CN112978128A - Cold-chain logistics transportation commodity quality monitoring and management system based on big data and image analysis technology - Google Patents
Cold-chain logistics transportation commodity quality monitoring and management system based on big data and image analysis technology Download PDFInfo
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Abstract
The invention discloses a quality monitoring and managing system for cold-chain logistics transportation commodities based on big data and an image analysis technology, which comprises an image acquisition module, an image preprocessing module, a temperature detection module, a humidity detection module, an ethylene concentration detection module, a fruit hardness detection module, a fruit quality detection module, a data preprocessing module, a modeling analysis server, a database and a display terminal.
Description
Technical Field
The invention belongs to the technical field of cold-chain logistics monitoring, and particularly relates to a cold-chain logistics transportation commodity quality monitoring and management system based on big data and image analysis technology.
Background
With the continuous development of economy in China, the quality of life of people is improved day by day, the demand of people for fresh fruits is increased continuously at present, the fresh fruits have extremely strict requirements on the temperature and the humidity during storage and transportation, and the market needs of the fresh fruits cannot be met by conventional storage and logistics, so that the cold-chain logistics technology is produced. Meanwhile, the frequent problem of food safety also prompts people to pay more attention to the quality and safety of food, and the quality monitoring of fresh fruits in the cold-chain logistics transportation process is particularly important.
Because the existing cold-chain logistics detection method is to detect at a certain time interval manually, transportation personnel usually observe the temperature and humidity of a hygrothermograph at a certain time point, cannot monitor the temperature and humidity in the vehicle constantly, and cannot effectively and timely perform corresponding refrigeration and humidification on the cold-chain logistics vehicle to control the temperature and humidity. The monitored parameters are single, the monitoring parameters of the cold-chain logistics commodities are not only temperature and humidity, but also gas components, fruit browning indexes and the like, and the temperature and humidity of the storage environment are monitored only, so that the fresh-keeping requirement of the cold-chain logistics commodities cannot be met.
Disclosure of Invention
Aiming at the problems, the invention provides a cold-chain logistics transportation commodity quality monitoring and management system based on big data and image analysis technology, and a plurality of parameters of fresh fruits are detected by combining an image acquisition module, a temperature detection module, a humidity detection module, an ethylene concentration detection module, a fruit hardness detection module and a fruit quality detection module with a modeling analysis server so as to analyze the fruit deterioration evaluation coefficient, thereby solving the problems in the prior art.
The purpose of the invention can be realized by the following technical scheme:
the cold-chain logistics transportation commodity quality monitoring and management system based on big data and image analysis technology comprises an image acquisition module, an image preprocessing module, a temperature detection module, a humidity detection module, an ethylene concentration detection module, a fruit hardness detection module, a fruit quality detection module, a data preprocessing module, a modeling analysis server, a database and a display terminal;
the temperature detection module, the humidity detection module and the ethylene concentration detection module are respectively connected with the data preprocessing module, the image preprocessing module is respectively connected with the image acquisition module and the modeling analysis server, the fruit hardness detection module, the fruit quality detection module and the database are respectively connected with the modeling analysis server, and the modeling analysis server is respectively connected with the data preprocessing module and the display terminal;
the image acquisition module comprises a high-definition camera and is used for acquiring images of fruits of various fruit types in the cold-chain logistics transportation process and sending the acquired images of the fruits of various fruit types in the cold-chain logistics transportation process to the image preprocessing module;
the image preprocessing module is used for receiving images of fruits of various fruit types in the cold chain logistics transportation process sent by the image acquisition module, carrying out image segmentation on the received images of the fruits of various fruit types in the cold chain logistics transportation process, splicing characteristic regions of the fruits of various fruit types obtained by image segmentation, removing background images outside the characteristic regions of the fruits of various fruit types, carrying out image noise reduction processing and image enhancement processing on the retained images of the characteristic regions of the fruits of various fruit types, obtaining target images of the fruits of various fruit types in the cold chain logistics transportation process after processing, and sending the target images of the fruits of various fruit types in the cold chain logistics transportation process to the modeling analysis server respectively;
