A method for collecting information of intelligent medical waste collection vehicles based on the Internet of Things

Abstract

The present invention relates to the technical field of information collection, and in particular to an information collection method for an intelligent medical waste collection vehicle based on the Internet of Things, comprising the following steps: binding a unique RFID tag to each medical waste container; configuring an RFID reader on the intelligent medical waste collection vehicle to automatically read the RFID tag of the medical waste container when the medical waste container is loaded; multi-tag reading optimization based on intelligent conflict detection and resolution; the present invention performs priority sorting and realizes dynamic optimization reading of conflicting tags. The mechanism effectively avoids reading conflicts in a multi-tag environment, improves the overall reading efficiency of the system, and ensures that high-risk waste information can be obtained in a priority and timely manner, thereby significantly improving the accuracy and reliability of information collection.

Description

Technical Field

[0001] The present invention relates to the technical field of information collection, and in particular to an information collection method for an intelligent medical waste collection vehicle based on the Internet of Things. Background Art

[0002] The safe management and disposal of medical waste is a vital part of the modern medical system. Because it is infectious, toxic and potentially dangerous, if it is not managed properly, it will not only cause serious pollution to the ecological environment, but also threaten health. At present, the management of medical waste mostly relies on manual operations, from waste classification, information registration to collection and transportation, and then to final disposal. The process is cumbersome and error-prone. In addition, with the increase in the number of medical institutions and the significant increase in the amount of medical waste generated, the traditional management model has been difficult to meet the requirements of efficiency and safety.

[0003] As a new type of medical waste management equipment, the intelligent medical waste collection vehicle introduces the Internet of Things technology and radio frequency identification (RFID) technology to realize the automatic collection and transmission of waste information, providing a new idea for improving the efficiency of medical waste management. However, the existing intelligent medical waste collection vehicle system still has the following technical limitations:

[0004] Multi-tag conflict problem: When the collection vehicle reads the RFID tags of multiple containers at the same time, the communication signals between the tags may conflict (such as frequency conflict or time slot competition between tags), resulting in reduced reading efficiency or loss of some tag information.

[0005] Information is not updated in a timely manner: The weight, storage time and other information of medical waste may change during the collection process, but traditional RFID tags mainly record statically and it is difficult to reflect changes in the status of waste in a timely manner.

[0006] Insufficient conflict detection and time slot optimization technology: Existing RFID systems deal with tag communication conflicts mostly by fixed time slot allocation or inefficient global rearrangement, which cannot meet the needs of efficient data collection in complex dynamic environments. Summary of the invention

[0007] The present invention provides an information collection method for an intelligent medical waste collection vehicle based on the Internet of Things.

[0008] An information collection method for an intelligent medical waste collection vehicle based on the Internet of Things comprises the following steps:

[0009] S1, medical waste container tag initialization: bind a unique RFID tag to each medical waste container;

[0010] S2, intelligent collection of tag information: the smart medical waste collection vehicle is equipped with an RFID reader, which automatically reads the RFID tag of the medical waste container when the medical waste container is loaded. A weight sensor is configured in the load compartment of the smart medical waste collection vehicle. When reading the RFID tag information, the weight information recorded in the tag is verified through the weight sensor in the load compartment. If a deviation is found, the weight is automatically updated and marked as abnormal;

[0011] S3, multi-tag reading optimization based on intelligent conflict detection and resolution:

[0012] S31, embedding a conflict detection unit based on spectrum analysis in the RFID reader of the intelligent medical waste collection vehicle to monitor the frequency occupancy status and conflict occurrence time slot of the RFID tag communication signal in real time;

[0013] S32, in order to solve the time slot problem caused by conflicts in RFID tag communication, a time slot allocation protocol is introduced. The time slot allocation protocol pre-allocates time slots through a fast negotiation mechanism, and reads RFID tag information according to tag priority. The tag priority is determined by a linear weighted model, and the priority of RFID tags in reading conflicts is dynamically sorted to ensure that important information is read first.

[0014] Optionally, the S1 specifically includes:

[0015] S11, label generation and content entry: input identification data including medical waste category, source department, hazard level, generation time and expected storage period through the medical waste management platform. After the waste container is weighed, the weight information is added to the identification data to form complete label data;

[0016] S12, label printing and attachment: using RFID printing equipment to print the identification data, print the corresponding RFID label, and attach the printed RFID label to the medical waste container.

