CN112985494A - Cold chain wisdom logistics transportation on-line real-time supervision cloud platform based on big data and artificial intelligence - Google Patents
Cold chain wisdom logistics transportation on-line real-time supervision cloud platform based on big data and artificial intelligence Download PDFInfo
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- CN112985494A CN112985494A CN202110145021.2A CN202110145021A CN112985494A CN 112985494 A CN112985494 A CN 112985494A CN 202110145021 A CN202110145021 A CN 202110145021A CN 112985494 A CN112985494 A CN 112985494A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60H—ARRANGEMENTS OF HEATING, COOLING, VENTILATING OR OTHER AIR-TREATING DEVICES SPECIALLY ADAPTED FOR PASSENGER OR GOODS SPACES OF VEHICLES
- B60H1/00—Heating, cooling or ventilating [HVAC] devices
- B60H1/32—Cooling devices
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60P—VEHICLES ADAPTED FOR LOAD TRANSPORTATION OR TO TRANSPORT, TO CARRY, OR TO COMPRISE SPECIAL LOADS OR OBJECTS
- B60P3/00—Vehicles adapted to transport, to carry or to comprise special loads or objects
- B60P3/20—Refrigerated goods vehicles
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60H—ARRANGEMENTS OF HEATING, COOLING, VENTILATING OR OTHER AIR-TREATING DEVICES SPECIALLY ADAPTED FOR PASSENGER OR GOODS SPACES OF VEHICLES
- B60H1/00—Heating, cooling or ventilating [HVAC] devices
- B60H1/32—Cooling devices
- B60H2001/3236—Cooling devices information from a variable is obtained
- B60H2001/3255—Cooling devices information from a variable is obtained related to temperature
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60H—ARRANGEMENTS OF HEATING, COOLING, VENTILATING OR OTHER AIR-TREATING DEVICES SPECIALLY ADAPTED FOR PASSENGER OR GOODS SPACES OF VEHICLES
- B60H1/00—Heating, cooling or ventilating [HVAC] devices
- B60H1/32—Cooling devices
- B60H2001/3269—Cooling devices output of a control signal
Abstract
The invention relates to a cold-chain intelligent logistics transportation online real-time monitoring cloud platform based on big data and artificial intelligence, which comprises an image detection module, an image preprocessing module, a frozen article temperature detection module, a frozen article humidity detection module, a frozen article vibration detection module, a frozen article volume detection module, a frozen article odor detection module, a data preprocessing module, a database, a modeling analysis server, a management server and a display terminal, wherein the frozen article deterioration evaluation coefficient can be analyzed by acquiring the temperature, the humidity and the vibration frequency of frozen articles in the transportation process and the odor property, the volume and the liquid area at the transportation end point and combining the modeling analysis server, so that the deterioration condition of each frozen article in the transportation process can be visually displayed, the quality detection efficiency and the accuracy of the frozen articles are improved, and the deterioration speed of the frozen articles is further reduced, and powerful technical support is provided for monitoring cold-chain logistics transportation.
Description
Technical Field
The invention belongs to the technical field of cold-chain logistics monitoring, and particularly relates to a cold-chain intelligent logistics transportation online real-time monitoring cloud platform based on big data and artificial intelligence.
Background
The cold chain logistics generally refers to a system project that refrigerated and frozen goods are always in a specified low-temperature environment in all links from production, storage, transportation and sale to the moment of consumption to ensure the quality of the goods and reduce the loss of the goods, is established along with the progress of scientific technology and the development of refrigeration technology, and is a low-temperature logistics process taking refrigeration technology as a means on the basis of refrigeration technology.
The cold chain logistics car is the essential instrument of article in the transportation, and current cold chain logistics car shock attenuation effect is not good when using, often road surface jolt makes the carriage rock, so that article rock in the carriage, article damage easily like this, and cold chain logistics car is at the in-process of transportation, inside temperature probably rises along with the time, humidity also can reduce, article probably deteriorate when the transportation, observe the humiture of hygrothermograph at a certain time point usually by the transport personnel, can not monitor temperature and humidity in the car constantly, can not in time effectually take the measure of control humiture, and only judge the state of frozen food through the change of humiture, the error is great.
Disclosure of Invention
Aiming at the problems, the invention provides a cold-chain intelligent logistics transportation online real-time monitoring cloud platform based on big data and artificial intelligence, and the cloud platform is used for detecting all parameters of frozen goods in real time by combining a frozen goods temperature detection module, a frozen goods humidity detection module, a frozen goods vibration detection module, a frozen goods volume detection module and a frozen goods odor detection module with a modeling analysis server so as to analyze the deterioration evaluation coefficient of the frozen goods, thereby solving the problems in the prior art.
