CN119670778B - Intelligent medical waste collection vehicle information acquisition method based on Internet of things - Google Patents
Intelligent medical waste collection vehicle information acquisition method based on Internet of things Download PDFInfo
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- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K7/00—Methods or arrangements for sensing record carriers, e.g. for reading patterns
- G06K7/10—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation
- G06K7/10009—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation sensing by radiation using wavelengths larger than 0.1 mm, e.g. radio-waves or microwaves
- G06K7/10019—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation sensing by radiation using wavelengths larger than 0.1 mm, e.g. radio-waves or microwaves resolving collision on the communication channels between simultaneously or concurrently interrogated record carriers.
- G06K7/10069—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation sensing by radiation using wavelengths larger than 0.1 mm, e.g. radio-waves or microwaves resolving collision on the communication channels between simultaneously or concurrently interrogated record carriers. the collision being resolved in the frequency domain, e.g. by hopping from one frequency to the other
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- G06K7/10—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation
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- G06K7/10366—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation sensing by radiation using wavelengths larger than 0.1 mm, e.g. radio-waves or microwaves the interrogation device being adapted for miscellaneous applications
- G06K7/10415—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation sensing by radiation using wavelengths larger than 0.1 mm, e.g. radio-waves or microwaves the interrogation device being adapted for miscellaneous applications the interrogation device being fixed in its position, such as an access control device for reading wireless access cards, or a wireless ATM
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Abstract
本发明涉及信息采集技术领域，具体涉及一种基于物联网的智能医疗废物收集车信息采集方法，包括以下步骤：为每个医疗废物容器绑定唯一的RFID标签；智能医疗废物收集车配置RFID阅读器，在医疗废物容器装载时自动读取医疗废物容器的RFID标签；基于智能冲突检测与消解的多标签读取优化；本发明，进行优先级排序，实现了对冲突标签的动态优化读取，该机制有效避免了多标签环境下的读取冲突，提高了系统的整体读取效率，同时确保高危废物信息能够被优先、及时地获取，显著提升了信息采集的准确性和可靠性。
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
The invention relates to the technical field of information acquisition, in particular to an intelligent medical waste collection vehicle information acquisition method based on the Internet of things.
Background
The safety management and disposal of medical waste are a vital part of modern medical systems, because of the infectivity, toxicity and potential danger, if the management is incorrect, serious pollution to the ecological environment can be caused, health can be threatened, at the present stage, the management of medical waste is mostly dependent on manual operation, from waste classification, information registration to collection and transportation, and then to final disposal, the process is tedious and error-prone, and in addition, along with the increase of the number of medical institutions and the remarkable improvement of the production amount of medical waste, the traditional management mode has difficulty in meeting the requirements of high efficiency and safety.
The intelligent medical waste collection vehicle is used as novel medical waste management equipment, the internet of things technology and the Radio Frequency Identification (RFID) technology are introduced, automatic collection and transmission of waste information are realized, a new thought is provided for improving the medical waste management efficiency, however, the existing intelligent medical waste collection vehicle system still has the following technical limitations:
Multi-tag collision problem-when the collection vehicle reads RFID tags of a plurality of containers at the same time, collision of communication signals between the tags (e.g., frequency collision or time slot competition between the tags) may occur, resulting in a decrease in reading efficiency or loss of part of tag information.
The dynamic update of the information is not timely, the weight, the storage time and other information of the medical waste can be changed in the collecting process, but the traditional RFID tag mainly records statically, and the state change of the waste is difficult to reflect timely.
The conflict detection and time slot optimization technology is insufficient, the existing RFID system is mainly used for processing the communication conflict of the tag, namely fixed time slot allocation or low-efficiency global rearrangement is adopted, and the high-efficiency data acquisition requirement in a complex dynamic environment cannot be met.
Disclosure of Invention
The invention provides an intelligent medical waste collection vehicle information acquisition method based on the Internet of things.
