Product oil circulation supervision method and system based on cloud-edge joint calculation

Abstract

The invention discloses a product oil circulation supervision method and system based on cloud-edge joint calculation. The method comprises the following steps: generating corresponding real-time information according to a refueling action identified by edge equipment; wherein the number of the real-time information is multiple; obtaining sales data of the product oil, and associating the sales data based on the real-time information; matching metering data acquired from a cloud end with the sales data to realize combination and association of circulation and sales links; the method has the beneficial effects that the real-time information is associated with the sales data; and finally, matching the metering data acquired from the cloud with the sales data to realize combination and association of circulation and sales links. Therefore, the defect in the prior art that data are mutually independent and circulation and sales links are difficult to combine so as to form more complete supervision is overcome.

Description

Technical Field

[0001] The present invention relates to the technical field of refined oil trading, and in particular to a refined oil circulation supervision method and system based on cloud-edge joint computing. Background Art

[0002] Finished oil is the most important energy source for logistics and transportation in today's society, and gas stations have become an important place for the circulation of finished oil. However, in actual applications, as the scale of the gas station industry continues to expand, the operating entities of gas stations are complex and the management is uneven, especially the low level of informatization, which makes it impossible to achieve real-time monitoring and intelligent management, and it is difficult to meet the needs of modern finished oil circulation management; by strengthening the monitoring and management of finished oil at gas stations, the operating behavior of gas stations can be standardized and the healthy development of the gas station industry can be promoted.

[0003] There are now some plans for using the Internet of Things for supervision. Although they have improved the level of informatization, when applied in supervision, there is a defect that the uploaded data are independent of each other, making it difficult to combine the circulation and sales links to form a more complete supervision. Summary of the invention

[0004] In view of the technical defects mentioned in the background technology, the purpose of the embodiments of the present invention is to provide a method and system for finished oil circulation supervision based on cloud-edge joint computing.

[0005] To achieve the above objectives, in a first aspect, an embodiment of the present invention provides a method for monitoring the circulation of refined oil products based on cloud-edge joint computing, the method comprising:

[0006] Generate corresponding real-time information according to the refueling action identified by the edge device; wherein the number of the real-time information is multiple;

[0007] Acquire sales data of refined oil products, and associate the sales data with the real-time information;

[0008] The metering data obtained from the cloud is matched with the sales data to achieve the combined association between circulation and sales links.

[0009] As a preferred implementation of the present application, the generating of corresponding real-time information according to the identified refueling action specifically includes:

[0010] Based on the refueling process, the refueling actions are divided into vehicle entry, refueling start, refueling period, refueling end and vehicle exit;

[0011] According to each refueling action, real-time information associated with the corresponding action is generated; wherein the real-time information includes a corresponding time mark, a fuel gun mark and a vehicle mark.

[0012] As a preferred implementation of the present application, the sales data includes corresponding time information, fuel gun information, label information and fuel quantity information;

[0013] The real-time information is associated with the sales data, specifically including: firstly making a judgment based on the comparison between the time and the oil gun, if the comparison time between the two is within a preset time range and the oil gun matches, then associating the real-time information with the sales data; otherwise, putting the real-time information and the sales data into a pre-built exception database.

[0014] As a preferred implementation of the present application, when matching the metering data with the sales data, processing is performed through a preset text matching model, specifically including:

[0015] Obtaining semantic representations of the metering data and the sales data, and comparing them;

[0016] In the comparison process, the semantics of the two sentences are extracted respectively, and then the semantics of the two sentences are encoded and modeled in the same vector space;

[0017] Finally, the calculated similarity is used to determine whether the match is successful.

[0018] As a preferred implementation of the present application, the method further includes:

[0019] Based on the real-time information, the vehicle data of the corresponding gas station is counted and classified;

[0020] And based on the sales data, oil product sales analysis is performed, and based on the analysis results, refined oil sales volume forecast is performed.

[0021] In a second aspect, an embodiment of the present invention further provides a refined oil circulation supervision system based on cloud-edge joint computing, the system comprising:

[0022] An identification module, used to generate corresponding real-time information according to the refueling action identified by the edge device; wherein the number of the real-time information is multiple;

[0023] an association module, for obtaining sales data of refined oil products and associating the sales data with the real-time information;

[0024] The processing module is used to match the metering data obtained from the cloud with the sales data to achieve the combined association between circulation and sales links.