the temperature detection module comprises a temperature sensor and is used for detecting the temperature in the cold-chain logistics carriage in the transportation process in real time and sending the detected temperature in the cold-chain logistics carriage in the transportation process to the data preprocessing module;
the humidity detection module comprises a humidity sensor and is used for detecting the humidity in the cold-chain logistics carriage in the transportation process in real time and sending the detected humidity in the cold-chain logistics carriage in the transportation process to the data preprocessing module;
the ethylene concentration detection module comprises a gas detector and is used for detecting the ethylene concentration released by all fruits in the cold-chain logistics carriage in real time in the transportation process and sending the detected ethylene concentration released by all fruits in the cold-chain logistics carriage in the transportation process to the data preprocessing module;
the fruit hardness detection module comprises a portable fruit hardness tester, is used for detecting the hardness of each fruit under each fruit type in the cold chain logistics transportation process, selects 3 points with fixed intervals on the equatorial plane of each fruit under each fruit type, measures single fruit for 3 times, averages to obtain the average value of the hardness of each fruit under each fruit type, and sends the detected average value of the hardness of each fruit under each fruit type in the cold chain logistics transportation process to the modeling analysis server;
the fruit quality detection module comprises a quality sensor and a modeling analysis server, wherein the quality sensor is used for detecting the quality of each fruit in the cold-chain logistics transportation process under each fruit type and sending the detected quality of each fruit in the cold-chain logistics transportation process under each fruit type to the modeling analysis server;
the data preprocessing module receives the temperature in the cold-chain logistics carriage in the transportation process sent by the temperature detection module, receives the humidity in the cold-chain logistics carriage in the transportation process sent by the humidity detection module, receives the ethylene concentration released by all fruits in the cold-chain logistics carriage in the transportation process, divides the received temperature, humidity and ethylene concentration in the cold-chain logistics carriage in the transportation process according to the detection time periods, divides the temperature, humidity and ethylene concentration into a plurality of detection time periods according to preset time interval values, and sequentially marks the detection time periods into 1,2, aw(qw1,qw2,...,qwt,...,qwu)，qwt is a numerical value corresponding to a w-th environmental parameter in a t-th detection time period in a cold-chain logistics carriage in the transportation process, w is an environmental parameter, w is p1, p2, p3, p1, p2 and p3 respectively represent the temperature, the humidity and the ethylene concentration in the cold-chain logistics carriage in the transportation process, and a time period environmental parameter set is sent to a modeling analysis server by a data preprocessing module;
the database is used for storing standard environmental parameters, storing fruit browning proportion ranges corresponding to the browning grades of the fruits, storing the number of the fruits under each fruit type, storing the standard quality of the fruits under each fruit type and storing the standard hardness of the fruits under each fruit type;
the modeling analysis server receives target images of fruits in the cold chain logistics transportation process under various fruit types sent by the image preprocessing module and receives the target imagesThe method comprises the steps of obtaining the area of each fruit and the browning area of each fruit in a target image of each fruit in the cold-chain logistics transportation process under each fruit type, counting the browning area proportion of each fruit under each fruit type, and forming a fruit type browning proportion set Ai(ai1,ai2,...,aij,...,aik)，aij represents the browning proportion of the jth fruit under the ith fruit type in the cold-chain logistics transportation process, the modeling analysis server extracts the fruit browning proportion range corresponding to each fruit browning grade stored in the database, compares the browning proportion of each fruit under each fruit type with the fruit browning proportion range corresponding to each fruit browning grade to obtain the browning grade of each fruit under each fruit type, extracts the number of each fruit under each fruit type stored in the database, and counts the browning index of each fruit type according to the browning grade and the number of each fruit under each fruit type;
the modeling analysis server receives the quality of each fruit in the cold chain logistics transportation process under each fruit type sent by the fruit quality detection module to form a fruit type quality set Bi(bi1,bi2,...,bij,...,bik)，bij is the quality of the jth fruit under the ith fruit type in the cold-chain logistics transportation process, the quality of each fruit under each fruit type in the cold-chain logistics transportation process is compared with the standard quality of each fruit under each fruit type stored in the database, and a fruit type quality comparison set B 'is formed'i(b′i1,b′i2,...,b′ij,...,b′ik)，b′ij is expressed as the difference value between the quality of the jth fruit under the ith fruit type and the standard quality of the jth fruit under the ith fruit type in the cold-chain logistics transportation process, and the modeling analysis server calculates the water loss rate of the fruit types according to the fruit type quality comparison set;