An intelligent medical waste collection vehicle information acquisition method based on the Internet of things comprises the following steps:
s1, initializing medical waste container labels, namely binding a unique RFID label for each medical waste container;
S2, intelligently acquiring tag information, namely configuring an RFID reader by the intelligent medical waste collection vehicle, automatically reading an RFID tag of a medical waste container when the medical waste container is loaded, configuring a weight sensor in a bearing bin of the intelligent medical waste collection vehicle, verifying the weight information recorded by the tag through the weight sensor in the bearing bin when the RFID tag information is read, and automatically updating the weight and marking the weight as abnormal if deviation is found;
s3, multi-tag reading optimization based on intelligent conflict detection and resolution:
s31, embedding a conflict detection unit based on spectrum analysis in an RFID reader of the intelligent medical waste collection vehicle, and monitoring the frequency occupation state of an RFID tag communication signal and conflict occurrence time slots in real time;
s32, aiming at the problem of time slots generated by conflict in RFID tag communication, introducing a time slot allocation protocol, pre-allocating time slots by the time slot allocation protocol through a quick negotiation mechanism, and reading RFID tag information according to tag priority ordering, wherein the tag priority ordering is determined by using a linear weighting model, and dynamically ordering the RFID tag priorities in the reading conflict, so that important information is ensured to be read preferentially.
Optionally, the S1 specifically includes:
S11, label generation and content input, namely inputting identification data comprising medical waste types, source departments, hazard grades, generation time and expected storage period through a medical waste management platform, and adding weight information into the identification data after weighing a waste container to form complete label data;
And S12, printing and attaching the label, namely printing the identification data by using an RFID printing device, printing the corresponding RFID label, and attaching the printed RFID label to the medical waste container.
Optionally, the S1 further comprises verification by the NFC device, wherein after the RFID tag is attached, the RFID tag content is read through the NFC device and is compared with identification data generated in the medical waste management platform, the verification content comprises the integrity (whether all necessary information is contained), the accuracy (whether the data is matched with the waste attribute) and the uniqueness (whether the tag ID is repeated with other waste containers) of the RFID tag, if the verification is passed, the tag is marked as valid and stored in the medical waste management platform, if the verification is failed, the tag content is automatically reminded to be regenerated or updated, the successfully bound RFID tag information is uploaded to the medical waste management platform, the long-term association relation between the RFID tag and the medical waste container is established, and the state of the waste container is tracked in real time in the management platform, wherein the real-time management platform comprises storage period early warning and dynamic management of the container.
Optionally, the S2 specifically includes:
S21, installing RFID readers at a loading port of the intelligent medical waste collection vehicle, wherein the RFID readers cover a loading area through multi-antenna array distribution, so that RFID tag signals can be rapidly captured when a waste container enters a bearing bin;
S22, when the medical waste container is loaded into the carriage, triggering the RFID reader to detect the RFID tag signal in real time and automatically read tag data, including category, source department, weight, hazard level, generation time and predicted storage period, and updating the current state of the medical waste container in the medical waste management platform after successful reading.
Optionally, a multipoint distributed weight sensor is configured at the bottom of the bearing bin of the intelligent medical waste collecting vehicle, total weight and partition weight distribution in the bearing bin are collected in real time, when the medical waste container is loaded, the weight sensor detects weight change of the newly added medical waste container, actual weight data of the current medical waste container is generated, the weight of the medical waste container read by the RFID tag is compared with the actual weight collected by the weight sensor of the bearing bin, if the detected weight deviation exceeds a 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.
Optionally, the step S31 specifically includes:
The conflict detection unit senses the frequency occupation condition of the RFID tag communication signals in real time through an embedded spectrum analysis chip, and the spectrum analysis chip detects the time distribution of signal transmission by using a time domain distribution analysis algorithm and marks the RFID tag communication activities of signal overlapping in the same time slot;
And (3) time slot detection positioning, namely detecting signal overlapping conditions of a plurality of tags in a time domain when signal collision is detected, mainly calculating time slot distribution and overlapping degree of the signals, and positioning a specific time slot when the collision occurs by calculating the strength, frequency characteristic and time characteristic of the RFID tag signals.
