Intelligent internet-of-things medical garbage sorting and recycling system, method, equipment and medium

Abstract

The invention discloses an intelligent internet-of-things medical garbage sorting and recycling system, and relates to the technical field of garbage sorting and recycling. The garbage collection module monitors a garbage can through a high-precision sensor, and data are transmitted through quantum encryption LoRa. Data transmission is combined with an LPWAN and a satellite link, and chaos encryption is used; deep reinforcement learning analysis is used for central control, a scheme is generated according to a GIS and traffic, garbage transportation depends on a multi-sensor AGV, intelligent obstacle avoidance, automatic charging and intelligent sorting can be achieved through a Raman spectrum and a flexible mechanical arm, and a block chain and a quantum watermarking technology are used for monitoring and tracing. Efficient collection through the intelligent garbage can, accurate transportation through the AGV, intelligent sorting through the spectrum and the mechanical arm, sterilization through the advanced disinfection technology and whole-course tracing through the block chain are achieved; the medical waste treatment efficiency is comprehensively improved, the pollution risk is reduced, and the safety and sanitation of the medical environment are guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of garbage recycling systems, and particularly to an intelligent Internet of Things medical waste sorting and recycling system, method, device, and medium. Background Art

[0002] In the medical field, the treatment of medical waste has always been a crucial and challenging issue. Traditional methods of treating medical waste have many drawbacks, seriously affecting the safety and hygiene of the medical environment.

[0003] Currently, the collection link of medical waste lacks intelligent management. Each department in the hospital usually uses ordinary trash cans to collect garbage, and it is impossible to accurately and timely grasp the status of the garbage in the trash cans in real time. Medical staff need to frequently check manually whether the trash cans are full, which not only wastes manpower, but also may cause garbage overflow due to failure to clean in time, increasing the risk of bacterial growth and cross-infection. Moreover, different types of medical waste are collected mixed, bringing great difficulties to the subsequent sorting work.

[0004] In terms of garbage transportation, traditional methods rely on manual operation, and the transportation process lacks effective monitoring and scheduling. The transportation personnel may not be able to transport according to the optimal route and time, resulting in low transportation efficiency, increasing the residence time of garbage in the hospital, and further increasing the possibility of pollution spread. At the same time, manual transportation is prone to mistakes, such as garbage dropping and omission, causing pollution to the hospital environment.

[0005] The sorting and recycling link of medical waste is full of problems. Traditional sorting methods mainly rely on manual visual recognition, with low efficiency and poor accuracy, and the sorting personnel are exposed to medical waste for a long time, facing a high risk of infection. In addition, for some special medical waste, such as garbage containing harmful substances, it is difficult to achieve precise classification by manual sorting, which is likely to cause waste of resources and environmental pollution. Moreover, the entire medical waste treatment process lacks an effective traceability mechanism. Once a problem occurs, it is difficult to identify the responsibility and the source.

[0006] With the continuous development of the medical industry, the generation volume of medical waste is increasing day by day, and the traditional treatment methods can no longer meet the actual needs. Therefore, it is of great practical significance to develop an intelligent Internet of Things medical waste sorting and recycling system, method, device, and medium to achieve intelligent and precise treatment of medical waste, improve the treatment efficiency and safety, and reduce environmental pollution. Summary of the Invention

[0007] The intelligent Internet of Things medical waste sorting and recycling system, method, device, and medium proposed by the present invention are used to solve the problems mentioned in the above prior art.

[0008] To achieve the above object, the present invention adopts the following technical solutions: An intelligent IoT medical waste sorting and recycling system includes the following modules:

[0009] Waste collection module: The trash cans set in each department of the hospital are equipped with a weight sensor and a liquid level sensor; the weight sensor adopts microelectromechanical system MEMS technology, and the liquid level sensor is based on the principle of optical interference. When the waste weight W reaches the dynamic threshold W threshold (t) or the liquid level height L reaches the dynamic threshold L threshold (t), the full bucket signal is sent to the central control module through LoRa wireless communication technology based on quantum encryption; the dynamic threshold is adjusted in real time according to the waste generation rules of different departments and different time periods by using time series analysis algorithm, and the formula is expressed as: when W≥W threshold (t) or L≥L threshold (t), send the full bucket signal;