[0017] Optionally, S1 also includes NFC device verification: after the RFID tag is attached, the RFID tag content is read by the NFC device and verified and compared with the identification data generated in the medical waste management platform. The verification content includes the integrity of the RFID tag (whether it contains all necessary information), accuracy (whether the data matches the waste attributes) and uniqueness (whether the tag ID is repeated with other waste containers). If the verification passes, the tag is marked as valid and stored in the medical waste management platform; if the verification fails, an automatic reminder is given to regenerate or update the tag content; the successfully bound RFID tag information is uploaded to the medical waste management platform to establish a long-term association between the RFID tag and the medical waste container; the status of the waste container is tracked in real time in the management platform, including storage period warning and dynamic management of the container.

[0018] Optionally, the S2 specifically includes:

[0019] S21, installing an RFID reader at the loading port of the smart medical waste collection vehicle, the RFID reader covers the loading area through a multi-antenna array distribution, ensuring that the RFID tag signal can be quickly captured when the waste container enters the carrying bin;

[0020] S22, when the medical waste container is loaded into the carriage, the RFID reader is triggered to detect the RFID tag signal in real time and automatically read the tag data, including category, source department, weight, hazard level, generation time and expected storage period. After successful reading, the current status of the medical waste container in the medical waste management platform is updated.

[0021] Optionally, a multi-point distributed weight sensor is configured at the bottom of the load-bearing bin of the intelligent medical waste collection vehicle to collect the total weight and partition weight distribution in the load-bearing bin in real time. When the medical waste container is loaded, the weight sensor detects the weight change of the newly added medical waste container and generates the actual weight data of the current medical waste container. The weight of the medical waste container read by the RFID tag is compared with the actual weight collected by the load-bearing bin weight sensor. If it is detected that the weight deviation exceeds the set threshold, the RFID tag of the current medical waste container is automatically marked as abnormal, and the actual weight data is updated in the RFID tag data.

[0022] Optionally, the S31 specifically includes:

[0023] Spectrum sensing and conflict identification: The conflict detection unit senses the frequency occupancy of the RFID tag communication signal in real time through the embedded spectrum analysis chip. The spectrum analysis chip uses the time domain distribution analysis algorithm to detect the time distribution of signal transmission and mark the RFID tag communication activities with overlapping signals in the same time slot.

[0024] Time slot detection and positioning: When a signal conflict is detected, the signal overlap of multiple tags is detected in the time domain. The time slot distribution and degree of overlap of the signals are mainly calculated. The specific time slot where the conflict occurs is located by calculating the strength, frequency characteristics and time characteristics of the RFID tag signal.

[0025] Optionally, the time domain distribution analysis algorithm specifically includes:

[0026] Power density calculation: ,in, Indicates frequency The power spectral density under is the time domain representation of the RFID tag signal, is the signal sampling duration, is the frequency, Indicates signal The Fourier transform result is used to map the signal from the time domain to the frequency domain. is the complex exponential kernel function of the Fourier transform, Represents the square of the complex number, which is used to convert the time domain signal into the frequency domain signal, representing the frequency The mapping of the sine wave in the time domain, the power spectral density When the set power threshold is exceeded, it indicates that the frequency is occupied;

[0027] The frequency occupancy status detection conditions are: ,in, Indicates frequency The occupancy status, 1 means occupied, 0 means idle, Indicates the power threshold of spectrum occupancy. It is set according to the statistical characteristics of the background noise power.

[0028] Optionally, the time slot set allocated by the RFID tag signal is defined as:

[0029] ,in, is the set of allocated time slots, is the total number of allocated time slots, in which middle, For the The detection condition for signal strength overlap is:

[0030] ;

[0031] in, It is a time slot The conflict status (1 means conflict, 0 means no conflict), It is an RFID tag In time slot The instantaneous signal strength in It is in the time slot The number of RFID tags communicating in It is the timeslot signal strength conflict threshold, which is set according to the system signal-to-noise ratio.

[0032] Conflicting tag positioning: If , locate the conflicting tags by calculating the contribution signal strength of each tag:

[0033] ,in, Represents the set of RFID tags that collide. It is the conflict contribution ratio threshold, which is used to filter out tags that have a greater impact on the conflict.