Optionally, the time domain distribution analysis algorithm specifically includes:
calculating the power spill density: , wherein, Representing frequencyThe power spectral density at the bottom of the box,For a time-domain representation of the RFID tag signal,Is the duration of the signal sample,Is the frequency at which the frequency is to be determined,Representing signalsFor mapping the signal from the time domain to the frequency domain,Is a complex exponential kernel of the fourier transform,Representing the modular square of complex numbers for converting a time domain signal into a frequency domain signal representing frequencyMapping of sine wave of (2) on time domain, power spectral densityWhen the set power threshold is exceeded, indicating that the frequency is in an occupied state;
the frequency occupation state detection conditions are as follows: , wherein, Representing frequencyAn occupied state of 1 indicates occupied, 0 indicates idle,Representing a power threshold for spectrum occupancy, a power threshold for spectrum occupancyAnd setting according to the statistical characteristics of the background noise power.
Optionally, the set of time slots allocated by the RFID tag signal is defined as:
, wherein, Is a set of assigned time slots and,Is the total number of assigned time slots, in whichIn the process, Is the firstThe detection conditions of signal strength overlapping of the time windows of the time slots are as follows:
;
Wherein, Is a time slotA conflict state (1 for conflict, 0 for no conflict),Is an RFID tagIn time slotIs used to determine the instantaneous signal strength of the signal,Is in time slotThe number of RFID tags in communication with each other,Is the time slot signal strength collision threshold, and setting according to the signal-to-noise ratio of the system.
Conflicting tag location ifLocating conflicting tags by calculating the contribution signal strength of each tag:
, wherein, Representing the set of RFID tags that are in conflict,Is a conflict contribution ratio threshold for screening tags that have a greater impact on conflicts.
Optionally, the step S32 specifically includes:
S321, a quick negotiation mechanism is used for realizing time slot pre-allocation, namely after conflict detection, the quick negotiation mechanism is used for dynamically adjusting the time slot allocation of the RFID tags, and a specific communication time slot is allocated for each RFID tag, so that no overlapping among the time slots is ensured;
And S322, dynamically sequencing the label priorities, namely generating a multidimensional feature vector based on the signal strength of the RFID label, the distance between the RFID label and the reader and the hazard level of the combined waste, and dynamically sequencing the multidimensional feature vector of the conflict label by using a linear weighting model.
S323, priority-driven tag reading, namely, distributing communication time slots in time sequence according to the sequencing result, and preferentially distributing earlier communication time slots of the high-risk waste tags, so as to ensure timely reading of information of the high-risk waste tags.
Optionally, the multi-dimensional feature vector is expressed as: , wherein, Representation tagFor describing the priority thereof,Representation tagIs measured by an RFID reader; representing RFID tags The distance between the sensor and the reader is obtained through direct calculation of the signal propagation time,Representation tagThe hazard level of the waste;
The linear weighting model calculates a label Is of integrated priority of (2)And is based onSequencing:
, wherein, Is a labelThe greater the value, the higher the priority,Are all characteristic weight coefficients used for balancing the influence of each characteristic on the priority,The setting is made to be 0.5,The setting is made to be 0.3,The setting is made to be 0.2,Representing the inverse of the distance, representing the more preferred the closer the tag is to the reader;
The fast negotiation mechanism dynamically adjusts the time slot allocation of the RFID tag as follows:
, wherein, Representing RFID tagsIs allocated to the start time of the slot,Is the start time of the communication slot and,For the duration of each time slot,Is an RFID tagIs determined by the prioritization result.
The invention has the beneficial effects that:
According to the method, the conflict detection unit based on spectrum analysis is embedded in the RFID reader, the frequency occupation state of a communication signal and the conflict occurrence time slot are monitored in real time, and the conflict problem is effectively solved by combining the dynamically adjusted enhanced time slot allocation protocol.
According to the method, a rapid negotiation mechanism of a time slot allocation protocol is introduced for solving the conflict problem in RFID tag communication, the reading sequence of the high-risk waste tags is guaranteed by dynamically allocating communication time slots, the multi-dimensional feature vectors based on tag signal strength, distance and hazard level are generated, and the priority order is carried out, so that the dynamic optimized reading of the conflict tags is realized.