[0010] Data transmission module: Adopt low-power wide area network LPWAN technology combined with satellite communication backup link. At the same time, use chaotic encryption algorithm to encrypt the transmitted data;

[0011] Central control module: Equipped with a server cluster, adopt parallel computing and distributed storage technology, and use deep reinforcement learning algorithm to analyze and process the received data; classify and identify waste pictures through a deep learning model that fuses multi-modal data. According to the algorithm results, combined with the hospital's internal geographic information system GIS and real-time traffic conditions, generate the optimal sorting and recycling plan to control the work of subsequent modules;

[0012] Waste transportation module: Composed of automatic guided vehicle AGV, equipped with a sensor fusion navigation system of laser navigation, visual navigation and inertial navigation, and its driving speed is automatically adjusted according to the path congestion situation and load;

[0013] Intelligent sorting module: At the sorting center, adopt the method of combining Raman spectroscopy analysis technology and robotic arm for waste sorting; the robotic arm adopts a flexible joint design and force feedback control technology, and sorts the waste into different recycling bins according to the analysis results;

[0014] Monitoring and traceability module: Install cameras, temperature and humidity sensors, and gas sensors at various positions of the system to monitor the operation status of the system in real time; record the whole process data of waste collection, transportation, sorting, and recycling through blockchain technology combined with quantum watermark technology.

[0015] Furthermore, it also includes:

[0016] Disinfection module: Set plasma disinfection device and photocatalyst disinfection layer in the trash can and recycling bin; at the same time, the disinfection module automatically adjusts the disinfection parameters according to the type and pollution degree of the waste, including disinfection time and intensity.

[0017] Early warning module: When the system fails or abnormal situations occur, including the AGV deviating from the route, abnormal sensor data, and disinfection module failure, warning messages are sent to the management personnel via text messages, emails, or pop-up windows within the system based on artificial intelligence voice synthesis technology; the warning messages include the type of failure, location of occurrence, time, and preliminary failure diagnosis suggestions.

[0018] Furthermore, the trash cans in the garbage collection module are made of biodegradable composite materials for the barrel body, and the lids are equipped with induction and voice interaction functions, and medical staff can control the opening and closing of the lids through voice commands.

[0019] Furthermore, the data transmission module uses a blockchain network to achieve distributed storage and sharing of data; during the data transmission process, the integrity and accuracy of the data are automatically verified and recorded through contracts; at the same time, edge computing technology is used to perform preliminary processing and screening of data at the trash can end.

[0020] Furthermore, the robotic arms in the sorting module are equipped with collaborative operation and self-repair capabilities; at the same time, the robotic arms are built-in with fault diagnosis and repair algorithms, and when a certain joint or component fails, the working mode can be automatically adjusted to continue to complete the sorting task.

[0021] A method for applying the intelligent IoT medical waste sorting and recycling system described above, including:

[0022] Data collection step: The weight sensors, liquid level sensors, cameras, and environmental sensors in the trash cans of each department collect data on garbage weight, liquid level height, garbage pictures, temperature and humidity, and gas concentration in real time; the collection frequency is dynamically adjusted according to different sensors and actual needs;

[0023] Data preprocessing step: At the trash can end, edge computing technology is used to perform preliminary processing and screening of the collected data, removing noise and invalid data; enhancing and extracting features from the image data, and smoothing the weight and liquid level data;

[0024] Data transmission step: The preprocessed data is encrypted and transmitted to the central control module through LPWAN technology based on quantum encryption and blockchain; an adaptive retransmission mechanism and congestion control algorithm are used during the data transmission process;

[0025] Data analysis and decision-making step: The central control module uses a deep reinforcement learning algorithm to analyze and process the received data; a deep learning model that fuses modal data is used to classify and risk-assess the garbage, and combined with the hospital's internal geographic information system GIS and real-time traffic conditions, a sorting and recycling plan is generated;

[0026] Task execution steps: According to the generated plan, the central control module sends instructions to the AGV of the garbage transportation module, and the AGV transports the full garbage bins to the sorting center; meanwhile, the sorting module sorts the garbage according to the analysis results; during the task execution process, the running status of each module is monitored in real time, and the task allocation and path planning are dynamically adjusted according to the actual situation.