The purpose of the invention can be realized by the following technical scheme:
the cold-chain intelligent logistics transportation online real-time monitoring cloud platform based on big data and artificial intelligence comprises an image detection module, an image preprocessing module, a frozen article temperature detection module, a frozen article humidity detection module, a frozen article vibration detection module, a frozen article volume detection module, a frozen article odor detection module, a data preprocessing module, a database, a modeling analysis server, a management server and a display terminal;
the data preprocessing module is respectively connected with the frozen article temperature detection module, the frozen article humidity detection module, the frozen article vibration detection module and the modeling analysis server, the image preprocessing module is respectively connected with the image acquisition module and the modeling analysis server, the modeling analysis server is respectively connected with the frozen article volume detection module, the frozen article odor detection module, the database and the management server, and the management server is respectively connected with the database and the display terminal;
the image detection module comprises a high-definition camera and is used for collecting image information of each frozen article at a transportation starting point and a transportation end point and respectively sending the collected image information of each frozen article at the transportation starting point and the transportation end point to the image preprocessing module;
the image preprocessing module receives the image information of each frozen article at the transportation starting point and the transportation ending point sent by the image detection module, image segmentation is carried out on the received image information of each frozen article at the transportation starting point and the transportation end point, the characteristic regions of the frozen articles obtained by image segmentation are spliced, removing background images outside the characteristic region of the frozen article, changing the retained characteristic region images of the frozen article into frozen article images with consistent size and no deflection angle through geometric normalization processing, simultaneously carrying out gray level conversion and image enhancement processing to obtain target images of the processed frozen articles at the transportation starting point and the transportation end point, the image preprocessing module respectively sends the processed target images of the frozen articles at the transportation starting point and the transportation end point to a modeling analysis server;
the frozen article temperature detection module comprises a temperature sensor and a data preprocessing module, wherein the temperature sensor is used for detecting the temperature of each frozen article in the transportation process in real time and sending the detected temperature of each frozen article in the transportation process to the data preprocessing module;
the frozen article humidity detection module comprises a humidity sensor and a data preprocessing module, wherein the humidity sensor is used for detecting the humidity of each frozen article in the transportation process in real time and sending the detected humidity of each frozen article in the transportation process to the data preprocessing module;
the frozen article vibration detection module comprises a vibration sensor and a data preprocessing module, wherein the vibration sensor is used for detecting the vibration frequency of each frozen article in the transportation process in real time and sending the detected vibration frequency of each frozen article in the transportation process to the data preprocessing module;
the data preprocessing module is used for receiving the temperature of the frozen articles in the transportation process sent by each frozen article temperature detection module, receiving the humidity of each frozen article in the transportation process sent by each frozen article humidity detection module, receiving the vibration frequency of each frozen article in the transportation process sent by each frozen article vibration detection module, dividing the temperature, the humidity and the vibration frequency of each received frozen article in the transportation process of each frozen article according to detection time periods, dividing a plurality of detection time periods according to preset fixed time intervals, and sequentially marking the detection time periods as 1,2, as, t, as, v according to a preset sequence to form a detection time period parameter set Qiw(qiw1,qiw2,...,qiwt,...,qiwv)，qiwt is the w-th frozen article parameter in the t-th detection time period of the ith frozen article in the transportation process, w is the frozen article parameter, w is p1, p2, p3, p1, p2 and p2 respectively represent the temperature, humidity and vibration frequency of the ith frozen article in the transportation process, and the data preprocessing module sends the detection time period parameter set to the modeling and analyzing server;
the frozen article volume detection module comprises a three-dimensional scanner and a modeling analysis server, wherein the three-dimensional scanner is used for acquiring the volume of each frozen article at a transportation starting point and a transportation end point and respectively sending the detected volume of each frozen article at the transportation starting point and the transportation end point to the modeling analysis server;
the odor detection module of the frozen goods comprises an odor detector, a modeling analysis server and a storage module, wherein the odor detector is used for detecting the concentration value of the gas emitted by each frozen goods at the transportation end point and sending the detected concentration value of the gas emitted by each frozen goods at the transportation end point to the modeling analysis server;
the database is used for storing gas concentration influence coefficients corresponding to different gas concentration levels, storing standard frozen article parameters of the frozen articles in the transportation process, storing gas concentration ranges corresponding to different gas concentration levels, and storing frozen article deterioration evaluation coefficient ranges corresponding to different frozen article deterioration evaluation levels.
