CN114926048B - Intelligent supervision method and system for third-party feed transportation enterprises - Google Patents
Intelligent supervision method and system for third-party feed transportation enterprises Download PDFInfo
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Abstract
The application discloses an intelligent supervision method and system for a third-party feed transportation enterprise, which belong to the field of artificial intelligence, and the method comprises the following steps: through high in the clouds supervisory systems platform and transportation information acquisition device and transportation monitoring devices communication connection for carry out intelligent supervision to third party fodder transportation enterprise, transportation information acquisition device is used for gathering transportation data in real time, transportation monitoring devices is used for right transportation data carries out dynamic monitoring, includes four subassemblies: the cloud supervision system platform is matched with a corresponding supervision scheme from a database after receiving the transportation evaluation result. Solves the technical problems of lack of intelligent supervision and high transportation cost of feed transportation enterprises in the prior art. The intelligent supervision of the third-party feed transportation enterprises is achieved, and the technical effects of improving supervision efficiency and reducing transportation cost are achieved.
Description
Technical Field
The application relates to the field of artificial intelligence, in particular to an intelligent supervision method and system for a third-party feed transportation enterprise.
Background
With the rapid development of economic level, materials are circulated in different areas, and must be transported through logistics. The research on the condition of logistics circulation in the process of feeding from the original supply place to the demand place has very important significance for the development of animal husbandry in China.
At present, feed logistics transportation belongs to a large number of commodity logistics, logistics enterprises mainly rely on manual operation under line in the process of carrying out logistics transportation to carry out delivery of feed, and data in the process of recording are recorded through paper in the transportation process to carry out delivery of data in different delivery links.
However, due to the many links in the logistics transportation transaction process, the paper records cannot be effectively stored, so that data is lost, and meanwhile, the whole transportation process is not effectively monitored. The logistics information platform cannot be utilized to timely and effectively communicate with logistics enterprises, the risk of artificial hysteresis management is high, the quality of the finally delivered product cannot be guaranteed, and the technical problems of lack of intelligent supervision to the feed transportation enterprises and high transportation cost exist in the prior art.
Disclosure of Invention
The purpose of the application is to provide an intelligent supervision method and system for a third-party feed transportation enterprise, which are used for solving the technical problems of lack of intelligent supervision for the feed transportation enterprise and high transportation cost in the prior art.
In view of the above problems, the present application provides an intelligent supervision method and system for a third party feed transportation enterprise.
In a first aspect, the present application provides an intelligent supervisory system for a third party feed transportation enterprise, the system comprising: the cloud supervision system platform is in communication connection with a plurality of transportation information acquisition devices and a plurality of transportation monitoring devices which are respectively and independently installed on different transportation vehicles and is used for intelligently supervising a third-party feed transportation enterprise; the transportation information acquisition device is used for acquiring speed data of the transportation vehicle, temperature and humidity data of the transportation vehicle and state information of feed in real time, and uploading the acquired transportation data to the transportation monitoring device, and is provided with a temperature and humidity sensor, a speed sensor, a GPS positioning module, a time node module, a communication module and an image acquisition module; the transportation monitoring device is used for dynamically monitoring the transportation data and comprises four components: the system comprises a data receiving and transmitting module, a data preprocessing module, a data analysis module and a transportation evaluation module; the data preprocessing module is arranged behind the data receiving and transmitting module and is used for preprocessing the received transportation data to obtain preprocessed data; the data analysis module is arranged behind the data preprocessing module and is used for analyzing the preprocessed data to obtain transportation condition information; the transportation evaluation module is arranged behind the data analysis module and is used for comparing the data in transportation with the transportation condition information to obtain a transportation evaluation result; the data transceiver module is used for receiving information from the information acquisition device and sending the transportation evaluation result to the cloud supervision system platform; and after receiving the transportation evaluation result, the cloud supervision system platform matches a corresponding supervision scheme from a database.