[0034] Optionally, the S32 specifically includes:

[0035] S321, fast negotiation mechanism to achieve time slot pre-allocation: after conflict detection, the fast negotiation mechanism is used to dynamically adjust the time slot allocation of the RFID tag, and a specific communication time slot is allocated to each RFID tag to ensure that there is no overlap between the time slots;

[0036] S322, dynamic sorting of tag priorities: based on the signal strength of the RFID tag, the distance between the RFID tag and the reader, and the hazard level of the waste, a multidimensional feature vector is generated, and a linear weighted model is used to dynamically prioritize the multidimensional feature vectors of the conflicting tags.

[0037] S323, priority-driven tag reading: according to the sorting results, the communication time slots are allocated in chronological order, and the earlier communication time slots of high-risk waste tags are allocated first to ensure the timely reading of their information.

[0038] Optionally, the multidimensional feature vector is expressed as: ,in, Representation Tags A multidimensional feature vector of is used to describe its priority, Representation Tags The signal strength is measured by the RFID reader; Indicates RFID tag The distance to the reader is directly calculated through the signal propagation time. Representation Tags The hazard level of the waste;

[0039] The linear weighted model calculates the label The overall priority , and based on To sort:

[0040] ,in, Yes Tags The comprehensive priority of the , the larger the value, the higher the priority. They are all feature weight coefficients, which are used to balance the impact of each feature on the priority. Set to 0.5, Set to 0.3, Set to 0.2, It represents the inverse of the distance, which means that the tags closer to the reader have higher priority;

[0041] The fast negotiation mechanism dynamically adjusts the time slot allocation of the RFID tag as follows:

[0042] ,in, Indicates RFID tag The start time of the allocated time slot, is the start time of the communication slot, is the duration of each time slot, It is an RFID tag The reading order is determined by the priority sorting result.

[0043] Beneficial effects of the present invention:

[0044] The present invention embeds a conflict detection unit based on spectrum analysis in the RFID reader, and realizes an efficient solution to the conflict problem by real-time monitoring of the frequency occupancy status of the communication signal and the time slot where the conflict occurs, combined with a dynamically adjusted enhanced time slot allocation protocol. The method avoids the reading failure problem caused by frequency interference and time slot competition in the traditional method by combining conflict detection with time slot allocation, and further optimizes the time slot allocation strategy by using a batch negotiation mechanism, ensuring that the information collection task can still be efficiently completed in a complex multi-tag communication environment.

[0045] The present invention aims at the conflict problem in RFID tag communication, introduces a fast negotiation mechanism of the time slot allocation protocol, prioritizes the reading order of high-risk waste tags by dynamically allocating communication time slots, generates multi-dimensional feature vectors based on tag signal strength, distance, and hazard level, and performs priority sorting, thereby realizing dynamic optimization reading of conflicting tags. This mechanism effectively avoids reading conflicts in a multi-tag environment, improves the overall reading efficiency of the system, and ensures that high-risk waste information can be obtained in a priority and timely manner, significantly improving the accuracy and reliability of information collection.

[0046] The present invention binds a unique RFID tag to each medical waste container and verifies the tag information in combination with a load-bearing bin weight sensor. It can dynamically collect multi-dimensional data such as the category, source department, weight, and hazard level of medical waste, and automatically update and mark abnormal weight information. It supports waste traceability and status monitoring based on real-time data upload and storage on a medical waste management platform. This precise full life cycle management method not only reduces human errors, but also provides efficient technical guarantees for the safe disposal of medical waste. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0048] Figure 1A schematic diagram of a method flow chart of an embodiment of the present invention;

[0049] Figure 2 A schematic diagram of tag priority sorting according to an embodiment of the present invention. DETAILED DESCRIPTION

[0050] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. At the same time, it is explained here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and those skilled in the art may also adopt other alternatives to implement some known technologies; and the accompanying drawings are only for more specific description of the embodiments, and are not intended to specifically limit the present invention.

[0051] It should be noted that the references to "one embodiment", "embodiment", "exemplary embodiments", "some embodiments" and the like in the specification indicate that the embodiments described may include specific features, structures or characteristics, but not every embodiment may include the specific features, structures or characteristics. In addition, when a specific feature, structure or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the art to implement such feature, structure or characteristic in conjunction with other embodiments (whether or not explicitly described).