The modeling analysis server receives the detection time period parameter set sent by the data preprocessing module, extracts the frozen article parameters corresponding to each frozen article in the detection time period parameter set in each detection time period, extracts the standard frozen article parameters of the frozen articles stored in the database in the transportation process, compares each frozen article parameter corresponding to each detection time period with the standard frozen article parameter of the frozen articles in the transportation process to form a detection time period frozen article parameter comparison set delta Qiw(Δqiw1,Δqiw2,...,Δqiwt,...,Δqiwv)，Δqiwt is the difference between the w-th frozen product parameter of the ith frozen product in the t detection time period in the transportation process and the w-th standard frozen product parameter of the ith frozen product in the transportation process, the frozen product parameter contrast value of each frozen product in each detection time period is compared with the frozen product parameter contrast value of each frozen product in the last detection time period to obtain the frozen product relative parameter contrast value of each frozen product in each detection time period, and the frozen product relative parameter contrast values of each frozen product in each detection time period form a time period frozen product relative parameter contrast set Q'iw(q′iw1,q′iw2,...,q′iwt,...,q′iwv)，q′wt is expressed as the difference between the w-th frozen article parameter in the t-th detection time period and the w-th frozen article parameter in the t-1 detection time period during the transportation of the ith frozen article;
the modeling analysis server receives target images of all frozen articles at a transportation starting point and a transportation end point, which are sent by the image preprocessing module, compares the target images of all the frozen articles at the transportation end point with the target images at the transportation starting point to obtain liquid areas on all the frozen articles, and forms a frozen article liquid area set A (a1, a 2.., ai.,..., ag), wherein ai represents the liquid areas of the ith frozen article at the transportation end point;
the modeling analysis server receives the gas concentration value sent by the frozen article odor detection module at the transportation end point of each frozen article, compares the received gas concentration value sent by each frozen article at the transportation end point with the gas concentration ranges corresponding to different gas concentration levels stored in the database, and extracts the gas concentration level corresponding to the gas concentration of each frozen article;
the modeling analysis server receives the volumes of the frozen goods at the transportation starting point and the transportation end point, which are sent by the frozen goods volume detection module, compares the volume of each frozen goods at the transportation end point with the volume at the transportation starting point to form a frozen goods volume comparison set B (B1, B2.., bi.., bg), wherein bi is represented as the volume comparison value of the ith frozen goods at the transportation end point;
the modeling analysis server extracts gas concentration influence coefficients corresponding to different gas concentration levels stored in the database, and according to the time period frozen article relative parameter comparison set, the frozen article liquid area set, the frozen article volume comparison set and the gas concentration influence coefficients corresponding to the gas concentration levels of all the frozen articles at the transportation end point, the frozen article deterioration evaluation coefficients are counted, and the modeling analysis server sends the counted frozen article deterioration evaluation coefficients to the management server;
the management server receives the frozen article deterioration evaluation coefficient sent by the modeling analysis server, compares the frozen article deterioration evaluation coefficient with frozen article deterioration evaluation coefficient ranges corresponding to different frozen article deterioration evaluation grades stored in the database, if the frozen article deterioration evaluation coefficient is within the frozen article deterioration evaluation coefficient range corresponding to the first-level frozen article deterioration evaluation grade, the frozen article deterioration evaluation grade is first-level, if the frozen article deterioration evaluation coefficient is within the frozen article deterioration evaluation coefficient range corresponding to the second-level frozen article deterioration evaluation grade, the frozen article deterioration evaluation grade is second-level, if the frozen article deterioration evaluation coefficient is within the frozen article deterioration evaluation coefficient range corresponding to the third-level frozen article deterioration evaluation grade, the frozen article deterioration evaluation grade is third-level, the management server sends the frozen article deterioration evaluation coefficient and the corresponding frozen article deterioration evaluation grade to the display terminal;
and the display terminal receives and displays the frozen article deterioration evaluation coefficient and the corresponding frozen article deterioration evaluation grade sent by the management server.
Further, an upper limit value of a gas concentration range corresponding to the primary gas concentration level is smaller than a lower limit value of a gas concentration range corresponding to the secondary gas concentration level, and an upper limit value of the gas concentration range corresponding to the secondary gas concentration level is smaller than a lower limit value of a gas concentration range corresponding to the tertiary gas concentration level.
Further, the gas concentration influence coefficients corresponding to the different gas concentration levels have the magnitude order
Furthermore, the upper limit value of the frozen article deterioration evaluation coefficient range corresponding to the first-level frozen article deterioration evaluation level is smaller than the lower limit value of the frozen article deterioration evaluation coefficient range corresponding to the second-level frozen article deterioration evaluation level, and the upper limit value of the frozen article deterioration evaluation coefficient range corresponding to the second-level frozen article deterioration evaluation level is smaller than the lower limit value of the frozen article deterioration evaluation coefficient range corresponding to the third-level frozen article deterioration evaluation level.
Further, the standard frozen item parameters include standard temperature, humidity, and vibration frequency.