According to the invention, by binding a unique RFID tag for each medical waste container and verifying tag information by combining a weight sensor of the bearing bin, multi-dimensional data such as the category, the source department, the weight, the hazard level and the like of medical waste can be dynamically acquired, abnormal weight information is automatically updated and marked, and the real-time data uploading and storage of a medical waste management platform are based, so that the waste tracing and state monitoring are supported.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only of the invention and that other drawings can be obtained from them without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a method according to an embodiment of the invention;
Fig. 2 is a schematic diagram of tag prioritization according to an embodiment of the present invention.
Detailed Description
The invention will now be described in detail with reference to the drawings and to specific embodiments. While the invention has been described herein in detail in order to make the embodiments more detailed, the following embodiments are preferred and can be embodied in other forms as well known to those skilled in the art, and the accompanying drawings are only for the purpose of describing the embodiments more specifically and are not intended to limit the invention to the specific forms disclosed herein.
It should be noted that references in the specification to "one embodiment," "an example embodiment," "some embodiments," etc., indicate that the embodiment described may include a particular feature, structure, or characteristic, but every embodiment may not necessarily include the particular feature, structure, or characteristic. Further, when a particular feature, structure, or characteristic is described in connection with an embodiment, it is submitted that it is within the knowledge of one skilled in the relevant art to effect such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described.
Generally, the terminology may be understood, at least in part, from the use of context. For example, the term "one or more" as used herein may be used to describe any feature, structure, or characteristic in a singular sense, or may be used to describe a combination of features, structures, or characteristics in a plural sense, depending at least in part on the context. In addition, the term "based on" may be understood as not necessarily intended to convey an exclusive set of factors, but may instead, depending at least in part on the context, allow for other factors that are not necessarily explicitly described.
As shown in fig. 1-2, an intelligent medical waste collection vehicle information collection method based on the internet of things comprises the following steps:
s1, initializing medical waste container labels, namely binding a unique RFID label for each medical waste container;
S2, intelligent label information collection, namely configuring a high-sensitivity RFID reader for the intelligent medical waste collection vehicle, automatically reading an RFID label of a medical waste container when the medical waste container is loaded, configuring a weight sensor for a bearing bin of the intelligent medical waste collection vehicle, verifying the weight information recorded by the label through the weight sensor in the bearing bin when the RFID label information is read, and automatically updating the weight and marking the weight as abnormal if deviation is found;
s3, multi-tag reading optimization based on intelligent conflict detection and resolution:
s31, embedding a conflict detection unit based on spectrum analysis in an RFID reader of the intelligent medical waste collection vehicle, and monitoring the frequency occupation state of an RFID tag communication signal and conflict occurrence time slots in real time;
S32, aiming at the problem of time slots generated by conflict in RFID tag communication, introducing a time slot allocation protocol, pre-allocating time slots by the time slot allocation protocol through a quick negotiation mechanism, and reading RFID tag information according to tag priority ordering to ensure the information reading of high-risk waste tags;
The conflict identification and resolution data is uploaded to the medical waste management platform for optimization of subsequent tag placement policies and reader parameter configurations.
S1 specifically comprises:
S11, label generation and content input, namely inputting identification data comprising medical waste types, source departments, hazard grades, generation time and expected storage period through a medical waste management platform, and adding weight information into the identification data after weighing a waste container to form complete label data;
And S12, printing and attaching the label, namely printing the identification data by using an RFID printing device, printing the corresponding RFID label, and attaching the printed RFID label to the medical waste container.
S1, further comprising NFC equipment verification, namely reading RFID tag content through NFC equipment after the RFID tag is attached, performing verification comparison with identification data generated in a medical waste management platform, wherein the verification content comprises the integrity (whether all necessary information is contained) of the RFID tag, the accuracy (whether data are matched with waste attributes) and the uniqueness (whether tag IDs are repeated with other waste containers) of the RFID tag, if the verification is passed, marking the tag as valid and storing the tag in the medical waste management platform, if the verification is failed, automatically reminding regeneration or updating of the tag content, uploading the successfully bound RFID tag information to the medical waste management platform, establishing long-term association relation between the RFID tag and the medical waste container, and performing real-time tracking on the state of the waste container in the management platform, wherein the real-time tracking comprises storage period early warning and dynamic management of the container.