[0027] Monitoring and recording steps: The monitoring and tracing module monitors the running status of the system in real time and records the data of the whole process of garbage collection, transportation, sorting, and recycling; the data is stored in the blockchain, and at the same time, big data analysis technology is used to mine and analyze the historical data.

[0028] Furthermore, it also includes:

[0029] Disinfection and warning steps: During the garbage collection and sorting process, the disinfection module automatically adjusts the disinfection parameters according to the type and pollution degree of the garbage, and performs regular disinfection treatment on the garbage bins and recycling bins; when a fault or abnormal situation occurs in the system, the warning module timely sends warning messages to the management personnel through text messages, emails or pop-up windows within the system based on artificial voice synthesis technology.

[0030] Furthermore, it includes a processor, a memory, and a computer program stored in the memory and running on the processor. The feature is that when the processor executes the computer program, it implements the steps of the method described in any one of claims 7-8; the device adopts an optimized chip architecture to meet the real-time and reliability requirements of the system.

[0031] Furthermore, it includes a computer-readable storage medium. The computer-readable storage medium stores a computer program. The feature is that when the computer program is executed by a processor, it implements the steps of the method described in any one of claims 7-8; the storage medium adopts encrypted storage technology.

[0032] Compared with the existing technologies, the beneficial effects of the present invention are:

[0033] In the garbage collection link, the intelligent garbage bins are equipped with high-precision sensors, which can accurately monitor the garbage status in real time and transmit the data to the central control module through advanced communication technologies. This enables medical staff not to manually check, and the system can automatically remind for cleaning, avoiding garbage overflow, reducing the risk of bacterial growth and cross-infection. At the same time, by dynamically adjusting the full-bin threshold according to different departments and time periods, the garbage cleaning work can be arranged more reasonably, improving the collection efficiency. The garbage transportation module uses an automatic guided vehicle (AGV) with multi-sensor fusion navigation, which has high positioning accuracy, can automatically plan the optimal path, and avoid obstacles. It also has an automatic charging function, which can ensure the efficiency and stability of transportation, reduce the mistakes of manual transportation and the residence time of garbage in the hospital, and reduce the possibility of pollution spread.

[0034] The intelligent sorting module utilizes advanced Raman spectroscopy analysis technology and a robotic arm with flexible joints and force feedback control, enabling it to quickly and accurately identify and sort garbage, thereby improving the sorting efficiency and accuracy. The collaborative operation and self-repair capabilities of the robotic arm further ensure the continuous and stable progress of the sorting work.

[0035] The disinfection module adopts a plasma disinfection device and a photocatalyst disinfection layer, which can effectively kill bacteria and viruses and purify the air. Moreover, it can automatically adjust the disinfection parameters according to the type of garbage and the degree of pollution, enhancing the disinfection effect.

[0036] The monitoring and traceability module, through blockchain and quantum watermarking technologies, realizes real-time monitoring of the entire process of medical waste treatment and information traceability. In case of problems, it can quickly identify the responsibility and the source, ensuring the security and credibility of the data. At the same time, big data analysis technology provides strong support for the optimization and management of the system, making the entire medical waste treatment process more scientific, intelligent, and environmentally friendly. Description of the Drawings

[0037] Figure 1 It is a schematic block diagram of the intelligent IoT medical waste sorting and recycling system proposed by the present invention;

[0038] Figure 2 It is a schematic block diagram of the intelligent IoT medical waste sorting and recycling method proposed by the present invention;

[0039] Figure 3 It is a schematic block diagram of the comparison of the collection efficiency of the intelligent IoT medical waste sorting and recycling proposed by the present invention;

[0040] Figure 4 It is a schematic block diagram of the comparison of the sorting accuracy of the intelligent IoT medical waste sorting and recycling proposed by the present invention. Detailed Embodiments

[0041] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0042] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", etc. is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present invention.

[0043] In addition, the terms "first" and "second" are only used for descriptive purposes and should not be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of the said features. In the description of the present invention, the meaning of "a plurality" is two or more unless otherwise specifically defined. In addition, the terms "mounted", "connected", and "coupled" should be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection; it may be a mechanical connection or an electrical connection; it may be directly connected or indirectly connected through an intermediate medium, and it may be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances. The present invention will be further described in detail below with reference to the drawings.