Further, the calculation formula of the deterioration evaluation coefficient of the frozen goods is
Is expressed as the gas concentration influence coefficient corresponding to the ith frozen product at the E-th gas concentration level, E is 1,2,3, q'wt is expressed as the w frozen article parameter and t-1 detection in the t detection time period of the ith frozen article in the transportation processDifference between the w-th frozen goods parameter over the time period, qiwt is expressed as the w-th frozen article parameter of the ith frozen article in the t-th detection time period in the transportation process, ai is expressed as the liquid area of the ith frozen article at the transportation end point, bi is expressed as the volume contrast value of the ith frozen article at the transportation end point, and e is expressed as a natural number.
Has the advantages that:
(1) according to the invention, through the frozen article temperature detection module, the frozen article humidity detection module, the frozen article vibration detection module, the frozen article volume detection module and the frozen article odor detection module and combining with the modeling analysis server, all parameters of the frozen articles are detected in real time to analyze the deterioration evaluation coefficient of the frozen articles, and the deterioration condition of all the frozen articles in the transportation process can be visually displayed through the deterioration evaluation coefficient of the frozen articles, so that the quality detection efficiency and accuracy of the frozen articles are improved, the deterioration speed of the frozen articles is further reduced, the storage cost is reduced, and a powerful technical support is provided for cold-chain logistics transportation monitoring.
(2) The method and the device provide reliable early-stage data preparation and reference basis for later statistics of the deterioration evaluation coefficient of the frozen article by acquiring the temperature, the humidity and the vibration frequency of the frozen article in the transportation process and the odor property, the volume and the liquid area at the transportation end point, and have the characteristics of high authenticity and high data accuracy and accuracy.
(3) According to the invention, the deterioration evaluation coefficients of all frozen articles are displayed at the display terminal, so that real-time detection data of the frozen articles are provided for logistics personnel, the logistics personnel can conveniently take different measures to manage the frozen articles according to the real-time detection data of the frozen articles, and the quality of the frozen articles in the transportation process is greatly guaranteed.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
FIG. 1 is a flow chart of the system of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the cold-chain intelligent logistics transportation online real-time monitoring cloud platform based on big data and artificial intelligence comprises an image detection module, an image preprocessing module, a frozen article temperature detection module, a frozen article humidity detection module, a frozen article vibration detection module, a frozen article volume detection module, a frozen article odor detection module, a data preprocessing module, a database, a modeling analysis server, a management server and a display terminal;
the data preprocessing module is respectively connected with the frozen article temperature detection module, the frozen article humidity detection module, the frozen article vibration detection module and the modeling analysis server, the image preprocessing module is respectively connected with the image acquisition module and the modeling analysis server, the modeling analysis server is respectively connected with the frozen article volume detection module, the frozen article odor detection module, the database and the management server, and the management server is respectively connected with the database and the display terminal;
the image detection module comprises a high-definition camera and is used for collecting image information of each frozen article at a transportation starting point and a transportation end point and respectively sending the collected image information of each frozen article at the transportation starting point and the transportation end point to the image preprocessing module;
the image preprocessing module receives the image information of each frozen article at the transportation starting point and the transportation ending point sent by the image detection module, image segmentation is carried out on the received image information of each frozen article at the transportation starting point and the transportation end point, the characteristic regions of the frozen articles obtained by image segmentation are spliced, removing background images outside the characteristic region of the frozen article, changing the retained characteristic region images of the frozen article into frozen article images with consistent size and no deflection angle through geometric normalization processing, simultaneously carrying out gray level conversion and image enhancement processing to obtain target images of the processed frozen articles at the transportation starting point and the transportation end point, the image preprocessing module respectively sends the processed target images of the frozen articles at the transportation starting point and the transportation end point to a modeling analysis server;
the frozen article temperature detection module comprises a temperature sensor and a data preprocessing module, wherein the temperature sensor is used for detecting the temperature of each frozen article in the transportation process in real time and sending the detected temperature of each frozen article in the transportation process to the data preprocessing module;
the frozen article humidity detection module comprises a humidity sensor and a data preprocessing module, wherein the humidity sensor is used for detecting the humidity of each frozen article in the transportation process in real time and sending the detected humidity of each frozen article in the transportation process to the data preprocessing module;
the frozen article vibration detection module comprises a vibration sensor and a data preprocessing module, wherein the vibration sensor is used for detecting the vibration frequency of each frozen article in the transportation process in real time and sending the detected vibration frequency of each frozen article in the transportation process to the data preprocessing module;