the modeling analysis server receives the time period environment parameter set sent by the data preprocessing module, and carries out the environment parameters corresponding to all detection time periods in the cold-chain logistics carriage in the transportation process with the standard environment parameters stored in the databaseComparing to form a time period environment parameter comparison set Q'w(q′w1,q′w2,...,q′wt,...,q′wu)，q′wt is represented as the difference value between the value corresponding to the w-th environmental parameter in the t-th detection time period in the cold-chain logistics carriage in the transportation process and the standard value corresponding to the w-th environmental parameter;
the modeling analysis server receives the average hardness value of each fruit in the cold chain logistics transportation process under each fruit type sent by the fruit hardness detection module to form a fruit type hardness set Ci(ci1,ci2,...,cij,...,cik),cij is the average hardness value of j fruit under the ith fruit type in the cold-chain logistics transportation process, and the average hardness value of each fruit under each fruit type in the cold-chain logistics transportation process is compared with the standard hardness of each fruit under each fruit type stored in the database to form a fruit type hardness comparison set C'i(c′i1,c′i2,...,c′ij,...,c′ik),c′ij is expressed as the difference between the average hardness of the jth fruit under the ith fruit category and the jth fruit under the ith fruit category during the cold chain logistics transportation process;
the modeling analysis server calculates fruit deterioration evaluation coefficients according to the fruit type browning indexes, the fruit type water loss rate, the time period environment parameter comparison set and the fruit type hardness comparison set, and sends the calculated fruit deterioration evaluation coefficients to the display terminal;
and the display terminal is used for receiving and displaying the fruit deterioration evaluation coefficient sent by the modeling analysis server.
Further, the fruit browning proportion range corresponding to the first-level fruit browning level is 0 to 1/4, the fruit browning proportion range corresponding to the second-level fruit browning level is 1/4 to 1/2, the fruit browning proportion range corresponding to the third-level fruit browning level is 1/2 to 3/4, and the fruit browning proportion corresponding to the fourth-level fruit browning level is 3/4 or above.
Further, of individual fruits under said individual fruit speciesThe calculation formula of the browning area ratio is
μij is expressed as the browning area of the jth fruit under the ith fruit type in the cold chain logistics transportation process, Sij is expressed as the area of the jth fruit under the ith fruit category.
Further, the water loss rate of each fruit under each fruit type is calculated according to the formula
b′ij is expressed as the difference between the mass of the jth fruit under the ith fruit category and the standard mass of the jth fruit under the ith fruit category during cold chain logistics transportation, mij is expressed as the standard quality of the jth fruit under the ith fruit category.
Further, the company for calculating the browning index of the fruit variety is
E is expressed as the browning rating of the fruit, riEExpressed as the number of fruits in the ith fruit type at the E-th browning level, niExpressed as the number under the ith fruit type.
Further, the calculation formula of the fruit deterioration evaluation coefficient is
θiExpressed as the browning index, σ, of the ith fruit speciesijExpressed as the water loss rate of the jth fruit under the ith fruit species, qwt is a numerical value q 'corresponding to the w environmental parameter in the t detection time period in the cold-chain logistics compartment in the transportation process'wt is represented as the difference value, c ', between the value corresponding to the w-th environmental parameter in the t-th detection time period in the cold-chain logistics carriage in the transportation process and the standard value corresponding to the w-th environmental parameter'ij is expressed as the average hardness of jth fruit under ith fruit type in the cold chain logistics transportation process and ith fruitDifference between jth fruit under the category.
Has the advantages that:
(1) according to the invention, through the image acquisition module, the temperature detection module, the humidity detection module, the ethylene concentration detection module, the fruit hardness detection module and the fruit quality detection module and combining with the modeling analysis server, a plurality of parameters of fresh fruits are detected to analyze the fruit deterioration evaluation coefficient, and the deterioration condition of various fruit types in the cold-chain logistics transportation process can be visually displayed through the fruit deterioration evaluation coefficient, so that the efficiency and the accuracy of the quality detection of the fresh fruits are improved, the deterioration speed of the fresh fruits is further reduced, the labor cost is reduced, and a powerful technical support is provided for the cold-chain logistics transportation monitoring of the fresh fruits.
(2) According to the invention, by acquiring the environmental temperature, humidity and ethylene concentration of fresh fruits in the cold chain logistics transportation process and the hardness, browning index and quality of each fruit under each fruit type, reliable early-stage data preparation and reference basis are provided for later-stage statistics of fruit deterioration evaluation coefficients, the method has the characteristics of high authenticity and high data accuracy, monitoring parameters are various, single monitoring data is avoided, and the accuracy of an evaluation result is greatly improved.
