storage - access - usage - return" through the Internet of Things terminal unit (weighing platform, RFID identification, face recognition, etc.), combines with the hazardous chemical information acquisition unit to build a unique "storage and usage data file", and realizes the fusion verification of "RFID - barcode - weight" three-source data. At the same time, it is connected to the hospital HIS system in real time, synchronizes inventory data and automatically triggers a procurement application, forming a complete data closed-loop from warehousing to traceability. Compared with the traditional manual ledger, the inventory counting efficiency is increased by 90%, and the traceability accuracy rate reaches 100%. Traditional management methods rely on manual registration of usage and verification of remaining quantities, which is prone to traceability gaps due to human error, and the approval process for requisitioning takes 3-5 days. Even systems that introduce RFID technology still require manual intervention in key aspects. This solution automatically records weight changes using a weighing platform (accuracy ±0.1g), verifies authorization through dual-person facial recognition, and links operation records with electronic locks, reducing the time for a single requisition from 10-15 minutes to 1-2 minutes. The dual-person, dual-lock mechanism for high-risk chemicals, along with automatic record-keeping reminders after forced unlocking, reduces human error risks while ensuring compliance in medical settings, resolving the conflict between operational efficiency and safety management.

[0049] Existing systems either have cumbersome emergency retrieval procedures that delay treatment, or lack post-event traceability mechanisms, making them difficult to adapt to the needs of hospital emergency scenarios. This solution features a forced unlock switch (fingerprint verification) that supports rapid emergency access while automatically recording the unlock time and operator information, triggering a reminder to re-encode within one hour. After re-encoding, the system dynamically adjusts the risk index using an emergency adaptation factor (δ) to ensure a balance between "emergency efficiency" and "safety traceability." This mechanism increases the emergency response compliance rate from 60% in the traditional model to 98%, without any liability disputes arising from missing traceability.

[0050] Traditional risk assessments rely on single environmental parameters or human experience, without considering factors such as operational compliance and emergency response specific to medical scenarios. This innovative solution introduces a calculation model for fire prevention scoring (F), emergency response scoring (Y), and storage hazard index (Q), integrating medical scenario parameters such as IoT status correction factor (γ) and operational compliance factor (λ) to achieve dynamic risk assessment. By using risk thresholds adapted to the hospital's emergency response system (e.g., Qy=50 for anesthetic drugs), safety management shifts from post-event accountability to pre-event prevention, reducing the annual safety accident rate to zero.

Claims

1. A hospital hazardous chemicals storage and management system based on the Internet of Things, characterized in that, The system includes: The IoT terminal module collects weight data, RFID tag information, operator identification information, and temperature and humidity of the storage cabinet, electronic lock status, and hazardous chemical presence status during the storage and retrieval of hazardous chemicals in the hospital, generating IoT terminal data. The hazardous chemical information acquisition module receives the IoT terminal data, integrates basic hazardous chemical information and historical data, and generates a hazardous chemical storage and usage data archive. The storage temperature analysis module analyzes the target temperature range of hazardous chemicals based on the hazardous chemical storage and usage data archive, compares real-time temperature and humidity with the target temperature range, and generates temperature adjustment signals or normal monitoring signals. The normal monitoring analysis module receives the normal monitoring signals and determines the compliance of the hazardous chemical storage method and retrieval operation. For compliance purposes, a storage adjustment signal or risk monitoring signal is generated; a storage risk analysis module is used to receive the risk monitoring signal, calculate the fire prevention score (F), the emergency plan score (Y), and the storage hazard index (Q), and generate an early warning signal, a continuous monitoring signal, or a safety signal based on the comparison result of Q and the risk threshold (Qy); a digital twin modeling module is used to construct a 1:1 virtual model of the physical terminal based on the IoT terminal data, dynamically map the storage and use status of hazardous chemicals, simulate risk scenarios, and visualize the risk distribution; a storage management information output module is used to output the temperature adjustment signal, storage adjustment signal, risk signal, and storage record, and interface with the hospital system to achieve data interaction and traceability query.

2. The hospital hazardous chemicals storage and management system based on the Internet of Things as described in claim 1, characterized in that, The IoT terminal module includes a storage and retrieval platform submodule and a storage cabinet submodule; the storage and retrieval platform module includes a weighing platform, an RFID identification module, a face recognition camera, a label printer, a barcode scanner, and a forced unlock switch; the weighing platform has an accuracy of ±0.1g and is used to record the initial weight of hazardous chemicals, the weight taken out, and the remaining weight after return; the face recognition camera is a dual-camera system that supports dual-person face verification; the forced unlock switch is a fingerprint unlock switch that automatically records the fingerprint and time after unlocking; The storage cabinet submodule includes partitioned storage space, RFID sensor array, electronic lock, and temperature and humidity sensor; the partitioned storage space is divided according to the risk level of hazardous chemicals, and each zone has an independent electronic lock; the RFID sensor array generates a loss warning if it does not identify a hazardous chemical RFID signal within 10 seconds.