according to the embodiment, the temperature, the humidity and the vibration frequency of the frozen article in the transportation process and the odor property, the volume and the liquid area at the transportation end point are obtained, so that reliable early-stage data preparation and reference basis are provided for later-stage statistics of the frozen article deterioration evaluation coefficient, and the method has the characteristics of high authenticity and high data accuracy and accuracy;
the data preprocessing module is used for receiving the temperature of the frozen articles in the transportation process sent by each frozen article temperature detection module, receiving the humidity of the frozen articles in the transportation process sent by each frozen article humidity detection module, receiving the vibration frequency of the frozen articles in the transportation process sent by each frozen article vibration detection module and receiving the vibration frequency of the frozen articles in the transportation process sent by each frozen article vibration detection moduleThe temperature, the humidity and the vibration frequency of each frozen article in the transportation process are divided according to detection time periods, a plurality of detection time periods are divided according to preset fixed time intervals, and the detection time period parameter set Q is formed by sequentially marking the detection time periods as 1,2, t, v according to a preset sequenceiw(qiw1,qiw2,...,qiwt,...,qiwv)，qiwt is the w-th frozen article parameter in the t-th detection time period of the ith frozen article in the transportation process, w is the frozen article parameter, w is p1, p2, p3, p1, p2 and p2 respectively represent the temperature, humidity and vibration frequency of the ith frozen article in the transportation process, and the data preprocessing module sends the detection time period parameter set to the modeling and analyzing server;
the frozen article volume detection module comprises a three-dimensional scanner and a modeling analysis server, wherein the three-dimensional scanner is used for acquiring the volume of each frozen article at a transportation starting point and a transportation end point and respectively sending the detected volume of each frozen article at the transportation starting point and the transportation end point to the modeling analysis server;
the odor detection module of the frozen goods comprises an odor detector, a modeling analysis server and a storage module, wherein the odor detector is used for detecting the concentration value of the gas emitted by each frozen goods at the transportation end point and sending the detected concentration value of the gas emitted by each frozen goods at the transportation end point to the modeling analysis server;
the database is used for storing gas concentration influence coefficients corresponding to different gas concentration levels, and the magnitude sequence of the gas concentration influence coefficients corresponding to the different gas concentration levels is
Storing standard frozen article parameters of the frozen article in the transportation process, wherein the standard frozen article parameters comprise standard temperature, humidity and vibration frequency, storing gas concentration ranges corresponding to different gas concentration levels, the upper limit value of the gas concentration range corresponding to the first-level odor concentration level is smaller than the lower limit value of the gas concentration range corresponding to the second-level odor concentration level, and the gas concentration range corresponding to the second-level odor concentration levelThe upper limit value of the frozen article deterioration evaluation coefficient range corresponding to the first-level frozen article deterioration evaluation level is smaller than the lower limit value of the frozen article deterioration evaluation coefficient range corresponding to the second-level frozen article deterioration evaluation level, and the upper limit value of the frozen article deterioration evaluation coefficient range corresponding to the second-level frozen article deterioration evaluation level is smaller than the lower limit value of the frozen article deterioration evaluation coefficient range corresponding to the third-level frozen article deterioration evaluation level.
The modeling analysis server receives the detection time period parameter set sent by the data preprocessing module, extracts the frozen article parameters corresponding to each frozen article in the detection time period parameter set in each detection time period, extracts the standard frozen article parameters of the frozen articles stored in the database in the transportation process, compares each frozen article parameter corresponding to each detection time period with the standard frozen article parameter of the frozen articles in the transportation process to form a detection time period frozen article parameter comparison set delta Qiw(Δqiw1,Δqiw2,...,Δqiwt,...,Δqiwv)，Δqiwt is the difference between the w-th frozen product parameter of the ith frozen product in the t detection time period in the transportation process and the w-th standard frozen product parameter of the ith frozen product in the transportation process, the frozen product parameter contrast value of each frozen product in each detection time period is compared with the frozen product parameter contrast value of each frozen product in the last detection time period to obtain the frozen product relative parameter contrast value of each frozen product in each detection time period, and the frozen product relative parameter contrast values of each frozen product in each detection time period form a time period frozen product relative parameter contrast set Q'iw(q′iw1,q′iw2,...,q′iwt,...,q′iwv)，q′wt is expressed as the w-th frozen article parameter in the t-th detection time period and the w-th frozen article in the t-1 detection time periods in the transportation process of the ith frozen articleDifferences between product parameters;
the modeling analysis server receives target images of all frozen articles at a transportation starting point and a transportation end point, which are sent by the image preprocessing module, compares the target images of all the frozen articles at the transportation end point with the target images at the transportation starting point to obtain liquid areas on all the frozen articles, and forms a frozen article liquid area set A (a1, a 2.., ai.,..., ag), wherein ai represents the liquid areas of the ith frozen article at the transportation end point;