[0044] Refer to Figures 1 - 4 : An intelligent Internet of Things medical waste sorting and recycling system, including the following modules:

[0045] Waste collection module: A plurality of intelligent trash cans are arranged in each department of the hospital, and high-precision weight sensors and liquid level sensors are provided inside the cans. The weight sensor adopts microelectromechanical system (MEMS) technology with an accuracy of ±0.05 kg, and the liquid level sensor is based on the principle of optical interference with an accuracy of ±0.5%, which can monitor the weight and liquid level height of the trash in the can in real time and accurately. When the trash weight W reaches the dynamic threshold W threshold (t) or the liquid level height L reaches the dynamic threshold L threshold (t), a full-can signal is sent to the central control module through LoRa wireless communication technology based on quantum encryption. The dynamic threshold is adjusted in real time according to the trash generation rules of different departments and different time periods by using a time series analysis algorithm, and the formula is expressed as: when W ≥ W threshold (t) or L > L threshold (t), a full-can signal is sent.

[0046] Data transmission module: Adopt low-power wide-area network (LPWAN) technology combined with a satellite communication backup link. For example, NB-IoT or Sigfox is used as the main link and automatically switches to satellite communication when the ground network signal is poor. The transmission rate of the main link is not less than 20 kbps, and the packet loss rate is less than 0.5%. The transmission rate of the satellite link is not less than 10 kbps, ensuring that data can be delivered stably, accurately, and in a timely manner in various complex environments. At the same time, the chaotic encryption algorithm is used to encrypt the transmitted data, and the key has a high degree of randomness and unpredictability, further ensuring data security.

[0047] Central control module: Equipped with a high-performance server cluster, adopting parallel computing and distributed storage technologies, and using deep reinforcement learning algorithms to analyze and process the received data. Through a deep learning model that fuses multi-modal data (images, weights, liquid levels, etc.), the garbage pictures are classified and identified, and the identification accuracy is not less than 98%. Based on the algorithm results, combined with the hospital's internal geographic information system (GIS) and real-time traffic conditions, an optimal sorting and recycling plan is generated to control the operation of subsequent modules.

[0048] Garbage transportation module: Composed of automated guided vehicles (AGVs), equipped with a multi-sensor fusion navigation system that combines laser navigation, visual navigation, and inertial navigation, with a positioning accuracy of ±2 mm. The AGV adopts an intelligent obstacle avoidance algorithm, can sense the surrounding environment in real time, automatically plan the optimal path, and avoid people and obstacles. Its driving speed is automatically adjusted according to the path congestion and load, with a maximum speed of 2.5 m / s, and it has an automatic charging function. When the battery level is lower than 20%, it automatically returns to the charging area for charging.

[0049] Intelligent sorting module: In the sorting center, Raman spectroscopy analysis technology is combined with a robotic arm for garbage sorting. Raman spectroscopy analysis technology can more accurately and quickly identify the chemical composition and material of garbage, and the identification time does not exceed 0.5 s. The robotic arm adopts a flexible joint design and force feedback control technology, with a repeat positioning accuracy of ±0.2 mm. According to the analysis results, the garbage is sorted into different recycling bins, and the grasping force can be automatically adjusted according to the shape and texture of the garbage. Monitoring and traceability module: Install a variety of sensors such as high-definition cameras, temperature and humidity sensors, and gas sensors at key positions in the system to monitor the operation status of the system in real time. Through blockchain technology combined with quantum watermark technology, the data of the entire process of garbage collection, transportation, sorting, and recycling is recorded to achieve information traceability and ensure that the data cannot be tampered with. The quantum watermark technology adds a unique quantum identifier to the data, further enhancing the security and credibility of the data.

[0050] In the present invention, it further includes:

[0051] Disinfection module. A plasma disinfection device and a photocatalyst disinfection layer are set inside the intelligent trash can and recycling bin. The plasma disinfection device can generate high-concentration plasma, quickly kill bacteria and viruses, and the disinfection efficiency is 30% higher than that of traditional ultraviolet disinfection. The photocatalyst disinfection layer continuously decomposes harmful organic substances under light conditions, effectively purifying the air. At the same time, the disinfection module automatically adjusts disinfection parameters such as disinfection time and intensity according to the type and pollution degree of the garbage.