On the other hand, the application also provides an intelligent supervision method of the third-party feed transportation enterprise, which is realized by an intelligent supervision system of the third-party feed transportation enterprise, wherein the method comprises the following steps: the method comprises the steps of setting a cloud supervision system platform, wherein the cloud supervision system platform is in communication connection with a plurality of transportation information acquisition devices and a plurality of transportation monitoring devices which are respectively and independently installed on different transportation vehicles and is used for intelligently supervising a third-party feed transportation enterprise; the method comprises the steps of acquiring speed data of a transport vehicle, temperature and humidity data of the transport vehicle and state information of feed in real time through a transport information acquisition device, and uploading the acquired transport data to a transport monitoring device, wherein the transport information acquisition device is provided with a temperature and humidity sensor, a speed sensor, a GPS positioning module, a time node module, a communication module and an image acquisition module; the transportation data is dynamically monitored by the transportation monitoring device, and the transportation monitoring device comprises four components: the system comprises a data receiving and transmitting module, a data preprocessing module, a data analysis module and a transportation evaluation module; preprocessing the received transportation data through the data preprocessing module to obtain preprocessed data; analyzing the preprocessed data through the data analysis module to obtain transportation condition information; comparing the in-transit data with the transit condition information through the transit evaluation module to obtain a transit evaluation result; receiving information from an information acquisition device through the data transceiver module and sending the transportation evaluation result to a cloud supervision system platform; and after receiving the transportation evaluation result, the cloud supervision system platform matches a corresponding supervision scheme from a database.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
according to the intelligent monitoring system, the cloud supervision system platform is in communication connection with a plurality of transportation information acquisition devices and a plurality of transportation monitoring devices which are respectively and independently installed on different transportation vehicles and is used for intelligently supervising a third-party feed transportation enterprise; the transportation information acquisition device is used for acquiring speed data of the transportation vehicle, temperature and humidity data of the transportation vehicle and state information of feed in real time, and uploading the acquired transportation data to the transportation monitoring device, and is provided with a temperature and humidity sensor, a speed sensor, a GPS positioning module, a time node module, a communication module and an image acquisition module; the transportation monitoring device is used for dynamically monitoring the transportation data and comprises four components: the system comprises a data receiving and transmitting module, a data preprocessing module, a data analysis module and a transportation evaluation module; the data preprocessing module is arranged behind the data receiving and transmitting module and is used for preprocessing the received transportation data to obtain preprocessed data; the data analysis module is arranged behind the data preprocessing module and is used for analyzing the preprocessed data to obtain transportation condition information; the transportation evaluation module is arranged behind the data analysis module and is used for comparing the data in transportation with the transportation condition information to obtain a transportation evaluation result; the data transceiver module is used for receiving information from the information acquisition device and sending the transportation evaluation result to the cloud supervision system platform; and after receiving the transportation evaluation result, the cloud supervision system platform matches a corresponding supervision scheme from a database. The intelligent supervision of the third-party feed transportation enterprises is achieved, and the technical effects of improving supervision efficiency and reducing transportation cost are achieved.
Drawings
Fig. 1 is a schematic diagram of the system architecture for intelligent supervision of a third party feed transportation enterprise;
FIG. 2 is a schematic diagram of the structure of a data preprocessing module in the system of the present application;
FIG. 3 is a schematic diagram of the structural components of the data analysis module in the system of the present application;
FIG. 4 is a schematic diagram of the structural composition of a transport assessment module in the system of the present application;
fig. 5 is a schematic structural diagram of a correction submodule in the system of the present application.
Reference numerals illustrate: the system comprises a cloud supervision system platform 1000, a transportation information acquisition device 2000, a transportation monitoring device 3000, a temperature and humidity sensor 2100, a speed sensor 2200, a GPS positioning module 2300, a time node module 2400, a communication module 2500, an image acquisition module 2600, a data transceiving module 3100, a data preprocessing module 3200, a data analysis module 3300, a transportation evaluation module 3400, a time-sequence processing sub-module 3210, a clustering processing sub-module 3220, an attribute extraction component 3221, a clustering component 3222, an information acquisition sub-module 3310, a weight distribution sub-module 3320, a weighting calculation sub-module 3330, a condition matching sub-module 3340, a comparison sub-module 3410, a judgment sub-module 3420, a correction sub-module 3430, an output sub-module 3440, an adjustment component 3431, a selection component 3432, a feedback component 3433 and a judgment component 3434.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the embodiments of the present application will be described in further detail below with reference to the accompanying drawings.
Referring to fig. 1 to 5, the structural composition of the intelligent supervision system for the third party feed transportation enterprise is specifically described.
As shown in fig. 1, the present application provides an intelligent supervisory system for a third party feed transportation enterprise, the system comprising:
cloud supervisory systems platform 1000, cloud supervisory systems platform 1000 and a plurality of transportation information acquisition device 2000 and a plurality of transportation monitoring devices 3000 of respectively independently installing on different transport vehicles are connected for carry out intelligent supervision to third party fodder transportation enterprise.