(3) According to the invention, the real-time detection data of the fresh fruits is provided for logistics personnel by displaying the deterioration evaluation coefficients of various fruit types at the display terminal, so that the logistics personnel can conveniently take different measures to keep the fresh fruits fresh according to the real-time detection data of the fresh fruits, and the quality of the fresh fruits in the cold-chain logistics transportation process is greatly ensured.
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 logistics transportation commodity quality monitoring and management system based on big data and image analysis technology comprises an image acquisition module, an image preprocessing module, a temperature detection module, a humidity detection module, an ethylene concentration detection module, a fruit hardness detection module, a fruit quality detection module, a data preprocessing module, a modeling analysis server, a database and a display terminal;
the temperature detection module, the humidity detection module and the ethylene concentration detection module are respectively connected with the data preprocessing module, the image preprocessing module is respectively connected with the image acquisition module and the modeling analysis server, the fruit hardness detection module, the fruit quality detection module and the database are respectively connected with the modeling analysis server, and the modeling analysis server is respectively connected with the data preprocessing module and the display terminal;
the image acquisition module comprises a high-definition camera and is used for acquiring images of fruits of various fruit types in the cold-chain logistics transportation process and sending the acquired images of the fruits of various fruit types in the cold-chain logistics transportation process to the image preprocessing module;
the image preprocessing module is used for receiving images of fruits of various fruit types in the cold chain logistics transportation process sent by the image acquisition module, carrying out image segmentation on the received images of the fruits of various fruit types in the cold chain logistics transportation process, splicing characteristic regions of the fruits of various fruit types obtained by image segmentation, removing background images outside the characteristic regions of the fruits of various fruit types, carrying out image noise reduction processing and image enhancement processing on the retained images of the characteristic regions of the fruits of various fruit types, obtaining target images of the fruits of various fruit types in the cold chain logistics transportation process after processing, and sending the target images of the fruits of various fruit types in the cold chain logistics transportation process to the modeling analysis server respectively;
the temperature detection module comprises a temperature sensor and is used for detecting the temperature in the cold-chain logistics carriage in the transportation process in real time and sending the detected temperature in the cold-chain logistics carriage in the transportation process to the data preprocessing module;
the humidity detection module comprises a humidity sensor and is used for detecting the humidity in the cold-chain logistics carriage in the transportation process in real time and sending the detected humidity in the cold-chain logistics carriage in the transportation process to the data preprocessing module;
the ethylene concentration detection module comprises a gas detector and is used for detecting the ethylene concentration released by all fruits in the cold-chain logistics carriage in real time in the transportation process and sending the detected ethylene concentration released by all fruits in the cold-chain logistics carriage in the transportation process to the data preprocessing module;
the fruit hardness detection module comprises a portable fruit hardness tester, is used for detecting the hardness of each fruit under each fruit type in the cold chain logistics transportation process, selects 3 points with fixed intervals on the equatorial plane of each fruit under each fruit type, measures single fruit for 3 times, averages to obtain the average value of the hardness of each fruit under each fruit type, and sends the detected average value of the hardness of each fruit under each fruit type in the cold chain logistics transportation process to the modeling analysis server;
the fruit quality detection module comprises a quality sensor and a modeling analysis server, wherein the quality sensor is used for detecting the quality of each fruit in the cold-chain logistics transportation process under each fruit type and sending the detected quality of each fruit in the cold-chain logistics transportation process under each fruit type to the modeling analysis server;
the data preprocessing module receives the temperature in the cold-chain logistics carriage in the transportation process sent by the temperature detection module, receives the humidity in the cold-chain logistics carriage in the transportation process sent by the humidity detection module, and receives the temperature in the cold-chain logistics carriage in the transportation processThe method comprises the steps that the ethylene concentration released by fruits is divided into a plurality of detection time periods according to the detection time periods and the temperature, the humidity and the ethylene concentration in the cold-chain logistics carriage in the transportation process, the detection time periods are divided into a plurality of detection time periods according to preset time interval values, and the detection time periods are sequentially marked as 1,2, aw(qw1,qw2,...,qwt,...,qwu)，qwt is a numerical value corresponding to a w-th environmental parameter in a t-th detection time period in a cold-chain logistics carriage in the transportation process, w is an environmental parameter, w is p1, p2, p3, p1, p2 and p3 respectively represent the temperature, the humidity and the ethylene concentration in the cold-chain logistics carriage in the transportation process, and a time period environmental parameter set is sent to a modeling analysis server by a data preprocessing module;