[0052] Early warning module: When the system has a fault or abnormal situation, such as the AGV deviating from the route, sensor data being abnormal, the disinfection module malfunctioning, etc., warning information is sent to the management personnel by means of text messages, emails or pop-ups within the system based on artificial intelligence voice synthesis technology. The warning information includes the type of fault, the location where it occurs, the time, and preliminary fault diagnosis suggestions, facilitating the management personnel to handle it quickly.

[0053] In the present invention, the intelligent trash can in the garbage collection module is made of a biodegradable composite material for the barrel body, and the barrel lid has intelligent induction and voice interaction functions. The automatic opening and closing of the barrel lid is realized through millimeter-wave radar induction technology, with an induction distance of 15 - 40 cm and an opening and closing time not exceeding 0.8 s. At the same time, medical staff can control the opening and closing of the barrel lid through voice commands, facilitating the disposal of garbage.

[0054] In the present invention, the data transmission module uses a blockchain network to realize the distributed storage and sharing of data. During the data transmission process, the integrity and accuracy of the data are automatically verified and recorded through smart contracts. At the same time, edge computing technology is used to preliminarily process and screen data at the intelligent trash can end, reducing the data transmission volume and improving the system response speed.

[0055] In the present invention, the robotic arm in the intelligent sorting module has the ability of collaborative operation and self-repair. Multiple robotic arms achieve real-time collaboration through wireless communication technology and automatically allocate tasks according to the quantity and distribution of the garbage. At the same time, the robotic arm is built-in with a fault diagnosis and repair algorithm. When it detects that a certain joint or component has a fault, it can automatically adjust the working mode, continue to complete the sorting task, and send a maintenance request in a timely manner.

[0056] The present invention also discloses a method for an intelligent Internet of Things medical waste sorting and recycling system, including the following steps:

[0057] Data acquisition step: Weight sensors, liquid level sensors, cameras, and other environmental sensors in the intelligent trash cans of each department collect multi-modal data such as garbage weight, liquid level height, garbage pictures, temperature and humidity, and gas concentration in real time. The acquisition frequency is dynamically adjusted according to different sensors and actual requirements, and the highest acquisition frequency can reach once per second to ensure the comprehensiveness and real-time nature of the data.

[0058] Data preprocessing step: At the intelligent trash can end, edge computing technology is used to preliminarily process and screen the collected data, removing noise and invalid data. Image data is enhanced and feature extracted, and weight and liquid level data are smoothed to improve data quality.

[0059] Data transmission step: The preprocessed data is encrypted and transmitted to the central control module through LPWAN technology based on quantum encryption and blockchain. An adaptive retransmission mechanism and congestion control algorithm are adopted during data transmission to ensure that the data transmission success rate is not less than 99.5%.

[0060] Data analysis and decision-making step: The central control module uses deep reinforcement learning algorithms to analyze and process the received data. Through a deep learning model that fuses multi-modal data, garbage is classified and risk assessed. Combining with the hospital's internal Geographic Information System (GIS) and real-time traffic conditions, an optimal sorting and recycling plan is generated. At the same time, a prediction model is used to predict the garbage generation volume of each department in the future for a period of time, and resource allocation is prepared in advance.

[0061] Task execution step: According to the generated plan, the central control module sends instructions to the AGV of the garbage transportation module, and the AGV transports the full trash cans to the sorting center. At the same time, the intelligent sorting module sorts the garbage according to the analysis results. During the task execution process, the operating status of each module is monitored in real time, and the task allocation and path planning are dynamically adjusted according to the actual situation.

[0062] Monitoring and recording step: The monitoring and tracing module monitors the system operating status in real time and records the whole process data of garbage collection, transportation, sorting, and recycling. The data is stored in the blockchain, and combined with quantum watermarking technology to ensure that the data cannot be tampered with. At the same time, big data analysis technology is used to mine and analyze historical data to provide decision support for system optimization and management.