[0052] In general, a term can be understood, at least in part, from its use in context. For example, depending, at least in part, on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending, at least in part, on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0053] like Figure 1-Figure 2 As shown, a method for collecting information of an intelligent medical waste collection vehicle based on the Internet of Things comprises the following steps:

[0054] S1, medical waste container tag initialization: bind a unique RFID tag to each medical waste container;

[0055] S2, intelligent collection of tag information: the intelligent medical waste collection vehicle is equipped with a high-sensitivity RFID reader, which automatically reads the RFID tag of the medical waste container when the medical waste container is loaded. A weight sensor is configured in the load compartment of the intelligent medical waste collection vehicle. When reading the RFID tag information, the weight information recorded by the tag is verified through the weight sensor in the load compartment. If a deviation is found, the weight is automatically updated and marked as abnormal;

[0056] S3, multi-tag reading optimization based on intelligent conflict detection and resolution:

[0057] S31, embedding a conflict detection unit based on spectrum analysis in the RFID reader of the intelligent medical waste collection vehicle to monitor the frequency occupancy status and conflict occurrence time slot of the RFID tag communication signal in real time;

[0058] S32, in order to solve the time slot problem caused by conflicts in RFID tag communication, a time slot allocation protocol is introduced. The time slot allocation protocol pre-allocates time slots through a fast negotiation mechanism, reads RFID tag information according to tag priority, and gives priority to the reading of high-risk waste tags; the tag priority is determined by a linear weighted model, and the priority of RFID tags in the reading conflict is dynamically sorted to ensure that important information is read first;

[0059] The conflict identification and resolution data are uploaded to the medical waste management platform to optimize subsequent tag placement strategies and reader parameter configurations.

[0060] S1 specifically includes:

[0061] S11, label generation and content entry: input identification data including medical waste category, source department, hazard level, generation time and expected storage period through the medical waste management platform. After the waste container is weighed, the weight information is added to the identification data to form complete label data;

[0062] S12, label printing and attachment: using RFID printing equipment to print the identification data, print the corresponding RFID label, and attach the printed RFID label to the medical waste container.

[0063] S1 also includes NFC device verification: after the RFID tag is attached, the RFID tag content is read through the NFC device and verified and compared with the identification data generated in the medical waste management platform. The verification content includes the integrity of the RFID tag (whether it contains all necessary information), accuracy (whether the data matches the waste attributes) and uniqueness (whether the tag ID is repeated in other waste containers). If the verification passes, the tag is marked as valid and stored in the medical waste management platform; if the verification fails, an automatic reminder is given to regenerate or update the tag content; the successfully bound RFID tag information is uploaded to the medical waste management platform to establish a long-term association between the RFID tag and the medical waste container; the status of the waste container is tracked in real time on the management platform, including storage period warnings and dynamic management of the container.

[0064] S2 specifically includes:

[0065] S21, installing an RFID reader at the loading port of the smart medical waste collection vehicle, the RFID reader covers the loading area through a multi-antenna array distribution, ensuring that the RFID tag signal can be quickly captured when the waste container enters the carrying bin;

[0066] S22, when the medical waste container is loaded into the carriage, the RFID reader is triggered to detect the RFID tag signal in real time and automatically read the tag data, including category, source department, weight, hazard level, generation time and expected storage period. After successful reading, the current status of the medical waste container in the medical waste management platform is updated.

[0067] The bottom of the load-bearing bin of the intelligent medical waste collection vehicle is equipped with multi-point distributed weight sensors to collect the total weight and partition weight distribution in the load-bearing bin in real time. When the medical waste container is loaded, the weight sensor detects the weight change of the newly added medical waste container and generates the actual weight data of the current medical waste container. The weight of the medical waste container read by the RFID tag is compared with the actual weight collected by the load-bearing bin weight sensor. If the weight deviation is detected to exceed the set threshold, the RFID tag of the current medical waste container is automatically marked as abnormal, and the actual weight data is updated in the RFID tag data;

[0068] At the same time, the abnormal records will be uploaded to the medical waste management platform, and an abnormal handling notification will be generated for subsequent management personnel to review and handle.

[0069] S31 specifically includes:

[0070] Spectrum sensing and conflict identification: The conflict detection unit senses the frequency occupancy of the RFID tag communication signal in real time through the embedded spectrum analysis chip. The spectrum analysis chip uses the time domain distribution analysis algorithm to detect the time distribution of signal transmission and mark the RFID tag communication activities with overlapping signals in the same time slot.