3. The hospital hazardous chemicals storage and management system based on the Internet of Things as described in claim 1, characterized in that, The specific method by which the storage temperature analysis module generates the target temperature range is as follows: extract the normal temperature range and the abnormal temperature range from the historical data; if there is an intersection between the two, the intersection is used as the target temperature range; if there is no intersection, the minimum value of the abnormal temperature range is used as the lower limit and the maximum value of the normal temperature range is used as the upper limit to generate the target temperature range.

4. The hospital hazardous chemicals storage and management system based on the Internet of Things as described in claim 1, characterized in that, The formula for calculating the fire protection score (F) by the storage risk analysis module is as follows: Where t1 is the response time of the protection system, t2 is the maintenance interval of the protection system, b is the number of maintenance times of the protection system, a is the number of fire-fighting equipment, β is the preset proportional coefficient (value 1.0-1.5), and γ is the IoT status correction factor. When the electronic lock is normal, γ=1.0, and when the electronic lock is abnormally opened, γ=0.

6.

5. A hospital hazardous chemicals storage and management system based on the Internet of Things as described in claim 1, characterized in that, The formula for calculating the contingency plan score (Y) by the storage risk analysis module is as follows: Where, Ln is the score of the nth emergency plan, ranging from 1 to 10 points; θ is the preset proportional coefficient, ranging from 0.8 to 1.2; δ is the emergency adaptation factor, with δ=1.0 if the data is added within 1 hour after forced unlocking, and δ=0.5 if the data is not added; and m is the total number of emergency plans.

6. The hospital hazardous chemicals storage and management system based on the Internet of Things according to claim 1, characterized in that, The formula for calculating the storage risk index (Q) by the storage risk analysis module is as follows: Where C is the quantity of hazardous chemicals in the storage area; T is the storage time of hazardous chemicals; λ is the operation compliance factor, with λ=1.0 for double verification and λ=0.3 for single verification; μ is the weight anomaly factor, with μ=1.0 when the balance deviation is ≤5% and μ=0.4 when the deviation is >20%; η is the preset coefficient, with a value of 0.9-1.

1.

7. A hospital hazardous chemicals storage and management system based on the Internet of Things as described in claim 1, characterized in that, The digital twin modeling module supports risk simulation, which can simulate scenarios such as abnormal temperature, loss of hazardous chemicals, and unauthorized use, output risk diffusion paths, and display the storage hazard index (Q) of each storage area in a heat map.

8. A hospital hazardous chemicals storage and management system based on the Internet of Things as described in claim 1, characterized in that, The storage management information output module can export a hazardous chemical storage traceability report in PDF format. The report includes RFID number, operator information, storage and retrieval time, weight change, and risk warning records.

9. A hospital hazardous chemicals storage and management system based on the Internet of Things as described in claim 1, characterized in that, The IoT terminal module includes a storage station (1) and a storage cabinet (2), wherein the storage cabinet (2) has a built-in storage space for storing hazardous chemicals. The storage station (1) is equipped with a host (101), a control panel, a weighing platform (102), and an RFID identification module (103) connected to the host (101); the weighing platform (102) is located on the front panel of the storage station (1) and is used to weigh the hazardous chemicals stored; the RFID identification module (103) is located above the weighing platform (102) and is used to read and identify the RFID tag of the hazardous chemicals when weighing them. The storage cabinet (2) is equipped with an electronic lock (104), which is connected to the host (101) and controlled by the host (101); the storage cabinet (2) is equipped with an RFID sensor (201) connected to the host (101); the RFID sensor (201) is used to identify the RFID tags of hazardous chemicals in the storage cabinet (2), thereby cooperating with the RFID identification module (103) to identify the hazardous chemical handling status.