S2 specifically comprises:
S21, installing RFID readers at a loading port of the intelligent medical waste collection vehicle, wherein the RFID readers cover a loading area through multi-antenna array distribution, so that RFID tag signals can be rapidly captured when a waste container enters a bearing bin;
S22, when the medical waste container is loaded into the carriage, triggering the RFID reader to detect the RFID tag signal in real time and automatically read tag data, including category, source department, weight, hazard level, generation time and predicted storage period, and updating the current state of the medical waste container in the medical waste management platform after successful reading.
The method comprises the steps that a multipoint distributed weight sensor is arranged at the bottom of a bearing bin of an intelligent medical waste collection vehicle, total weight and partition weight distribution in the bearing bin are collected in real time, when a medical waste container is loaded, the weight sensor detects weight change of a newly added medical waste container, actual weight data of the current medical waste container are generated, the weight of the medical waste container read through an RFID tag is compared with the actual weight collected by the weight sensor of the bearing bin, if the detected weight deviation exceeds a set threshold value, 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;
And uploading the abnormal records to a medical waste management platform, and generating an abnormal processing notification for subsequent managers to review and process.
S31 specifically includes:
The conflict detection unit senses the frequency occupation condition of the RFID tag communication signals in real time through an embedded spectrum analysis chip, and the spectrum analysis chip detects the time distribution of signal transmission by using a time domain distribution analysis algorithm and marks the RFID tag communication activities of signal overlapping in the same time slot;
And (3) time slot detection positioning, namely detecting signal overlapping conditions of a plurality of tags in a time domain when signal collision is detected, mainly calculating time slot distribution and overlapping degree of the signals, and positioning a specific time slot when the collision occurs by calculating the strength, frequency characteristic and time characteristic of the RFID tag signals.
The time domain distribution analysis algorithm specifically comprises:
calculating the power spill density: , wherein, Representing frequencyThe power spectral density at the bottom of the box,For a time-domain representation of the RFID tag signal,Is the duration of the signal sample,Is the frequency at which the frequency is to be determined,Representing signalsFor mapping the signal from the time domain to the frequency domain,Is a complex exponential kernel of the fourier transform,Representing the modular square of complex numbers for converting a time domain signal into a frequency domain signal representing frequencyMapping of sine wave of (2) on time domain, power spectral densityWhen the set power threshold is exceeded, indicating that the frequency is in an occupied state;
the frequency occupation state detection conditions are as follows: , wherein, Representing frequencyAn occupied state of 1 indicates occupied, 0 indicates idle,Representing a power threshold for spectrum occupancy, a power threshold for spectrum occupancySetting according to the statistical characteristics of the background noise power:
, wherein, The average power of background noise is obtained through statistics of historical data of idle frequency segments,Adjusting factors and takingFor tolerating noise fluctuations over a range of frequencies, in short,The value of (2) is set to 1.5 to 3 times the background noise power for distinguishing the actual signal from the background noise.
The set of time slots allocated by the RFID tag signal is defined as:
, wherein, Is a set of assigned time slots and,Is the total number of assigned time slots, in whichIn the process, Is the firstThe detection conditions of signal strength overlapping of the time windows of the time slots are as follows:
;
Wherein, Is a time slotA conflict state (1 for conflict, 0 for no conflict),Is an RFID tagIn time slotIs used to determine the instantaneous signal strength of the signal,Is in time slotThe number of RFID tags in communication with each other,Is the time slot signal strength collision threshold, setting according to the signal-to-noise ratio of the system;
time slot signal strength collision threshold Based on the signal-to-noise ratio (SNR) of the system and the maximum supported signal strength accumulation setting: , wherein, The maximum intensity of a single tag signal, measured from the range of communication power of the tag with the reader,Label conflict accumulated male part Xu Bili, fetchIndicating that the total strength is exceededTo the point ofWhen a collision is considered to occur,Is the maximum value of the accumulation of tag signal strength that the system can tolerate for use in determining collisions.