[0071] Time slot detection and positioning: When a signal conflict is detected, the signal overlap of multiple tags is detected in the time domain. The time slot distribution and degree of overlap of the signals are mainly calculated. The specific time slot where the conflict occurs is located by calculating the strength, frequency characteristics and time characteristics of the RFID tag signal.

[0072] The time domain distribution analysis algorithm specifically includes:

[0073] Power density calculation: ,in, Indicates frequency The power spectral density under is the time domain representation of the RFID tag signal, is the signal sampling duration, is the frequency, Indicates signal The Fourier transform result is used to map the signal from the time domain to the frequency domain. is the complex exponential kernel function of the Fourier transform, Represents the square of the complex number, which is used to convert the time domain signal into the frequency domain signal, representing the frequency The mapping of the sine wave in the time domain, the power spectral density When the set power threshold is exceeded, it indicates that the frequency is occupied;

[0074] The frequency occupancy status detection conditions are: ,in, Indicates frequency The occupancy status, 1 means occupied, 0 means idle, Indicates the power threshold of spectrum occupancy. According to the statistical characteristics of background noise power:

[0075] ,in, : The average power of background noise, obtained through historical data statistics of idle frequency bands, :Adjustment factor, take , used to tolerate noise fluctuations within a certain range. In simple terms, The value is set to 1.5 to 3 times the background noise power to distinguish the actual signal from the background noise.

[0076] The set of time slots allocated to RFID tag signals is defined as:

[0077] ,in, is the set of allocated time slots, is the total number of allocated time slots, in which middle, For the The detection condition for signal strength overlap is:

[0078] ;

[0079] in, It is a time slot The conflict status (1 means conflict, 0 means no conflict), It is an RFID tag In time slot The instantaneous signal strength in It is in the time slot The number of RFID tags communicating in is the timeslot signal strength conflict threshold, which is set according to the system signal-to-noise ratio;

[0080] Timeslot signal strength conflict threshold According to the system's signal-to-noise ratio (SNR) and the maximum supported signal strength accumulation setting: ,in, : The maximum strength of a single tag signal, measured based on the communication power range between the tag and the reader, : The permitted ratio of label conflict accumulation, taken , indicating that the total strength exceeds to When a conflict occurs, It is the maximum value of the accumulated tag signal strength that the system can tolerate and is used to determine conflicts.

[0081] Conflicting tag positioning: If , locate the conflicting tags by calculating the contribution signal strength of each tag:

[0082] ,in, Represents the set of RFID tags that collide. It is the conflict contribution ratio threshold, which is used to filter out tags that have a greater impact on the conflict.

[0083] Frequency occupancy status detection is the basis for time slot conflicts:

[0084] In a time slot ti, if multiple signals occupy the same frequency (or the frequencies overlap), frequency competition will inevitably lead to conflicts.

[0085] Timeslot conflict is the manifestation of frequency occupancy in the time domain: even if a frequency occupancy conflict occurs, if these signals are scheduled in different timeslots, no timeslot conflict will occur. Therefore, frequency occupancy does not necessarily lead to timeslot conflict.

[0086] Comprehensive judgment: The judgment of time slot conflict needs to be combined with the frequency occupancy status and the signal strength in the time slot: if frequency occupancy occurs but the signal strength does not exceed Sthreshold, the time slot may still be considered to be conflict-free; if frequency occupancy occurs and the accumulated signal strength exceeds the threshold, it is determined to be a time slot conflict.

[0087] The relationship between the frequency occupancy status and the time slot conflict status is as follows:

[0088] Frequency occupancy status is the basis and determines whether a conflict is likely to occur;

[0089] The time slot conflict status is the specific manifestation of the frequency occupancy status in the time domain, and combined with the signal strength, it can further confirm whether the conflict actually occurs.

[0090] S32 specifically includes:

[0091] S321, fast negotiation mechanism to achieve time slot pre-allocation: after conflict detection, the fast negotiation mechanism is used to dynamically adjust the time slot allocation of the RFID tag, and a specific communication time slot is allocated to each RFID tag to ensure that there is no overlap between the time slots;

[0092] S322, dynamic sorting of tag priorities: generating a multidimensional feature vector based on the signal strength of the RFID tag, the distance between the RFID tag and the reader, and the hazard level of the waste, and dynamically sorting the multidimensional feature vectors of the conflicting tags using a linear weighted model;

[0093] Tag priority sorting rules:

[0094] High-hazard waste labels take precedence over general waste labels;

[0095] Tags with high signal strength take precedence over tags with weak signals;

[0096] Among tags of the same category, tags closer to the reader take priority.