Preferably, the cloud supervision system platform 1000 is a platform for intelligent supervision of the third-party feed transportation enterprises by the suppliers and the receivers, so that an intelligent supervision transportation process can be realized, transportation efficiency and quality are ensured, and transportation cost is reduced.
The transportation information collection device 2000 is configured to collect speed data of the transportation vehicle, temperature and humidity data of the transportation vehicle, and status information of the feed in real time, and upload the collected transportation data to the transportation monitoring device 3000, where the transportation information collection device 2000 is provided with a temperature and humidity sensor 2100, a speed sensor 2200, a GPS positioning module 2300, a time node module 2400, a communication module 2500, and an image collection module 2600.
Preferably, the transportation information collection device 2000 is disposed on each transportation vehicle, and collects real-time temperature and humidity data in a space environment of a compartment of the transportation vehicle through the temperature and humidity sensor 2100, and transmits the real-time temperature and humidity data to the communication module 2500, where the number of the temperature and humidity sensors 2100 may be multiple, specifically set by a worker, and may be disposed at multiple positions of the transportation compartment, and thermal resistance temperature sensors, thermocouple temperature sensors and the like may be used.
Preferably, the speed sensor 2200 is used to collect real-time speed information of the transport vehicle and transmit the real-time speed information to the communication module 2500, wherein the speed sensor is disposed in a tire of the transport vehicle.
The GPS positioning module 2300 is configured to position the real-time position of the transport vehicle, thereby obtaining the real-time position of the transport vehicle, obtaining the road condition in the transportation process, and transmitting the positioning information to the communication module 2500 in real time. The GPS positioning module 2300 may be disposed on a roof of a transport vehicle, so as to avoid signals from being received without being blocked.
The time node module 2400 is configured to record the condition of the transportation flow node where the transportation vehicle is located, thereby determining the flow information of the transportation vehicle at different nodes, and transmitting the time node information to the communication module 2500 in real time.
The image acquisition module 2600 is disposed in a carriage of the transport vehicle, and is used for image acquisition of the feed, so as to provide a judgment basis for subsequently judging the state of the feed, and transmit the acquired image information to the communication module 2500 in real time.
The communication module 2500 is configured to be in communication connection with the transportation monitoring device 3000, and transmit the information collected by the received temperature and humidity sensor 2100, the received speed sensor 2200, the received GPS positioning module 2300, the received time node module 2400, and the received information collected by the received image collecting module 2600 to the transportation monitoring device 3000, so as to provide basic data for subsequent supervision.
The transportation monitoring device 3000 is configured to dynamically monitor the transportation data, and includes four components: a data transceiver module 3100, a data preprocessing module 3200, a data analysis module 3300 and a transportation evaluation module 3400.
Preferably, the transportation monitoring device is arranged on a driving platform of the vehicle, and after receiving the transportation data in the transportation information acquisition device 2000, the transportation monitoring device performs intelligent monitoring, so as to accurately monitor the third-party feed transportation enterprise.
The data preprocessing module 3200 is disposed behind the data transceiving module 3100, and is configured to preprocess the received transportation data, to obtain preprocessed data.
Further, as shown in fig. 2, the data preprocessing module 3200 further includes:
the data preprocessing module 3200 includes a sequential processing sub-module 3210 and a clustering processing sub-module 3220;
the time-sequence processing sub-module 3210 is configured to perform time-sequence processing on the obtained transportation data to obtain time-sequence processed data;
the clustering sub-module 3220 is disposed behind the time-series processing sub-module 3210, and is configured to perform processing clustering on the time-series processing data to obtain the preprocessing data.
Specifically, the preprocessing data is data obtained by performing the time-series processing and the clustering processing on the received transportation data. The time-series processing refers to ordering the transportation data in the order from the early to the late. The time-series processing data is data obtained after time arrangement. The clustering process refers to that three groups of data with similar composition are carried out on the time-sequence processing data according to different attributes, and analysis data is provided for subsequent supervision after the data are divided.
Further, the cluster processing sub-module 3220 further includes:
the clustering sub-module 3220 includes an attribute extraction component 3221 and a clustering component 3222;
the attribute extraction component 3221 is configured to extract an attribute of the time-sequential processing data to obtain an attribute data set;
the clustering unit 3222 is configured to perform clustering on the data in the attribute data set after the attribute extraction unit 3221 to obtain the preprocessed data, where the preprocessed data is divided into three groups of data, and includes: loading data, in-transit data, and receiving data.