Conflicting tag location ifLocating conflicting tags by calculating the contribution signal strength of each tag:
, wherein, Representing the set of RFID tags that are in conflict,Is a conflict contribution ratio threshold for screening tags that have a greater impact on conflicts.
Frequency occupancy state detection is the basis for slot collisions:
In one time slot ti, if multiple signals occupy the same frequency (or overlap of frequencies), frequency contention necessarily results in collisions.
Slot collisions are a manifestation of frequency occupancy in the time domain in that even if frequency occupancy collisions occur, if these signals are scheduled in different slots, no slot collisions will occur and therefore frequency occupancy does not necessarily cause slot collisions.
The comprehensive judgment comprises the step of judging the time slot conflict by combining the frequency occupation state and the signal strength in the time slot, wherein if the frequency occupation occurs, but the signal strength does not exceed Sthreshold, the time slot can still be considered as collision-free, and if the frequency occupation occurs and the signal strength is accumulated to exceed a threshold value, the time slot conflict is determined.
The relationship between the frequency occupancy state and the slot collision state is as follows:
The frequency occupation state is the basis, and determines whether the conflict is possible to occur;
the time slot conflict state is the specific expression of the frequency occupation state in the time domain, and the combination of the signal strength further confirms whether the conflict actually occurs.
S32 specifically includes:
S321, a quick negotiation mechanism is used for realizing time slot pre-allocation, namely after conflict detection, the quick negotiation mechanism is used for dynamically adjusting the time slot allocation of the RFID tags, and a specific communication time slot is allocated for each RFID tag, so that no overlapping among the time slots is ensured;
S322, dynamically sequencing tag priorities, namely generating a multidimensional feature vector based on the signal intensity of the RFID tag, the distance between the RFID tag and a reader and the hazard level of combined waste, and dynamically sequencing the multidimensional feature vector of the conflict tag by using a linear weighting model;
tag prioritization rules:
High-risk waste tags take precedence over normal waste tags;
Tags with high signal strength are preferred over tags with weak signals;
among the same category of tags, tags close to the reader are preferred.
S323, priority-driven tag reading, namely, distributing communication time slots in time sequence according to the sequencing result, and preferentially distributing earlier communication time slots of the high-risk waste tags, so as to ensure timely reading of information of the high-risk waste tags.
The multidimensional feature vector is expressed as: , wherein, Representation tagFor describing the priority thereof,Representation tagIs measured by an RFID reader; representing RFID tags The distance between the sensor and the reader is obtained through direct calculation of the signal propagation time,Representation tagThe hazard level of the waste;
linear weighting model calculation tag Is of integrated priority of (2)And is based onSequencing:
, wherein, Is a labelThe greater the value, the higher the priority,Are all characteristic weight coefficients used for balancing the influence of each characteristic on the priority,The setting is made to be 0.5,The setting is made to be 0.3,The setting is made to be 0.2,Representing the inverse of the distance, representing the more preferred the closer the tag is to the reader;
The fast negotiation mechanism dynamically adjusts the slot allocation of the RFID tag is expressed as:
, wherein, Representing RFID tagsIs allocated to the start time of the slot,Is the start time of the communication slot and,For the duration of each time slot,Is an RFID tagIs determined by the prioritization result.
The invention is intended to cover any alternatives, modifications, equivalents, and variations that fall within the spirit and scope of the invention. In the following description of preferred embodiments of the invention, specific details are set forth in order to provide a thorough understanding of the invention, and the invention will be fully understood to those skilled in the art without such details. In other instances, well-known methods, procedures, flows, components, circuits, and the like have not been described in detail so as not to unnecessarily obscure aspects of the present invention.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.