[0097] S323, priority-driven tag reading: according to the sorting results, the communication time slots are allocated in chronological order, and the earlier communication time slots of high-risk waste tags are allocated first to ensure the timely reading of their information.

[0098] The multidimensional feature vector is represented as: ,in, Representation Tags A multidimensional feature vector of is used to describe its priority, Representation Tags The signal strength is measured by the RFID reader; Indicates RFID tag The distance to the reader is directly calculated through the signal propagation time. Representation Tags The hazard level of the waste;

[0099] Linear weighted model calculation tags The overall priority , and based on To sort:

[0100] ,in, Yes Tags The comprehensive priority of the , the larger the value, the higher the priority. They are all feature weight coefficients, which are used to balance the impact of each feature on the priority. Set to 0.5, Set to 0.3, Set to 0.2, It represents the inverse of the distance, which means that the tags closer to the reader have higher priority;

[0101] The fast negotiation mechanism dynamically adjusts the time slot allocation of RFID tags as follows:

[0102] ,in, Indicates RFID tag The start time of the allocated time slot, is the start time of the communication slot, is the duration of each time slot, It is an RFID tag The reading order is determined by the priority sorting result.

[0103] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0104] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for collecting information of an intelligent medical waste collection vehicle based on the Internet of Things, characterized in that: The following steps are involved: S1, medical waste container tag initialization: bind a unique RFID tag to each medical waste container; S2, intelligent collection of tag information: the smart medical waste collection vehicle is equipped with an RFID reader, which automatically reads the RFID tag of the medical waste container when the medical waste container is loaded. A weight sensor is configured in the load compartment of the smart medical waste collection vehicle. When reading the RFID tag information, the weight information recorded in the tag is verified through the weight sensor in the load compartment. If a deviation is found, the weight is automatically updated and marked as abnormal; S3, multi-tag reading optimization based on intelligent conflict detection and resolution: S31, embedding a conflict detection unit based on spectrum analysis in the RFID reader of the intelligent medical waste collection vehicle to monitor the frequency occupancy status and conflict occurrence time slot of the RFID tag communication signal in real time; S32, in order to solve the time slot problem caused by conflicts in RFID tag communication, a time slot allocation protocol is introduced. The time slot allocation protocol pre-allocates time slots through a fast negotiation mechanism, and reads RFID tag information according to tag priority. The tag priority is determined by a linear weighted model, and the priority of RFID tags in reading conflicts is dynamically sorted to ensure that important information is read first.

2. According to the method for collecting information of an intelligent medical waste collection vehicle based on the Internet of Things in claim 1, it is characterized in that: The S1 specifically includes: S11, label generation and content entry: input identification data including medical waste category, source department, hazard level, generation time and expected storage period through the medical waste management platform. After the waste container is weighed, the weight information is added to the identification data to form complete label data; S12, label printing and attachment: using RFID printing equipment to print the identification data, print the corresponding RFID label, and attach the printed RFID label to the medical waste container.

3. The method for collecting information of an intelligent medical waste collection vehicle based on the Internet of Things according to claim 2 is characterized in that: The S1 also includes NFC device verification: after the RFID tag is attached, the RFID tag content is read by the NFC device and compared with the identification data generated in the medical waste management platform. The verification content includes the integrity, accuracy and uniqueness of the RFID tag; the successfully bound RFID tag information is uploaded to the medical waste management platform to establish a long-term association between the RFID tag and the medical waste container.

4. The method for collecting information of an intelligent medical waste collection vehicle based on the Internet of Things according to claim 1 is characterized in that: The S2 specifically includes: S21, installing an RFID reader at the loading port of the smart medical waste collection vehicle, and the RFID reader covers the loading area through a multi-antenna array distribution; S22, when the medical waste container is loaded into the carriage, the RFID reader is triggered to detect the RFID tag signal in real time and automatically read the tag data, including category, source department, weight, hazard level, generation time and expected storage period. After successful reading, the current status of the medical waste container in the medical waste management platform is updated.