Specifically, the attribute of the time-series processing data is an attribute for characterizing which stage in the transportation process the data is in, and includes: loading, transporting and receiving. The attribute extraction module 3221 extracts the attribute of the time-series processing data to obtain the attribute data set. Wherein the attribute data set is a data set containing all attributes of the time-series processing data. Clustering is carried out according to a top-down method, and the attribute data set is clustered according to attributes to obtain the preprocessing data. The loading data are data in the loading process, the data in transportation are data in the transportation process, and the receiving data are data in the receiving process. By classifying the data according to different stages in the transportation process, the technical effect of providing target data for subsequent supervision is achieved.
The data analysis module 3300 is disposed behind the data preprocessing module 3200, and is configured to analyze the preprocessed data to obtain transportation condition information.
Further, as shown in fig. 3, the data analysis module 3300 further includes:
the data analysis module 3300 determines condition information during transportation by analyzing the pre-processed data, wherein the data analysis module 3300 includes: information acquisition submodule 3310, weight assignment submodule 3320, weight calculation submodule 3330, and condition matching submodule 3340;
the information obtaining sub-module 3310 is used for obtaining historical transportation information;
the weight distribution sub-module 3320 is arranged behind the information acquisition sub-module 3310 and is used for distributing weights of the loading data, the in-transit data and the receiving data according to the historical transportation condition information to obtain a weight distribution result;
the weight calculation sub-module 3330 is arranged behind the weight distribution sub-module 3320 and is used for carrying out weight calculation on the loading data, the in-transit data and the receiving data according to the weight distribution result to obtain a calculation result;
the condition matching sub-module 3340 is arranged behind the weight calculation sub-module 3330 and is used for matching corresponding transportation conditions in the sub-module according to the calculation result to obtain the transportation condition information.
Specifically, the transportation condition information is transportation condition information that is required to be satisfied in the course of transportation, which is judged based on the historical transportation situation information. The historical transportation condition information is obtained in the past transportation process of a certain period of time and comprises the influence condition of each data on the transportation process. The weight distribution sub-module 3320 distributes weights to the loading data, the in-transit data and the receiving data, and the weight distribution result comprises weight values of three groups of data. Further, the weight calculation is performed by the weight calculation sub-module 3330 based on the weight distribution result to obtain the calculation result. The calculation result is a transportation situation result obtained after weighting calculation. Finally, matching is performed in the sub-module according to the calculation result by the condition matching sub-module 3340, and the transportation condition which accords with the current transportation condition is found. The technical effect of providing a judging basis for judging whether the transportation conditions are met in the transportation process of the transportation enterprises is achieved.
The transportation evaluation module 3400 is disposed after the data analysis module 3300 and is configured to compare the in-transportation data with the transportation condition information to obtain a transportation evaluation result.
Further, as shown in fig. 4, the transport evaluation module 3400 further includes:
the transport evaluation module 3400 includes a comparison sub-module 3410, a judgment sub-module 3420, a correction sub-module 3430, and an output sub-module 3440;
the comparing sub-module 3410 is configured to compare the in-transit data with the transit condition information to obtain a preliminary evaluation result;
the judging submodule 3420 is used for judging whether the preliminary evaluation result meets a preset transportation condition or not;
the correction submodule 3430 is used for analyzing factors which are not met when the preset transportation conditions are not met, so as to obtain a correction result;
the output sub-module 3440 is configured to correct the preliminary evaluation result according to the correction result, and obtain and output the transportation evaluation result.
Specifically, the preliminary evaluation result is that an information difference result is obtained after comparing the in-transit data with the transit condition information. The preset transportation condition is a preset difference value, and if the information difference between the data in transportation and the transportation condition information is within the difference value range, the transportation enterprise is proved to be in accordance with the requirement in the transportation process.
Specifically, when the preset transportation condition is not met, analyzing the unsatisfied factors, and pertinently adjusting the unsatisfied factors until the preset transportation condition is met, and then obtaining a correction result. And the transportation evaluation result is that the transportation process is evaluated and graded, and different grades correspond to different supervision schemes. Therefore, the aim of matching different supervision schemes according to different transportation evaluation grades is fulfilled, and the technical effects of improving supervision efficiency and reducing supervision cost are achieved.