Claims (10)
1. The intelligent medical waste collection vehicle information acquisition method based on the Internet of things is characterized by comprising the following steps of:
s1, initializing medical waste container labels, namely binding a unique RFID label for each medical waste container;
S2, intelligently acquiring tag information, namely configuring an RFID reader by the intelligent medical waste collection vehicle, automatically reading an RFID tag of a medical waste container when the medical waste container is loaded, configuring a weight sensor in a bearing bin of the intelligent medical waste collection vehicle, verifying the weight information recorded by the tag through the weight sensor in the bearing bin when the RFID tag information is read, and automatically updating the weight and marking the weight as abnormal if deviation is found;
s3, multi-tag reading optimization based on intelligent conflict detection and resolution:
s31, embedding a conflict detection unit based on spectrum analysis in an RFID reader of the intelligent medical waste collection vehicle, and monitoring the frequency occupation state of an RFID tag communication signal and conflict occurrence time slots in real time;
s32, aiming at the problem of time slots generated by conflict in RFID tag communication, introducing a time slot allocation protocol, pre-allocating time slots by the time slot allocation protocol through a quick negotiation mechanism, and reading RFID tag information according to tag priority ordering, wherein the tag priority ordering is determined by using a linear weighting model, and dynamically ordering the RFID tag priorities in the reading conflict, so that important information is ensured to be read preferentially.
2. The intelligent medical waste collection vehicle information collection method based on the internet of things according to claim 1, wherein the S1 specifically comprises:
S11, label generation and content input, namely inputting identification data comprising medical waste types, source departments, hazard grades, generation time and expected storage period through a medical waste management platform, and adding weight information into the identification data after weighing a waste container to form complete label data;
And S12, printing and attaching the label, namely printing the identification data by using an RFID printing device, printing the corresponding RFID label, and attaching the printed RFID label to the medical waste container.
3. The intelligent medical waste collection vehicle information acquisition method based on the Internet of things is characterized in that S1 further comprises NFC equipment verification, after RFID tags are attached, RFID tag content is read through NFC equipment and is compared with identification data generated in a medical waste management platform, the verification content comprises the integrity, the accuracy and the uniqueness of the RFID tags, the successfully-bound RFID tag information is uploaded to the medical waste management platform, and long-term association relation between the RFID tags and medical waste containers is established.
4. The intelligent medical waste collection vehicle information collection method based on the internet of things according to claim 1, wherein the S2 specifically comprises:
s21, installing RFID readers at a loading port of the intelligent medical waste collection vehicle, wherein the RFID readers are distributed and cover a loading area through a multi-antenna array;
S22, when the medical waste container is loaded into the carriage, triggering the RFID reader to detect the RFID tag signal in real time and automatically read tag data, including category, source department, weight, hazard level, generation time and predicted storage period, and updating the current state of the medical waste container in the medical waste management platform after successful reading.
5. The internet of things-based intelligent medical waste collection vehicle information collection method according to claim 4, wherein a multipoint distributed weight sensor is configured at the bottom of a carrying bin of the intelligent medical waste collection vehicle, total weight and partition weight distribution in the carrying bin are collected in real time, when a medical waste container is loaded, the weight sensor detects weight change of a newly added medical waste container, actual weight data of the current medical waste container is generated, the weight of the medical waste container read by an RFID (radio frequency identification) tag is compared with the actual weight collected by the carrying bin weight sensor, if the detected weight deviation exceeds a 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 intelligent medical waste collection vehicle information collection method based on the internet of things according to claim 1, wherein the S31 specifically comprises:
The conflict detection unit senses the frequency occupation condition of the RFID tag communication signals in real time through an embedded spectrum analysis chip, and the spectrum analysis chip detects the time distribution of signal transmission by using a time domain distribution analysis algorithm and marks the RFID tag communication activities of signal overlapping in the same time slot;
and (3) time slot detection positioning, namely when the signal conflict is detected, positioning the specific time slot where the conflict occurs by calculating the strength, the frequency characteristic and the time characteristic of the RFID tag signal.
7. The intelligent medical waste collection vehicle information collection method based on the internet of things of claim 6, wherein the time domain distribution analysis algorithm specifically comprises:
calculating the power spill density: , wherein, Representing frequencyThe power spectral density at the bottom of the box,For a time-domain representation of the RFID tag signal,Is the duration of the signal sample,Is the frequency at which the frequency is to be determined,Representing signalsIs used for the Fourier transform result of the (a),Is a complex exponential kernel of the fourier transform,Representing the modular square of the complex number, power spectral densityWhen the set power threshold is exceeded, indicating that the frequency is in an occupied state;
the frequency occupation state detection conditions are as follows: , wherein, Representing frequencyAn occupied state of 1 indicates occupied, 0 indicates idle,Representing the power threshold of the spectrum occupation.