the modeling analysis server receives the gas concentration value sent by the frozen article odor detection module at the transportation end point of each frozen article, compares the received gas concentration value sent by each frozen article at the transportation end point with the gas concentration ranges corresponding to different gas concentration levels stored in the database, and extracts the gas concentration level corresponding to the gas concentration of each frozen article;
the modeling analysis server receives the volumes of the frozen goods at the transportation starting point and the transportation end point, which are sent by the frozen goods volume detection module, compares the volume of each frozen goods at the transportation end point with the volume at the transportation starting point to form a frozen goods volume comparison set B (B1, B2.., bi.., bg), wherein bi is represented as the volume comparison value of the ith frozen goods at the transportation end point;
the modeling analysis server extracts gas concentration influence coefficients corresponding to different gas concentration levels stored in the database, and according to the time period relative parameter comparison set of the frozen goods, the liquid area set of the frozen goods, the volume comparison set of the frozen goods and the gas concentration influence coefficients corresponding to the gas concentration levels of all the frozen goods at the transportation end point, the deterioration evaluation coefficients of the frozen goods are counted, and the calculation formula of the deterioration evaluation coefficients of the frozen goods is
Is expressed as the gas concentration influence coefficient corresponding to the ith frozen product at the E-th gas concentration level, E is 1,2,3, q'wt is expressed as the ith frozen article during the t detection period in the transportation processDifference between w frozen goods parameters and the w-th frozen goods parameter in t-1 detection periods, qiwt represents the w-th frozen article parameter in the t-th detection time period of the ith frozen article in the transportation process, ai represents the liquid area of the ith frozen article at the transportation end point, bi represents the volume contrast value of the ith frozen article at the transportation end point, e represents a natural number, and the modeling analysis server sends the statistical frozen article deterioration evaluation coefficient to the management server;
the management server receives the frozen article deterioration evaluation coefficient sent by the modeling analysis server, compares the frozen article deterioration evaluation coefficient with frozen article deterioration evaluation coefficient ranges corresponding to different frozen article deterioration evaluation grades stored in the database, if the frozen article deterioration evaluation coefficient is within the frozen article deterioration evaluation coefficient range corresponding to the first-level frozen article deterioration evaluation grade, the frozen article deterioration evaluation grade is first-level, if the frozen article deterioration evaluation coefficient is within the frozen article deterioration evaluation coefficient range corresponding to the second-level frozen article deterioration evaluation grade, the frozen article deterioration evaluation grade is second-level, if the frozen article deterioration evaluation coefficient is within the frozen article deterioration evaluation coefficient range corresponding to the third-level frozen article deterioration evaluation grade, the frozen article deterioration evaluation grade is third-level, the management server sends the frozen article deterioration evaluation coefficient and the corresponding frozen article deterioration evaluation grade to the display terminal;
the display terminal receives the frozen article deterioration evaluation coefficient sent by the management server and the corresponding frozen article deterioration evaluation grade, displays the deterioration evaluation coefficient of each frozen article, provides real-time detection data of the frozen articles for logistics personnel, facilitates the logistics personnel to take different measures to manage the frozen articles according to the real-time detection data of the frozen articles, and greatly ensures the quality of the frozen articles in the transportation process.
According to the invention, through the frozen article temperature detection module, the frozen article humidity detection module, the frozen article vibration detection module, the frozen article volume detection module and the frozen article odor detection module and combining with the modeling analysis server, all parameters of the frozen articles are detected in real time to analyze the deterioration evaluation coefficient of the frozen articles, and the deterioration condition of all the frozen articles in the transportation process can be visually displayed through the deterioration evaluation coefficient of the frozen articles, so that the quality detection efficiency and accuracy of the frozen articles are improved, the deterioration speed of the frozen articles is further reduced, the storage cost is reduced, and a powerful technical support is provided for cold-chain logistics transportation monitoring.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (6)
1. Cold chain wisdom logistics transportation on-line real-time supervision cloud platform based on big data and artificial intelligence, its characterized in that: the system comprises an image detection module, an image preprocessing module, a frozen article temperature detection module, a frozen article humidity detection module, a frozen article vibration detection module, a frozen article volume detection module, a frozen article odor detection module, a data preprocessing module, a database, a modeling analysis server, a management server and a display terminal;
the data preprocessing module is respectively connected with the frozen article temperature detection module, the frozen article humidity detection module, the frozen article vibration detection module and the modeling analysis server, the image preprocessing module is respectively connected with the image acquisition module and the modeling analysis server, the modeling analysis server is respectively connected with the frozen article volume detection module, the frozen article odor detection module, the database and the management server, and the management server is respectively connected with the database and the display terminal;
the image detection module comprises a high-definition camera and is used for collecting image information of each frozen article at a transportation starting point and a transportation end point and respectively sending the collected image information of each frozen article at the transportation starting point and the transportation end point to the image preprocessing module;