Further, as shown in fig. 5, the correction submodule 3430 further includes:
the adjusting component 3431 is arranged in the correction submodule 3430, is connected with the intelligent compartment system and is used for giving a command for adjusting an intelligent assembly structure in the compartment;
a selection component 3432, wherein the selection component 3432 is configured to select the corresponding intelligent assembly structure according to the unsatisfied factors;
a feedback component 3433, wherein the feedback component 3433 is connected with the adjusting component 3431 and feeds back the adjusted structural condition to the adjusting component 3431;
and a determining component 3434, where the determining component 3434 is configured to determine that the adjusted transportation condition is met, and output the correction result.
Specifically, the intelligent car system is a system for adjusting the intelligent car. The intelligent carriage is provided with an adjustable structure, and the carriage structure and the environment can be adjusted according to different transportation conditions so as to adapt to different transportation requirements. The intelligent assembly structure is a structure which is arranged on a carriage and can be freely combined.
Preferably, the intelligent assembly structure can be a moisture barrier, a damping layer and the like.
Specifically, according to the unsatisfied factors, the selection component 3432 obtains which adjustments to be performed on the intelligent compartment are required to make the factors meet the transportation conditions, selects the corresponding intelligent assembly structure, and performs structural adjustment. And the feedback component 3433 feeds back the adjusted carriage structure condition to the adjustment component 3431, and after the adjustment component acquires the adjustment information, the information is input into the judgment component 3434 to judge whether the preset transportation condition is met, and if so, the correction result is output. Therefore, the intelligent regulation of the carriage structure is realized to meet different transportation conditions, and the technical effect of improving the intelligent supervision efficiency is achieved.
For example, if the factor that is not met is that the humidity is too high, it is stated that the climate environment of the area that is experienced during transportation is wet at a price, resulting in too high humidity in the transportation compartment. And the excessive humidity can cause feed deterioration, so the moisture-proof layer in the intelligent assembly structure can be selected through the selection component 3432, and the technical effect of adjusting the humidity in the transportation carriage can be achieved by additionally arranging the moisture-proof layer on the carriage.
Illustratively, the vibration amplitude is too large and the road is relatively bumpy by the selecting component 3432 according to the unsatisfied factors, and the vibration damping layer in the corresponding intelligent assembly structure is selected, so that the degree of the road bumpy is slowed down. Through intelligent shock absorption layer additional in the transport carriage reaches the amplitude in the adjustment transport carriage, improves the technical effect of transportation stability.
The data transceiver module 3100 is configured to receive information from the information collecting device and send the transportation evaluation result to a cloud supervision system platform;
and after receiving the transportation evaluation result, the cloud supervision system platform matches a corresponding supervision scheme from a database.
Specifically, different supervision schemes are stored in a database of the cloud supervision system platform, the grade corresponding to the transportation condition is obtained according to the transportation evaluation result, and the corresponding supervision schemes are matched according to the different grades. Therefore, the technical effect of improving the supervision efficiency is achieved.
In order to solve the technical problem, the application also provides an intelligent supervision method of a third-party feed transportation enterprise, and the intelligent supervision system for the third-party feed transportation enterprise is adopted, wherein the method comprises the following steps:
step 1, setting a cloud supervision system platform, wherein the cloud supervision system platform is in communication connection with a plurality of transportation information acquisition devices and a plurality of transportation monitoring devices which are respectively and independently installed on different transportation vehicles and is used for intelligently supervising a third-party feed transportation enterprise;
step 2, acquiring speed data of a transport vehicle, temperature and humidity data of the transport vehicle and state information of feed in real time through a transport information acquisition device, and uploading the acquired transport data to a transport monitoring device, wherein the transport information acquisition device is provided with a temperature and humidity sensor, a speed sensor, a GPS positioning module, a time node module, a communication module and an image acquisition module;
step 3, dynamically monitoring the transportation data through a transportation monitoring device, wherein the transportation data comprises four components: the system comprises a data receiving and transmitting module, a data preprocessing module, a data analysis module and a transportation evaluation module;
step 4, preprocessing the received transportation data through the data preprocessing module to obtain preprocessed data;
step 5, analyzing the preprocessed data through the data analysis module to obtain transportation condition information;
step 6, comparing the in-transit data with the transit condition information through the transit evaluation module to obtain a transit evaluation result;
step 7, receiving information from the information acquisition device through the data transceiver module and sending the transportation evaluation result to a cloud supervision system platform;
and 8, after receiving the transportation evaluation result, the cloud supervision system platform matches a corresponding supervision scheme from a database.