according to the embodiment, the environment temperature, the humidity and the ethylene concentration of the fresh fruits in the cold chain logistics transportation process and the hardness, the browning index and the quality of each fruit under each fruit type are obtained, so that reliable early-stage data preparation and reference basis is provided for later-stage statistics of fruit deterioration evaluation coefficients, the fruit quality evaluation method has the characteristics of high authenticity and high data accuracy, monitoring parameters are various, single monitoring data is avoided, and the accuracy of evaluation results is greatly improved;
the database is used for storing standard environmental parameters and storing fruit browning proportion ranges corresponding to the fruit browning grades, the fruit browning proportion range corresponding to the first-level fruit browning grade is 0-1/4, the fruit browning proportion range corresponding to the second-level fruit browning grade is 1/4-1/2, the fruit browning proportion range corresponding to the third-level fruit browning grade is 1/2-3/4, the fruit browning proportion corresponding to the fourth-level fruit browning grade is above 3/4, the number of each fruit in each fruit type is stored, the standard quality of each fruit in each fruit type is stored, and the standard hardness of each fruit in each fruit type is stored;
the modeling analysis server receives target images of fruits in the cold chain logistics transportation process under various fruit types sent by the image preprocessing module, and the fruits in the cold chain logistics transportation process under various fruit types are conveyed by the modeling analysis serverThe area and the browning area of each fruit are obtained by the target image in the process, the browning area proportion of each fruit under each fruit type is counted, and the calculation formula of the browning area proportion of each fruit under each fruit type is
μij is expressed as the browning area of the jth fruit under the ith fruit type in the cold chain logistics transportation process, Sij is the area of the jth fruit under the ith fruit type and forms a fruit type browning ratio set Ai(ai1,ai2,...,aij,...,aik)，aij represents the browning proportion of the jth fruit under the ith fruit type in the cold-chain logistics transportation process, a modeling analysis server extracts the fruit browning proportion range corresponding to each fruit browning grade stored in a database, compares the browning proportion of each fruit under each fruit type with the fruit browning proportion range corresponding to each fruit browning grade to obtain the browning grade of each fruit under each fruit type, extracts the number of each fruit under each fruit type stored in the database, and counts the browning indexes of the fruit types according to the browning grade and the number of each fruit under each fruit type, wherein the calculation company of the browning indexes of the fruit types is
E is expressed as the browning rating of the fruit, riEExpressed as the number of fruits in the ith fruit type at the E-th browning level, niExpressed as the number under the ith fruit species;
the modeling analysis server receives the quality of each fruit in the cold chain logistics transportation process under each fruit type sent by the fruit quality detection module to form a fruit type quality set Bi(bi1,bi2,...,bij,...,bik)，bij represents the quality of the jth fruit under the ith fruit type in the cold-chain logistics transportation process, and the quality of each fruit under each fruit type in the cold-chain logistics transportation process is compared with the quality of each fruit under each fruit type stored in the databaseComparing the standard quality of each fruit to form a fruit type quality comparison set B'i(b′i1,b′i2,...,b′ij,...,b′ik)，b′ij is expressed as the difference value between the quality of the jth fruit under the ith fruit type and the standard quality of the jth fruit under the ith fruit type in the cold-chain logistics transportation process, the modeling analysis server counts the water loss rate of the fruit types according to the fruit type quality comparison set, and the calculation formula of the water loss rate of each fruit under each fruit type is
b′ij is expressed as the difference between the mass of the jth fruit under the ith fruit category and the standard mass of the jth fruit under the ith fruit category during cold chain logistics transportation, mij is expressed as the standard quality of the jth fruit under the ith fruit category;
the modeling analysis server receives the time period environment parameter set sent by the data preprocessing module, compares the environment parameters corresponding to all detection time periods in the cold-chain logistics carriage in the transportation process with the standard environment parameters stored in the database to form a time period environment parameter comparison set Q'w(q′w1,q′w2,...,q′wt,...,q′wu)，q′wt is represented as the difference value between the value corresponding to the w-th environmental parameter in the t-th detection time period in the cold-chain logistics carriage in the transportation process and the standard value corresponding to the w-th environmental parameter;