[0025] The technical solution provided by the embodiment of the present invention first generates corresponding real-time information according to the refueling action recognized by the edge device; then obtains the sales data of the refined oil and associates the real-time information with the sales data; finally, matches the metering data obtained from the cloud with the sales data to realize the combination and association of circulation and sales links; thereby overcoming the defects of the prior art that the data are independent of each other and it is difficult to combine the circulation and sales links to form a more complete supervision. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the specific implementation of the present invention or the technical solution in the prior art, the drawings required for use in the specific implementation or the description of the prior art are briefly introduced below.

[0027] Figure 1 It is a flow chart of a method for monitoring the circulation of refined oil products based on cloud-edge joint computing provided by an embodiment of the present invention;

[0028] Figure 2 It is a principle block diagram of a refined oil circulation supervision system based on cloud-edge joint computing provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0029] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so as to describe the embodiments of the present application described herein.

[0031] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0032] Throughout the specification, references to "one embodiment," "an embodiment," "an example," or "an example" mean that a particular feature, structure, or characteristic described in conjunction with the embodiment or example is included in at least one embodiment of the present invention. Therefore, the phrases "in one embodiment," "in an embodiment," "an example," or "an example" appearing in various places throughout the specification do not necessarily all refer to the same embodiment or example. Furthermore, particular features, structures, or characteristics may be combined in one or more embodiments or examples in any appropriate combinations and / or subcombinations.

[0033] It should be noted that, unless otherwise specified, the technical terms in this embodiment have the common meanings understood in the relevant technical field.

[0034] Please refer to Figure 1 , an embodiment of the present invention provides a method for monitoring the circulation of refined oil products based on cloud-edge joint computing, the method comprising:

[0035] Generate corresponding real-time information according to the refueling action identified by the edge device; wherein the number of the real-time information is multiple;

[0036] Acquire sales data of refined oil products, and associate the sales data with the real-time information;

[0037] The metering data obtained from the cloud is matched with the sales data to achieve the combined association between circulation and sales links.

[0038] In this embodiment, the application scenario of a gas station is taken as an example; the edge device includes network equipment, smart cameras and sensors deployed in the gas station, which will not be elaborated here; the cloud comes from data from the Metrology Association; the above scheme is used to realize cloud-edge joint computing processing.

[0039] In this embodiment, the corresponding refueling action is obtained through image recognition, and the extracted features are classified using a machine learning or deep learning model to identify objects in the image or to identify specific objects in the image.

[0040] The generating corresponding real-time information according to the identified refueling action specifically includes:

[0041] Based on the refueling process, the refueling actions are divided into vehicle entry, refueling start, refueling period, refueling end and vehicle exit;

[0042] According to each refueling action, real-time information associated with the corresponding action is generated; wherein the real-time information includes a corresponding time mark, a fuel gun mark and a vehicle mark; and may also include corresponding camera information.

[0043] When in use, the system identifies the lifting of the gun, connection of the oil gun and release of the gun at the beginning, during and end of refueling, thereby achieving more accurate recognition of the refueling action.

[0044] The sales data includes corresponding time information, fuel gun information, label information and fuel quantity information;

[0045] The real-time information is associated with the sales data, specifically including: firstly making a judgment based on the comparison between the time and the oil gun, if the comparison time between the two is within a preset time range and the oil gun matches, then associating the real-time information with the sales data; otherwise, putting the real-time information and the sales data into a pre-built exception database.

[0046] The above settings make the supervision of refined oil more real-time and detailed. It should be noted that the vehicle identification includes the corresponding license plate information, including the vehicle type, such as motorcycles, cars, tricycles, etc., which makes the specific flow of refined oil clearer.

[0047] Meanwhile, when associating, the association may be based on at least one amount of real-time information, or may be based on multiple real-time information, and there is no limitation here;

[0048] Furthermore, during implementation, when matching the metering data with the sales data, the matching is performed through a preset text matching model, specifically including:

[0049] Obtaining semantic representations of the metering data and the sales data, and comparing them;

[0050] In the comparison process, the semantics of the two sentences are extracted respectively, and then the semantics of the two sentences are encoded and modeled in the same vector space;

[0051] Finally, the calculated similarity is used to determine whether the match is successful.

[0052] When applied, the text matching model uses ABCNN for text matching, thereby improving the matching accuracy and efficiency.

[0053] The above scheme first generates corresponding real-time information based on the refueling action recognized by the edge device; then obtains the sales data of refined oil and associates the real-time information with the sales data; finally, matches the metering data obtained from the cloud with the sales data to achieve the combination and association of circulation and sales links; thereby overcoming the defects of the prior art that the data are independent of each other and it is difficult to combine the circulation and sales links to form a more complete supervision.