[0063] In the present invention, it further includes:

[0064] Disinfection and warning step: During garbage collection and sorting, the disinfection module automatically adjusts the disinfection parameters according to the type and pollution degree of the garbage, and performs regular disinfection on the intelligent trash cans and recycling bins. When a system failure or abnormal situation occurs, the warning module timely sends warning information to the management personnel through SMS, email or pop-up windows within the system based on artificial intelligence voice synthesis technology, and at the same time starts the emergency treatment plan to ensure the stable operation of the system.

[0065] In the present invention, an intelligent Internet of Things medical waste sorting and recycling device includes a processor, a memory, and a computer program stored in the memory and executable on the processor. It is characterized in that when the processor executes the computer program, the steps of the method according to any one of claims 7-8 are implemented. This device adopts a low-power, high-performance chip architecture, has powerful computing capabilities and data processing capabilities, and can meet the real-time and reliability requirements of the system.

[0066] In the present invention, a computer-readable storage medium stores a computer program. It is characterized in that when the computer program is executed by a processor, the steps of the method according to any one of claims 7-8 are implemented. This storage medium adopts encrypted storage technology to ensure the security and reliability of the stored data, preventing data leakage and tampering.

[0067] The beneficial effects are characterized by the following data:

[0068] Evaluation metrics Traditional method The method of this patent Improvement effect Garbage collection efficiency (average cleaning response time) Approximately 2 hours Less than 30 minutes Improvement exceeds 75% Transportation efficiency (average transportation time) Approximately 1 hour Less than 20 minutes Improvement exceeds 66% Sorting accuracy Approximately 80% Not less than 98% Improvement exceeds 22% Disinfection effect (bacteria killing rate) Approximately 70% Greater than 95% Improvement exceeds 35% Data security (data tampering rate) Approximately 1% Approaching 0 Basically eliminate tampering

[0069] Through the above specific implementation manners and data comparison, it can be seen that the intelligent Internet of Things medical waste sorting and recycling system, method, device, and medium of this patent have significant advantages in medical waste treatment, can effectively improve the treatment efficiency, safety, and traceability, and reduce environmental pollution.

[0070] The above is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, makes equivalent replacements or changes, and should be covered by the protection scope of the present invention.

Claims

1. An intelligent Internet of Things medical waste sorting and recycling system, characterized in that, It includes the following modules: Garbage collection module: The trash cans set in each department of the hospital are equipped with a weight sensor and a liquid level sensor; the weight sensor uses MEMS (Micro-Electro-Mechanical System) technology, and the liquid level sensor is based on the principle of optical interference. When the garbage weight W reaches the dynamic threshold W threshold (t) or the liquid level height L reaches the dynamic threshold L threshold (t), the full bucket signal is sent to the central control module through LoRa wireless communication technology based on quantum encryption; the dynamic threshold is adjusted in real time using a time series analysis algorithm according to the garbage generation rules in different departments and different time periods, and the formula is expressed as: when W ≥ W threshold (t) or L ≥ L threshold (t), the full bucket signal is sent; Data transmission module: It uses the low-power wide-area network LPWAN technology combined with a satellite communication backup link. At the same time, it encrypts the transmitted data using a chaotic encryption algorithm; Central control module: It is equipped with a server cluster, uses parallel computing and distributed storage technologies, and uses deep reinforcement learning algorithms to analyze and process the received data; It classifies and identifies garbage pictures through a deep learning model that fuses multi-modal data. According to the algorithm results, combined with the hospital's internal geographic information system GIS and real-time traffic conditions, it generates an optimal sorting and recycling plan to control the work of subsequent modules; Garbage transportation module: It consists of automatic guided vehicles (AGVs), equipped with a sensor fusion navigation system that combines laser navigation, visual navigation, and inertial navigation. Its driving speed is automatically adjusted according to the path congestion and load; Intelligent sorting module: At the sorting center, it uses the method of combining Raman spectroscopy analysis technology with a robotic arm for garbage sorting; the robotic arm adopts a flexible joint design and force feedback control technology, and sorts the garbage into different recycling bins according to the analysis results; Monitoring and traceability module: Cameras, temperature and humidity sensors, and gas sensors are installed at various positions in the system to monitor the system operation status in real time; the data of the garbage collection, transportation, sorting, and recycling processes are recorded through blockchain technology combined with quantum watermark technology.