10. A method for the storage and management of hazardous chemicals in hospitals based on the Internet of Things, characterized in that, The method includes the following steps: Step S1: IoT terminal data collection. Through the storage and retrieval platform module and storage cabinet sub-module of the IoT terminal module, synchronously collect the entire process data of the hospital's hazardous chemicals "storage-retrieval-use-return": The storage and retrieval platform module records the initial weight, retrieval weight, and remaining balance of hazardous chemicals through the weighing platform, reads the RFID tag information of hazardous chemicals through the RFID identification module, verifies the identity of the operator through the facial recognition camera, and records the fingerprint and time of emergency retrieval through the forced unlock switch. The storage cabinet sub-module detects the presence of hazardous chemicals through an RFID sensor array, collects real-time temperature and humidity data of the storage area through temperature and humidity sensors, and records the unlocking / locking status through an electronic lock. All collected data is labeled as IoT terminal data and transmitted to the hazardous chemicals information acquisition module; Step S2: Hazardous chemical information integration. The hazardous chemical information acquisition module receives data from the IoT terminal and integrates basic information and historical data of hazardous chemicals. The basic information includes type, production time, expiration date, medical use, and storage temperature and humidity requirements. The historical data includes historical access records, temperature anomaly records, and risk warning records. Unstructured data (facial images) is converted into structured data (facial feature codes) and associated with structured data (weight, RFID number, electronic lock status) to generate a unique "hazardous chemical storage data file," which is then transmitted to the storage temperature analysis module. Step S3: Storage temperature analysis and adjustment. The storage temperature analysis module performs the following operations based on the hazardous chemical storage data archive: Extract normal and abnormal temperature ranges from historical data. If there is an intersection between the two, use the intersection as the target temperature range. If there is no intersection, use the minimum value of the abnormal temperature range as the lower limit and the maximum value of the normal temperature range as the upper limit to generate the target temperature range. Compare the real-time temperature and humidity transmitted by the storage cabinet module with the target temperature range: if the real-time temperature and humidity exceed the target range, generate a temperature adjustment signal and transmit it to the storage management information output module to control the adjustment of the refrigeration / ventilation equipment; if the real-time temperature and humidity meet the target range, generate a normal monitoring signal and transmit it to the normal monitoring and analysis module. Step S4: Compliance monitoring of storage and retrieval. The normal monitoring and analysis module receives normal monitoring signals and determines the compliance of storage methods and retrieval operations respectively. Storage method determination: Compare the hazardous chemical storage requirements with the actual zoning of the storage cabinet. If they do not match, a storage adjustment signal is generated, prompting the transfer to the corresponding zoning and transmitting the information to the storage management information output module. If they match, proceed to the retrieval operation determination. Access operation judgment: verify the operator's identity and permissions, access weight deviation, and unlocking process. If compliant, generate a risk monitoring signal and transmit it to the storage risk analysis module; if non-compliant, generate a storage adjustment signal, lock the electronic lock, trigger an alarm, and transmit it to the storage management information output module. Step S5: Storage Risk Calculation and Early Warning. The storage risk analysis module receives risk monitoring signals, calculates risks, and generates early warnings according to the following process: Calculate the fire protection score (F): Substitute the following factors into the formula: response time t1 of the protection system, maintenance interval t2, number of maintenance operations b, number of fire-fighting equipment a, preset proportional coefficient β, and IoT status correction factor γ. For a normal electronic lock, γ = 1.0; for an abnormal lock, γ = 0.

6. The F value is obtained. Calculate the emergency plan score (Y): Substitute the scores Ln of the m emergency plans, the preset proportional coefficient θ, and the emergency adaptation factor δ into the formula. If δ is added within one hour of forced unlocking (δ=1.0), and not added (δ=0.5), then... The Y value is obtained; Calculate the storage hazard index (Q): Substitute the F value, Y value, quantity of hazardous chemicals C, storage time T, operational compliance factor λ (λ=1.0 for dual-person verification, λ=0.3 for single-person verification), weight anomaly factor μ (μ=1.0 for deviation ≤5%, μ=0.4 for deviation >20%), and preset coefficient η into the formula. The Q value is obtained; Risk assessment: Compare the Q value with the risk threshold Qy: If Q>Qy, generate an early warning signal; if Q≤Qy, monitor the change of Q value in 15-minute intervals. If the Q value increases, generate an early warning signal; if the Q value is stable, generate a safety signal. The warning signal or safety signal is transmitted to the storage management information output module and the digital twin modeling module; Step S6: Digital twin modeling and visualization. The digital twin modeling module constructs a 1:1 virtual model of the physical access station and storage cabinet based on real-time data from IoT terminals. Dynamic mapping: Synchronously update the on-site status of hazardous chemicals, temperature and humidity, electronic lock switches, and operator actions in the virtual model to ensure that the virtual model is consistent with the physical scene in real time; Risk simulation: Simulate scenarios such as abnormal temperature, loss of hazardous chemicals, and unauthorized use, and output the risk diffusion path; Visualization: The Q value of each storage area is marked with a heat map, allowing managers to click on the virtual model to view individual hazardous chemical storage data files. Step S7: Information output and traceability management. The storage management information output module performs the following operations: Signal output: Display temperature adjustment signals, store adjustment signals, and warning / safety signals on the nurse station screen and the administrator's PC. In case of abnormality, push alarm information to the administrator's mobile phone simultaneously. Data interaction: It interfaces with hospital systems and drug management systems to synchronize hazardous chemical inventory data and automatically triggers procurement requests when the remaining quantity falls below a threshold; Traceability query: Supports searching stored records by RFID number, operator, and time range, and exporting traceability reports in PDF format containing RFID number, operation information, weight changes, and risk warnings.

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