the modeling analysis server receives the average hardness value of each fruit in the cold chain logistics transportation process under each fruit type sent by the fruit hardness detection module to form a fruit type hardness set Ci(ci1,ci2,...,cij,...,cik),cij is the hardness average value of jth fruit under ith fruit type in the cold-chain logistics transportation process, and the hardness average value of each fruit under each fruit type in the cold-chain logistics transportation process is compared with the standard hardness of each fruit under each fruit type stored in the database to form the fruit typeHardness comparative set C'i(c′i1,c′i2,...,c′ij,...,c′ik),c′ij is expressed as the difference between the average hardness of the jth fruit under the ith fruit category and the jth fruit under the ith fruit category during the cold chain logistics transportation process;
the modeling analysis server counts the fruit deterioration evaluation coefficient according to the fruit type browning index, the fruit type water loss rate, the time period environmental parameter comparison set and the fruit type hardness comparison set, and the calculation formula of the fruit deterioration evaluation coefficient is
θiExpressed as the browning index, σ, of the ith fruit speciesijExpressed as the water loss rate of the jth fruit under the ith fruit species, qwt is a numerical value q 'corresponding to the w environmental parameter in the t detection time period in the cold-chain logistics compartment in the transportation process'wt is represented as the difference value, c ', between the value corresponding to the w-th environmental parameter in the t-th detection time period in the cold-chain logistics carriage in the transportation process and the standard value corresponding to the w-th environmental parameter'ij is expressed as the difference value between the hardness average value of the jth fruit under the ith fruit type and the jth fruit under the ith fruit type in the cold-chain logistics transportation process, and the statistical fruit deterioration evaluation coefficient is sent to a display terminal;
the display terminal is used for receiving the fruit deterioration evaluation coefficient that the modeling analysis server sent to show, shows through the deterioration evaluation coefficient to each fruit kind, provides the real-time detection number data of giving birth to bright fruit for the logistics personnel, makes things convenient for the logistics personnel to take different measures to keep fresh to bright fruit according to the real-time detection data of giving birth to bright fruit, has ensured the quality of giving birth to bright fruit in cold chain logistics transportation greatly.
According to the invention, through the image acquisition module, the temperature detection module, the humidity detection module, the ethylene concentration detection module, the fruit hardness detection module and the fruit quality detection module and combining with the modeling analysis server, a plurality of parameters of fresh fruits are detected to analyze the fruit deterioration evaluation coefficient, and the deterioration condition of various fruit types in the cold-chain logistics transportation process can be visually displayed through the fruit deterioration evaluation coefficient, so that the efficiency and the accuracy of the quality detection of the fresh fruits are improved, the deterioration speed of the fresh fruits is further reduced, the labor cost is reduced, and a powerful technical support is provided for the cold-chain logistics transportation monitoring of the fresh fruits.
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 logistics transportation commodity quality monitoring management system based on big data and image analysis technique, its characterized in that: the system comprises an image acquisition module, an image preprocessing module, a temperature detection module, a humidity detection module, an ethylene concentration detection module, a fruit hardness detection module, a fruit quality detection module, a data preprocessing module, a modeling analysis server, a database and a display terminal;
the temperature detection module, the humidity detection module and the ethylene concentration detection module are respectively connected with the data preprocessing module, the image preprocessing module is respectively connected with the image acquisition module and the modeling analysis server, the fruit hardness detection module, the fruit quality detection module and the database are respectively connected with the modeling analysis server, and the modeling analysis server is respectively connected with the data preprocessing module and the display terminal;
the image acquisition module comprises a high-definition camera and is used for acquiring images of fruits of various fruit types in the cold-chain logistics transportation process and sending the acquired images of the fruits of various fruit types in the cold-chain logistics transportation process to the image preprocessing module;
the image preprocessing module is used for receiving images of fruits of various fruit types in the cold chain logistics transportation process sent by the image acquisition module, carrying out image segmentation on the received images of the fruits of various fruit types in the cold chain logistics transportation process, splicing characteristic regions of the fruits of various fruit types obtained by image segmentation, removing background images outside the characteristic regions of the fruits of various fruit types, carrying out image noise reduction processing and image enhancement processing on the retained images of the characteristic regions of the fruits of various fruit types, obtaining target images of the fruits of various fruit types in the cold chain logistics transportation process after processing, and sending the target images of the fruits of various fruit types in the cold chain logistics transportation process to the modeling analysis server respectively;