5. The method for collecting information of an intelligent medical waste collection vehicle based on the Internet of Things according to claim 4 is characterized in that: The bottom of the load-bearing bin of the intelligent medical waste collection vehicle is configured with multi-point distributed weight sensors to collect the total weight and partition weight distribution in the load-bearing bin in real time. When the medical waste container is loaded, the weight sensor detects the weight change of the newly added medical waste container and generates the actual weight data of the current medical waste container. The weight of the medical waste container read by the RFID tag is compared with the actual weight collected by the load-bearing bin weight sensor. If it is detected that the weight deviation exceeds the set threshold, the RFID tag of the current medical waste container is automatically marked as abnormal, and the actual weight data is updated in the RFID tag data.

6. The method for collecting information of an intelligent medical waste collection vehicle based on the Internet of Things according to claim 1 is characterized in that: The S31 specifically includes: Spectrum sensing and conflict identification: The conflict detection unit senses the frequency occupancy of the RFID tag communication signal in real time through the embedded spectrum analysis chip. The spectrum analysis chip uses the time domain distribution analysis algorithm to detect the time distribution of signal transmission and mark the RFID tag communication activities with overlapping signals in the same time slot. Time slot detection and positioning: When a signal conflict is detected, the specific time slot where the conflict occurs is located by calculating the strength, frequency characteristics and time characteristics of the RFID tag signal.

7. The method for collecting information of an intelligent medical waste collection vehicle based on the Internet of Things according to claim 6 is characterized in that: The time domain distribution analysis algorithm specifically includes: Power density calculation: ,in, Indicates frequency The power spectral density under is the time domain representation of the RFID tag signal, is the signal sampling duration, is the frequency, Indicates signal The Fourier transform result is, is the complex exponential kernel function of the Fourier transform, Represents the square of the complex number, power spectral density When the set power threshold is exceeded, it indicates that the frequency is occupied; The frequency occupancy status detection conditions are: ,in, Indicates frequency The occupancy status, 1 means occupied, 0 means idle, Indicates the power threshold of spectrum occupancy.

8. The method for collecting information of an intelligent medical waste collection vehicle based on the Internet of Things according to claim 7 is characterized in that: The time slot set allocated by the RFID tag signal is defined as: ,in, is the set of allocated time slots, is the total number of allocated time slots, in which middle, For the The detection condition for signal strength overlap is: ； in, It is a time slot The conflict state It is an RFID tag In time slot The instantaneous signal strength in It is in the time slot The number of RFID tags communicating in is the timeslot signal strength conflict threshold; Conflicting tag positioning: If , locate the conflicting tags by calculating the contribution signal strength of each tag: ,in, Represents the set of RFID tags that collide. is the conflict contribution ratio threshold.

9. The method for collecting information of an intelligent medical waste collection vehicle based on the Internet of Things according to claim 8 is characterized in that: The S32 specifically includes: S321, fast negotiation mechanism to achieve time slot pre-allocation: after conflict detection, the fast negotiation mechanism is used to dynamically adjust the time slot allocation of the RFID tag, and a specific communication time slot is allocated to each RFID tag to ensure that there is no overlap between the time slots; S322, dynamic sorting of tag priorities: generating a multidimensional feature vector based on the signal strength of the RFID tag, the distance between the RFID tag and the reader, and the hazard level of the waste, and dynamically sorting the multidimensional feature vectors of the conflicting tags using a linear weighted model; S323, priority-driven tag reading: according to the sorting result, the time sequence of the communication time slots is allocated.

10. The method for collecting information of an intelligent medical waste collection vehicle based on the Internet of Things according to claim 9, characterized in that: The multidimensional feature vector is expressed as: ,in, Representation Tags The multidimensional feature vector of Representation Tags Signal strength; Indicates RFID tag The distance from the reader, Representation Tags The hazard level of the waste; The linear weighted model calculates the label The overall priority , and based on To sort: ,in, Yes Tags The comprehensive priority of the , the larger the value, the higher the priority. They are all feature weight coefficients, which are used to balance the impact of each feature on the priority. It represents the inverse of the distance, which means that the tag closer to the reader has higher priority; The fast negotiation mechanism dynamically adjusts the time slot allocation of the RFID tag as follows: ,in, Indicates RFID tag The start time of the allocated time slot, is the start time of the communication slot, For the duration of each time slot, It is an RFID tag The reading order is determined by the priority sorting result.

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