2. The intelligent Internet of Things medical waste sorting and recycling system according to claim 1, wherein It also includes: Disinfection module: Plasma disinfection devices and photocatalyst disinfection layers are set in the trash cans and recycling bins; At the same time, the disinfection module automatically adjusts the disinfection parameters according to the type and degree of pollution of the garbage, including the disinfection time and intensity.

3. The intelligent Internet of Things medical waste sorting and recycling system according to claim 1, characterized in that, It also includes: Early warning module: When the system fails or abnormal situations occur, including the AGV deviating from the route, sensor data anomalies, and disinfection module failures, it sends early warning messages to the management personnel through text messages, emails, or pop-up windows within the system based on artificial intelligence voice synthesis technology; the early warning messages include the type of failure, the location, time, and preliminary failure diagnosis suggestions.

4. The intelligent IoT medical waste sorting and recycling system according to claim 1, wherein The trash cans in the garbage collection module are made of biodegradable composite materials for the barrel body, and the barrel lids are equipped with induction and voice interaction functions. Medical staff control the opening and closing of the barrel lids through voice commands.

5. The intelligent IoT medical waste sorting and recycling system according to claim 1, wherein The data transmission module uses a blockchain network to achieve distributed storage and sharing of data; during the data transmission process, the integrity and accuracy of the data are automatically verified and recorded through a contract; at the same time, edge computing technology is used to perform preliminary processing and screening of data at the trash can end.

6. The intelligent IoT medical waste sorting and recycling system according to claim 1, wherein The robotic arm in the sorting module is equipped with collaborative operation and self-repair capabilities; at the same time, the robotic arm is built-in with a fault diagnosis and repair algorithm. When it detects that a certain joint or component fails, it automatically adjusts the working mode and continues to complete the sorting task.

7. A method of applying the intelligent IoT medical waste sorting and recycling system according to any one of claims 1-6, characterized in that, It includes: Data acquisition step: The weight sensors, liquid level sensors, cameras, and environmental sensors in the trash cans of each department collect data on garbage weight, liquid level height, garbage pictures, temperature and humidity, and gas concentration in real time; the acquisition frequency is dynamically adjusted according to different sensors and actual needs; Data preprocessing step: At the trash can end, use edge computing technology to preliminarily process and screen the collected data, removing noise and invalid data; enhance and extract features from image data, and smooth the weight and liquid level data; Data transmission step: Encrypt and transmit the preprocessed data to the central control module through LPWAN technology based on quantum encryption and blockchain; adopt an adaptive retransmission mechanism and congestion control algorithm during the data transmission process; Data analysis and decision-making step: The central control module uses a deep reinforcement learning algorithm to analyze and process the received data; Classify and conduct risk assessment on the garbage through a deep learning model that fuses modal data, and generate a sorting and recycling plan by combining the hospital's internal geographic information system GIS and real-time traffic conditions; Task execution step: According to the generated plan, the central control module sends instructions to the AGV of the garbage transportation module, and the AGV transports the full trash cans to the sorting center; at the same time, the sorting module sorts the garbage according to the analysis results; during the task execution process, monitor the running status of each module in real time, and dynamically adjust the task allocation and path planning according to the actual situation; Monitoring and recording step: The monitoring and tracing module monitors the running status of the system in real time, records the data of the whole process of garbage collection, transportation, sorting, and recycling; stores the data in the blockchain, and at the same time, uses big data analysis technology to mine and analyze the historical data.

8. The intelligent IoT medical waste sorting and recycling method according to claim 7, wherein It also includes: Disinfection and warning step: During the garbage collection and sorting process, the disinfection module automatically adjusts the disinfection parameters according to the type and pollution degree of the garbage, and performs regular disinfection on the trash cans and recycling bins; When a fault or abnormal situation occurs in the system, the warning module sends warning messages to the management personnel through text messages, emails or pop-up windows within the system based on artificial voice synthesis technology.

9. An intelligent Internet of Things medical waste sorting and recycling device, comprising a processor, a memory, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it realizes the steps of the method according to any one of claims 7-8; the device adopts an optimized chip architecture to meet the real-time and reliability requirements of the system.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it realizes the steps of the method according to any one of claims 7-8; the storage medium adopts encrypted storage technology.

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