The above method may implement the content of the system of the present application, which is not described herein again.
In summary, the intelligent supervision method for the third-party feed transportation enterprise provided by the application has the following technical effects:
1. through high in the clouds supervisory systems platform and transportation information acquisition device and transportation monitoring devices communication connection for carry out intelligent supervision to third party fodder transportation enterprise, transportation information acquisition device is used for gathering transportation data in real time, transportation monitoring devices is used for right transportation data carries out dynamic monitoring, includes four subassemblies: the cloud supervision system platform is matched with a corresponding supervision scheme from a database after receiving the transportation evaluation result. The intelligent supervision of the third-party feed transportation enterprises is achieved, and the technical effects of improving supervision efficiency and reducing transportation cost are achieved.
2. And comparing the in-transportation data with the transportation condition information through the transportation evaluation module 3400 to obtain a transportation evaluation result. And when the preset transportation conditions are not met, analyzing the factors which are not met, and carrying out targeted adjustment on the factors which are not met until the preset transportation conditions are met, so as to obtain a correction result. And the transportation evaluation result is that the transportation process is evaluated and graded, and different grades correspond to different supervision schemes. Therefore, the aim of matching different supervision schemes according to different transportation evaluation grades is fulfilled, and the technical effects of improving supervision efficiency and reducing supervision cost are achieved.
3. According to the method, the selection component 3432 obtains which adjustment needs to be carried out on the intelligent carriage in order to enable the factors to meet the transportation conditions according to the unsatisfied factors, and selects the corresponding intelligent assembly structure to carry out structural adjustment. And the feedback component 3433 feeds back the adjusted carriage structure condition to the adjustment component 3431, and after the adjustment component acquires the adjustment information, the information is input into the judgment component 3434 to judge whether the preset transportation condition is met, and if so, the correction result is output. Therefore, the intelligent regulation of the carriage structure is realized to meet different transportation conditions, and the technical effect of improving the intelligent supervision efficiency is achieved.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (6)
1. An intelligent supervisory system for a third party feed transportation enterprise, the system comprising:
the cloud supervision system platform is in communication connection with a plurality of transportation information acquisition devices and a plurality of transportation monitoring devices which are respectively and independently installed on different transportation vehicles and is used for intelligently supervising a third-party feed transportation enterprise;
the transportation information acquisition device is used for acquiring speed data of the transportation vehicle, temperature and humidity data of the transportation vehicle and state information of feed in real time, and uploading the acquired transportation data to the transportation monitoring device, and is provided with a temperature and humidity sensor, a speed sensor, a GPS positioning module, a time node module, a communication module and an image acquisition module;
the transportation monitoring device is used for dynamically monitoring the transportation data and comprises four components: the system comprises a data receiving and transmitting module, a data preprocessing module, a data analysis module and a transportation evaluation module;
the data preprocessing module is arranged behind the data receiving and transmitting module and is used for preprocessing the received transportation data to obtain preprocessed data;
the data analysis module is arranged behind the data preprocessing module and is used for analyzing the preprocessed data to obtain transportation condition information;
the transportation evaluation module is arranged behind the data analysis module and is used for comparing the data in transportation with the transportation condition information to obtain a transportation evaluation result;
the data transceiver module is used for receiving information from the information acquisition device and sending the transportation evaluation result to the cloud supervision system platform;
after receiving the transportation evaluation result, the cloud supervision system platform matches a corresponding supervision scheme from a database;
the data analysis module comprises:
the data analysis module determines condition information in the transportation process by analyzing the preprocessed data, wherein the data analysis module comprises: the system comprises an information acquisition sub-module, a weight distribution sub-module, a weight calculation sub-module and a condition matching sub-module;
the information acquisition sub-module is used for acquiring historical transportation condition information;
the weight distribution sub-module is arranged behind the information acquisition sub-module and is used for distributing weights of loading data, in-transit data and receiving data according to historical transportation condition information to obtain a weight distribution result;
the weight calculation sub-module is arranged behind the weight distribution sub-module and is used for carrying out weight calculation on the loading data, the in-transport data and the receiving data according to the weight distribution result to obtain a calculation result;
the condition matching sub-module is arranged behind the weight calculation sub-module and is used for matching corresponding transportation conditions in the sub-module according to the calculation result to obtain the transportation condition information.