the image preprocessing module receives the image information of each frozen article at the transportation starting point and the transportation ending point sent by the image detection module, image segmentation is carried out on the received image information of each frozen article at the transportation starting point and the transportation end point, the characteristic regions of the frozen articles obtained by image segmentation are spliced, removing background images outside the characteristic region of the frozen article, changing the retained characteristic region images of the frozen article into frozen article images with consistent size and no deflection angle through geometric normalization processing, simultaneously carrying out gray level conversion and image enhancement processing to obtain target images of the processed frozen articles at the transportation starting point and the transportation end point, the image preprocessing module respectively sends the processed target images of the frozen articles at the transportation starting point and the transportation end point to a modeling analysis server;
the frozen article temperature detection module comprises a temperature sensor and a data preprocessing module, wherein the temperature sensor is used for detecting the temperature of each frozen article in the transportation process in real time and sending the detected temperature of each frozen article in the transportation process to the data preprocessing module;
the frozen article humidity detection module comprises a humidity sensor and a data preprocessing module, wherein the humidity sensor is used for detecting the humidity of each frozen article in the transportation process in real time and sending the detected humidity of each frozen article in the transportation process to the data preprocessing module;
the frozen article vibration detection module comprises a vibration sensor and a data preprocessing module, wherein the vibration sensor is used for detecting the vibration frequency of each frozen article in the transportation process in real time and sending the detected vibration frequency of each frozen article in the transportation process to the data preprocessing module;
the data preprocessing module is used for receiving the temperature of the frozen articles in the transportation process sent by each frozen article temperature detection module, receiving the humidity of the frozen articles in the transportation process sent by each frozen article humidity detection module, receiving the vibration frequency of the frozen articles in the transportation process sent by each frozen article vibration detection module, and transmitting the vibration frequency of the frozen articles in the transportation process to each received frozen articleDividing the temperature, the humidity and the vibration frequency in the process according to detection time periods, dividing a plurality of detection time periods according to preset fixed time intervals, sequentially marking the detection time periods as 1,2, aiw(qiw1,qiw2,...,qiwt,...,qiwv)，qiwt is the w-th frozen article parameter in the t-th detection time period of the ith frozen article in the transportation process, w is the frozen article parameter, w is p1, p2, p3, p1, p2 and p2 respectively represent the temperature, humidity and vibration frequency of the ith frozen article in the transportation process, and the data preprocessing module sends the detection time period parameter set to the modeling and analyzing server;
the frozen article volume detection module comprises a three-dimensional scanner and a modeling analysis server, wherein the three-dimensional scanner is used for acquiring the volume of each frozen article at a transportation starting point and a transportation end point and respectively sending the detected volume of each frozen article at the transportation starting point and the transportation end point to the modeling analysis server;
the odor detection module of the frozen goods comprises an odor detector, a modeling analysis server and a storage module, wherein the odor detector is used for detecting the concentration value of the gas emitted by each frozen goods at the transportation end point and sending the detected concentration value of the gas emitted by each frozen goods at the transportation end point to the modeling analysis server;
the database is used for storing gas concentration influence coefficients corresponding to different gas concentration levels, storing standard frozen article parameters of the frozen articles in the transportation process, storing gas concentration ranges corresponding to different gas concentration levels and storing frozen article deterioration evaluation coefficient ranges corresponding to different frozen article deterioration evaluation levels;
the modeling analysis server receives the detection time period parameter set sent by the data preprocessing module, extracts the frozen article parameters corresponding to each frozen article in the detection time period parameter set in each detection time period, extracts the standard frozen article parameters of the frozen articles stored in the database in the transportation process, and carries out the standard frozen article parameters of each frozen article parameter corresponding to each detection time period and the standard frozen article parameters of the frozen articles in the transportation processComparing to form a parameter comparison set delta Q of the frozen goods in the detection time periodiw(Δqiw1,Δqiw2,...,Δqiwt,...,Δqiwv)，Δqiwt is the difference between the w-th frozen product parameter of the ith frozen product in the t detection time period in the transportation process and the w-th standard frozen product parameter of the ith frozen product in the transportation process, the frozen product parameter contrast value of each frozen product in each detection time period is compared with the frozen product parameter contrast value of each frozen product in the last detection time period to obtain the frozen product relative parameter contrast value of each frozen product in each detection time period, and the frozen product relative parameter contrast values of each frozen product in each detection time period form a time period frozen product relative parameter contrast set Q'iw(q′iw1,q′iw2,...,q′iwt,...,q′iwv)，q′wt is expressed as the difference between the w-th frozen article parameter in the t-th detection time period and the w-th frozen article parameter in the t-1 detection time period during the transportation of the ith frozen article;