8. The intelligent medical waste collection vehicle information collection method based on the internet of things according to claim 7, wherein the time slot set allocated by the RFID tag signal is defined as:
, wherein, Is a set of assigned time slots and,Is the total number of assigned time slots, in whichIn the process, Is the firstThe detection conditions of signal strength overlapping of the time windows of the time slots are as follows:
;
Wherein, Is a time slotIs used to determine the conflict state of (1),Is an RFID tagIn time slotIs used to determine the instantaneous signal strength of the signal,Is in time slotThe number of RFID tags in communication with each other,Is a time slot signal strength collision threshold;
Conflicting tag location if Locating conflicting tags by calculating the contribution signal strength of each tag:
, wherein, Representing the set of RFID tags that are in conflict,Is the conflict contribution ratio threshold.
9. The method for collecting information of the intelligent medical waste collection vehicle based on the internet of things according to claim 8, wherein the step S32 specifically includes:
S321, a quick negotiation mechanism is used for realizing time slot pre-allocation, namely after conflict detection, the quick negotiation mechanism is used for dynamically adjusting the time slot allocation of the RFID tags, and a specific communication time slot is allocated for each RFID tag, so that no overlapping among the time slots is ensured;
S322, dynamically sequencing tag priorities, namely generating a multidimensional feature vector based on the signal intensity of the RFID tag, the distance between the RFID tag and a reader and the hazard level of combined waste, and dynamically sequencing the multidimensional feature vector of the conflict tag by using a linear weighting model;
And S323, reading the tags driven by the priority, namely distributing the time sequence of the communication time slots according to the sequencing result.
10. The intelligent medical waste collection vehicle information collection method based on the internet of things according to claim 9, wherein the multidimensional feature vector is expressed as: , wherein, Representation tagIs used to determine the multi-dimensional feature vector of (a),Representation tagIs a signal strength of (2); representing RFID tags The distance from the reader is set to be equal to the distance between the reader and the sensor,Representation tagThe hazard level of the waste;
The linear weighting model calculates a label Is of integrated priority of (2)And is based onSequencing:
, wherein, Is a labelThe greater the value, the higher the priority,Are all characteristic weight coefficients used for balancing the influence of each characteristic on the priority,Representing the inverse of the distance, representing the more preferred the closer the tag is to the reader;
The fast negotiation mechanism dynamically adjusts the time slot allocation of the RFID tag as follows:
, wherein, Representing RFID tagsIs allocated to the start time of the slot,Is the start time of the communication slot and,For the duration of each time slot,Is an RFID tagIs determined by the prioritization result.
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| CN102663330A (en) * | 2012-03-29 | 2012-09-12 | 无锡中科沃谱瑞科技有限责任公司 | Method for radio frequency tag inventory, radio frequency tag card reader and radio frequency tag |
| CN111710400A (en) * | 2020-06-15 | 2020-09-25 | 南京贝克勒尔智能科技有限公司 | Management method for preventing medical waste leakage |
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| EP1256083B1 (en) * | 1999-12-03 | 2005-10-26 | Tagsys SA | Electronic label reading system |
| GB201006907D0 (en) * | 2010-04-26 | 2010-06-09 | Cambridge Entpr Ltd | RFID TAG interrogation systems |
| US20130222118A1 (en) * | 2012-02-28 | 2013-08-29 | Umm Al-Qura University | Method of predicting tag detection probability for rfid framed slotted aloha anti-collision protocols |
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| CN102663330A (en) * | 2012-03-29 | 2012-09-12 | 无锡中科沃谱瑞科技有限责任公司 | Method for radio frequency tag inventory, radio frequency tag card reader and radio frequency tag |
| CN111710400A (en) * | 2020-06-15 | 2020-09-25 | 南京贝克勒尔智能科技有限公司 | Management method for preventing medical waste leakage |
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