2. The system of claim 1, wherein the data preprocessing module comprises:
the data preprocessing module comprises a time sequence processing sub-module and a clustering processing sub-module;
the time-sequence processing submodule is used for performing time-sequence processing on the obtained transportation data to obtain time-sequence processing data;
the clustering processing sub-module is arranged behind the time sequence processing sub-module and is used for processing and clustering the time sequence processing data to obtain the preprocessing data.
3. The system of claim 2, wherein the cluster processing submodule includes:
the clustering processing sub-module comprises an attribute extraction component and a clustering component;
the attribute extraction component is used for extracting the attribute of the time-sequence processing data to obtain an attribute data set;
the clustering component is arranged behind the attribute extraction component and is used for clustering the data in the attribute data set to obtain the preprocessing data, and the preprocessing data is divided into three groups of data, including: loading data, in-transit data, and receiving data.
4. The system of claim 1, the transport assessment module comprising:
the transportation evaluation module comprises a comparison sub-module, a judgment sub-module, a correction sub-module and an output sub-module;
the comparison sub-module is used for comparing the in-transportation data with the transportation condition information to obtain a preliminary evaluation result;
the judging submodule is used for judging whether the preliminary evaluation result meets a preset transportation condition or not;
the correction submodule is used for analyzing factors which are not met when the preset transportation conditions are not met, and obtaining a correction result;
and the output sub-module is used for correcting the preliminary evaluation result according to the correction result to obtain and output the transportation evaluation result.
5. The system of claim 4, wherein the correction submodule includes:
the adjusting component is arranged in the correcting sub-module, is connected with the intelligent carriage system and is used for issuing a command for adjusting an intelligent assembly structure in the carriage;
the selection component is used for selecting the corresponding intelligent assembly structure according to unsatisfied factors;
the feedback component is connected with the adjusting component and feeds back the adjusted structural condition to the adjusting component;
and the judging component is used for judging that the preset transportation condition is met after adjustment and outputting the correction result.
6. An intelligent supervision method for a third party feed transportation enterprise, wherein the method is applied to an intelligent supervision system for a third party feed transportation enterprise as set forth in any one of claims 1-5, the method comprising:
the method comprises the steps of setting a cloud supervision system platform, wherein the cloud supervision system platform is in communication connection with a plurality of transportation information acquisition devices and a plurality of transportation monitoring devices which are respectively and independently installed on different transportation vehicles and is used for intelligently supervising a third-party feed transportation enterprise;
the method comprises the steps of acquiring speed data of a transport vehicle, temperature and humidity data of the transport vehicle and state information of feed in real time through a transport information acquisition device, and uploading the acquired transport data to a transport monitoring device, wherein the transport information acquisition device is provided with a temperature and humidity sensor, a speed sensor, a GPS positioning module, a time node module, a communication module and an image acquisition module;
carrying out dynamic monitoring on the transportation data through a transportation monitoring device, and comprising four components: the system comprises a data receiving and transmitting module, a data preprocessing module, a data analysis module and a transportation evaluation module;
preprocessing the received transportation data through the data preprocessing module to obtain preprocessed data;
analyzing the preprocessed data through the data analysis module to obtain transportation condition information;
comparing the in-transit data with the transit condition information through the transit evaluation module to obtain a transit evaluation result;
receiving information from an information acquisition device through the data transceiver module and sending the transportation evaluation result to a cloud supervision system platform;
after receiving the transportation evaluation result, the cloud supervision system platform matches a corresponding supervision scheme from a database;
analyzing the preprocessed data by the data analysis module to obtain transportation condition information, including:
analyzing the preprocessed data by the data analysis module to determine condition information during transportation, wherein the data analysis module comprises: the system comprises an information acquisition sub-module, a weight distribution sub-module, a weight calculation sub-module and a condition matching sub-module;
acquiring historical transportation condition information through the information acquisition sub-module;
the weight distribution submodule distributes weights of the loading data, the in-transit data and the receiving data according to historical transportation condition information to obtain a weight distribution result;
the weighting calculation sub-module is used for carrying out weighting calculation on the loading data, the in-transit data and the receiving data according to the weight distribution result to obtain a calculation result;
and matching corresponding transportation conditions in the sub-module according to the calculation result by the condition matching sub-module to obtain the transportation condition information.
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