the temperature detection module comprises a temperature sensor and is used for detecting the temperature in the cold-chain logistics carriage in the transportation process in real time and sending the detected temperature in the cold-chain logistics carriage in the transportation process to the data preprocessing module;
the humidity detection module comprises a humidity sensor and is used for detecting the humidity in the cold-chain logistics carriage in the transportation process in real time and sending the detected humidity in the cold-chain logistics carriage in the transportation process to the data preprocessing module;
the ethylene concentration detection module comprises a gas detector and is used for detecting the ethylene concentration released by all fruits in the cold-chain logistics carriage in real time in the transportation process and sending the detected ethylene concentration released by all fruits in the cold-chain logistics carriage in the transportation process to the data preprocessing module;
the fruit hardness detection module comprises a portable fruit hardness tester, is used for detecting the hardness of each fruit under each fruit type in the cold chain logistics transportation process, selects 3 points with fixed intervals on the equatorial plane of each fruit under each fruit type, measures single fruit for 3 times, averages to obtain the average value of the hardness of each fruit under each fruit type, and sends the detected average value of the hardness of each fruit under each fruit type in the cold chain logistics transportation process to the modeling analysis server;
the fruit quality detection module comprises a quality sensor and a modeling analysis server, wherein the quality sensor is used for detecting the quality of each fruit in the cold-chain logistics transportation process under each fruit type and sending the detected quality of each fruit in the cold-chain logistics transportation process under each fruit type to the modeling analysis server;
the data preprocessing module receives the temperature in the cold-chain logistics carriage in the transportation process sent by the temperature detection module, receives the humidity in the cold-chain logistics carriage in the transportation process sent by the humidity detection module, receives the ethylene concentration released by all fruits in the cold-chain logistics carriage in the transportation process, divides the received temperature, humidity and ethylene concentration in the cold-chain logistics carriage in the transportation process according to the detection time periods, divides the temperature, humidity and ethylene concentration into a plurality of detection time periods according to preset time interval values, and sequentially marks the detection time periods into 1,2, aw(qw1,qw2,...,qwt,...,qwu)，qwt is a numerical value corresponding to a w-th environmental parameter in a t-th detection time period in a cold-chain logistics carriage in the transportation process, w is an environmental parameter, w is p1, p2, p3, p1, p2 and p3 respectively represent the temperature, the humidity and the ethylene concentration in the cold-chain logistics carriage in the transportation process, and a time period environmental parameter set is sent to a modeling analysis server by a data preprocessing module;
the database is used for storing standard environmental parameters, storing fruit browning proportion ranges corresponding to the browning grades of the fruits, storing the number of the fruits under each fruit type, storing the standard quality of the fruits under each fruit type and storing the standard hardness of the fruits under each fruit type;
the modeling analysis server receives target images of fruits in the cold-chain logistics transportation process under various fruit types sent by the image preprocessing module, obtains the area of each fruit and the browning area of each fruit in the cold-chain logistics transportation process by receiving the target images of the fruits under various fruit types, calculates the browning area proportion of each fruit under various fruit types, and forms a fruit type browning proportion set Ai(ai1,ai2,...,aij,...,aik)，aij is expressed as the number of the ith fruit type in the cold chain logistics transportation processThe modeling analysis server extracts fruit browning proportion ranges corresponding to the fruit browning grades stored in the database, compares the browning proportion of each fruit in each fruit type with the fruit browning proportion range corresponding to each fruit browning grade to obtain the browning grade of each fruit in each fruit type, extracts the number of each fruit in each fruit type stored in the database, and counts the browning index of each fruit type according to the browning grade and the number of each fruit in each fruit type;