the modeling analysis server receives target images of all frozen articles at a transportation starting point and a transportation end point, which are sent by the image preprocessing module, compares the target images of all the frozen articles at the transportation end point with the target images at the transportation starting point to obtain liquid areas on all the frozen articles, and forms a frozen article liquid area set A (a1, a 2.., ai.,..., ag), wherein ai represents the liquid areas of the ith frozen article at the transportation end point;
the modeling analysis server receives the gas concentration value sent by the frozen article odor detection module at the transportation end point of each frozen article, compares the received gas concentration value sent by each frozen article at the transportation end point with the gas concentration ranges corresponding to different gas concentration levels stored in the database, and extracts the gas concentration level corresponding to the gas concentration of each frozen article;
the modeling analysis server receives the volumes of the frozen goods at the transportation starting point and the transportation end point, which are sent by the frozen goods volume detection module, compares the volume of each frozen goods at the transportation end point with the volume at the transportation starting point to form a frozen goods volume comparison set B (B1, B2.., bi.., bg), wherein bi is represented as the volume comparison value of the ith frozen goods at the transportation end point;
the modeling analysis server extracts gas concentration influence coefficients corresponding to different gas concentration levels stored in the database, and according to the time period frozen article relative parameter comparison set, the frozen article liquid area set, the frozen article volume comparison set and the gas concentration influence coefficients corresponding to the gas concentration levels of all the frozen articles at the transportation end point, the frozen article deterioration evaluation coefficients are counted, and the modeling analysis server sends the counted frozen article deterioration evaluation coefficients to the management server;
the management server receives the frozen article deterioration evaluation coefficient sent by the modeling analysis server, compares the frozen article deterioration evaluation coefficient with frozen article deterioration evaluation coefficient ranges corresponding to different frozen article deterioration evaluation grades stored in the database, if the frozen article deterioration evaluation coefficient is within the frozen article deterioration evaluation coefficient range corresponding to the first-level frozen article deterioration evaluation grade, the frozen article deterioration evaluation grade is first-level, if the frozen article deterioration evaluation coefficient is within the frozen article deterioration evaluation coefficient range corresponding to the second-level frozen article deterioration evaluation grade, the frozen article deterioration evaluation grade is second-level, if the frozen article deterioration evaluation coefficient is within the frozen article deterioration evaluation coefficient range corresponding to the third-level frozen article deterioration evaluation grade, the frozen article deterioration evaluation grade is third-level, the management server sends the frozen article deterioration evaluation coefficient and the corresponding frozen article deterioration evaluation grade to the display terminal;
and the display terminal receives and displays the frozen article deterioration evaluation coefficient and the corresponding frozen article deterioration evaluation grade sent by the management server.
2. The cold-chain smart logistics transportation online real-time monitoring cloud platform based on big data and artificial intelligence of claim 1, wherein: the upper limit value of the gas concentration range corresponding to the first-level odor concentration grade is smaller than the lower limit value of the gas concentration range corresponding to the second-level odor concentration grade, and the upper limit value of the gas concentration range corresponding to the second-level odor concentration grade is smaller than the lower limit value of the gas concentration range corresponding to the third-level odor concentration grade.
3. The cold-chain smart logistics transportation online real-time monitoring cloud platform based on big data and artificial intelligence of claim 1, wherein: the gas concentration influence coefficients corresponding to different gas concentration levels have the magnitude sequence of
4. The cold-chain smart logistics transportation online real-time monitoring cloud platform based on big data and artificial intelligence of claim 1, wherein: the upper limit value of the frozen article deterioration evaluation coefficient range corresponding to the first-level frozen article deterioration evaluation level is smaller than the lower limit value of the frozen article deterioration evaluation coefficient range corresponding to the second-level frozen article deterioration evaluation level, and the upper limit value of the frozen article deterioration evaluation coefficient range corresponding to the second-level frozen article deterioration evaluation level is smaller than the lower limit value of the frozen article deterioration evaluation coefficient range corresponding to the third-level frozen article deterioration evaluation level.
5. The cold-chain smart logistics transportation online real-time monitoring cloud platform based on big data and artificial intelligence of claim 1, wherein: the standard frozen good parameters include standard temperature, humidity and vibration frequency.
6. The cold-chain smart logistics transportation online real-time monitoring cloud platform based on big data and artificial intelligence of claim 1, wherein: the deterioration evaluation coefficient of the frozen goods is calculated by the formula
Is expressed as the gas concentration influence coefficient corresponding to the ith frozen product at the E-th gas concentration level, E is 1,2,3, q'wt is expressed as the difference between the w parameter of the frozen article in the t detection time period and the w parameter of the frozen article in the t-1 detection time period during the transportation of the ith frozen article, qiwt is expressed as the w-th frozen article parameter of the ith frozen article in the t-th detection time period in the transportation process, ai is expressed as the liquid area of the ith frozen article at the transportation end point, bi is expressed as the volume contrast value of the ith frozen article at the transportation end point, and e is expressed as a natural number.
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