the modeling analysis server receives the quality of each fruit in the cold chain logistics transportation process under each fruit type sent by the fruit quality detection module to form a fruit type quality set Bi(bi1,bi2,...,bij,...,bik)，bij is the quality of the jth fruit under the ith fruit type in the cold-chain logistics transportation process, the quality of each fruit under each fruit type in the cold-chain logistics transportation process is compared with the standard quality of each fruit under each fruit type stored in the database, and a fruit type quality comparison set B 'is formed'i(b′i1,b′i2,...,b′ij,...,b′ik)，b′ij is expressed as the difference value between the quality of the jth fruit under the ith fruit type and the standard quality of the jth fruit under the ith fruit type in the cold-chain logistics transportation process, and the modeling analysis server calculates the water loss rate of the fruit types according to the fruit type quality comparison set;
the modeling analysis server receives the time period environment parameter set sent by the data preprocessing module, compares the environment parameters corresponding to all detection time periods in the cold-chain logistics carriage in the transportation process with the standard environment parameters stored in the database to form a time period environment parameter comparison set Q'w(q′w1,q′w2,...,q′wt,...,q′wu)，q′wt is represented as the difference value between the value corresponding to the w-th environmental parameter in the t-th detection time period in the cold-chain logistics carriage in the transportation process and the standard value corresponding to the w-th environmental parameter;
modeling analysis serverReceiving the average hardness value of each fruit in the cold chain logistics transportation process under each fruit type sent by the fruit hardness detection module to form a fruit type hardness set Ci(ci1,ci2,...,cij,...,cik),cij is the average hardness value of j fruit under the ith fruit type in the cold-chain logistics transportation process, and the average hardness value of each fruit under each fruit type in the cold-chain logistics transportation process is compared with the standard hardness of each fruit under each fruit type stored in the database to form a fruit type hardness comparison set C'i(c′i1,c′i2,...,c′ij,...,c′ik),c′ij is expressed as the difference between the average hardness of the jth fruit under the ith fruit category and the jth fruit under the ith fruit category during the cold chain logistics transportation process;
the modeling analysis server calculates fruit deterioration evaluation coefficients according to the fruit type browning indexes, the fruit type water loss rate, the time period environment parameter comparison set and the fruit type hardness comparison set, and sends the calculated fruit deterioration evaluation coefficients to the display terminal;
and the display terminal is used for receiving and displaying the fruit deterioration evaluation coefficient sent by the modeling analysis server.
2. The cold-chain logistics transportation commodity quality monitoring management system based on big data and image analysis technology as claimed in claim 1, characterized in that: the fruit browning proportion range corresponding to the first-level fruit browning level is 0-1/4, the fruit browning proportion range corresponding to the second-level fruit browning level is 1/4-1/2, the fruit browning proportion range corresponding to the third-level fruit browning level is 1/2-3/4, and the fruit browning proportion corresponding to the fourth-level fruit browning level is 3/4 or above.
3. The cold-chain logistics transportation commodity quality monitoring management system based on big data and image analysis technology as claimed in claim 1, characterized in that: the calculation formula of the browning area proportion of each fruit under each fruit type is
μij is expressed as the browning area of the jth fruit under the ith fruit type in the cold chain logistics transportation process, Sij is expressed as the area of the jth fruit under the ith fruit category.
4. The cold-chain logistics transportation commodity quality monitoring management system based on big data and image analysis technology as claimed in claim 1, characterized in that: the water loss rate calculation formula of each fruit under each fruit type is
b′ij is expressed as the difference between the mass of the jth fruit under the ith fruit category and the standard mass of the jth fruit under the ith fruit category during cold chain logistics transportation, mij is expressed as the standard quality of the jth fruit under the ith fruit category.
5. The cold-chain logistics transportation commodity quality monitoring management system based on big data and image analysis technology as claimed in claim 1, characterized in that: the fruit variety browning index is calculated by
E is expressed as the browning rating of the fruit, riEExpressed as the number of fruits in the ith fruit type at the E-th browning level, niExpressed as the number under the ith fruit type.
6. The cold-chain logistics transportation commodity quality monitoring management system based on big data and image analysis technology as claimed in claim 1, characterized in that: the fruit deterioration evaluation coefficient is calculated by the formula
θiExpressed as the ith fruit speciesIndex of browning, σijExpressed as the water loss rate of the jth fruit under the ith fruit species, qwt is a numerical value q 'corresponding to the w environmental parameter in the t detection time period in the cold-chain logistics compartment in the transportation process'wt is represented as the difference value, c ', between the value corresponding to the w-th environmental parameter in the t-th detection time period in the cold-chain logistics carriage in the transportation process and the standard value corresponding to the w-th environmental parameter'ij is expressed as the difference between the average of the firmness of the jth fruit under the ith fruit category and the jth fruit under the ith fruit category during cold chain logistics transportation.
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