[0054] Furthermore, based on the above technical solution, in order to realize the extended application of data, in another embodiment, the method further includes:

[0055] Based on the real-time information, the vehicle data of the corresponding gas station is counted and classified;

[0056] And based on the sales data, oil product sales analysis is performed, and based on the analysis results, refined oil sales volume forecast is performed.

[0057] When applied, the LSTM model is used as the basic model for prediction. Its application is mature and will not be described here. The difference is that the influencing parameters are introduced for training; wherein, the influencing parameters include price adjustment data, holiday data and weather characteristics;

[0058] This allows the predictive data output by the model to provide effective feedback on relevant influencing factors, thereby improving the accuracy of the prediction and the comprehensiveness of supervision.

[0059] Reference Figure 2 Based on the same inventive concept, an embodiment of the present invention further provides a refined oil circulation supervision system based on cloud-edge joint computing, the system comprising:

[0060] An identification module, used to generate corresponding real-time information according to the refueling action identified by the edge device; wherein the number of the real-time information is multiple;

[0061] an association module, for obtaining sales data of refined oil products and associating the sales data with the real-time information;

[0062] The processing module is used to match the metering data obtained from the cloud with the sales data to achieve the combined association between circulation and sales links.

[0063] Furthermore, the generating of corresponding real-time information according to the identified refueling action specifically includes:

[0064] Based on the refueling process, the refueling actions are divided into vehicle entry, refueling start, refueling period, refueling end and vehicle exit;

[0065] According to each refueling action, real-time information associated with the corresponding action is generated; wherein the real-time information includes a corresponding time mark, a fuel gun mark and a vehicle mark.

[0066] The sales data includes corresponding time information, fuel gun information, label information and fuel quantity information;

[0067] The real-time information is associated with the sales data, specifically including: firstly making a judgment based on the comparison between the time and the oil gun, if the comparison time between the two is within a preset time range and the oil gun matches, then associating the real-time information with the sales data; otherwise, putting the real-time information and the sales data into a pre-built exception database.

[0068] In this embodiment, when matching the metering data with the sales data, the matching is performed through a preset text matching model, specifically including:

[0069] Obtaining semantic representations of the metering data and the sales data, and comparing them;

[0070] In the comparison process, the semantics of the two sentences are extracted respectively, and then the semantics of the two sentences are encoded and modeled in the same vector space;

[0071] Finally, the calculated similarity is used to determine whether the match is successful.

[0072] It should be noted that for a more specific description of the workflow of the system embodiment, please refer to the aforementioned method embodiment part, which will not be repeated here.

[0073] The entire solution first generates corresponding real-time information based on the refueling action recognized by the edge device; then obtains the sales data of refined oil and associates the real-time information with the sales data; finally, matches the metering data obtained from the cloud with the sales data to achieve the combination and association of circulation and sales links; thereby overcoming the defects of the existing technology that the data are independent of each other and it is difficult to combine the circulation and sales links to form a more complete supervision.

[0074] Further, in another embodiment, based on the above solution, the processing module is further used for:

[0075] Based on the real-time information, the vehicle data of the corresponding gas station is counted and classified;

[0076] And based on the sales data, oil product sales analysis is performed, and based on the analysis results, refined oil sales volume forecast is performed.

[0077] When applied, the LSTM model is used as the basic model for prediction. Its application is mature and will not be described here. The difference is that the influencing parameters are introduced for training; wherein, the influencing parameters include price adjustment data, holiday data and weather characteristics;

[0078] This allows the predictive data output by the model to provide effective feedback on relevant influencing factors, thereby improving the accuracy of the prediction and the comprehensiveness of supervision.

[0079] In several embodiments provided in the present application, it should be understood that the disclosed system and method can also be implemented in other ways. The system embodiment described above is only schematic, for example, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0080] In addition, the functional modules in the various embodiments of the present invention can be integrated together to form an independent part, or each module can exist separately, or two or more modules can be integrated to form an independent part. When in use, each module only collects and stores user information with the full authorization of the user and in compliance with relevant laws and regulations, and protects the security and privacy of user data, and unauthorized access is strictly prohibited; data processing will be carried out within the scope prescribed by law and shall not exceed the purpose and scope authorized by the user; at the same time, users enjoy relevant rights such as access, correction, deletion, restriction of processing, and rejection of their personal data; and strictly abide by applicable laws and regulations and conduct compliance reviews.

[0081] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. It should be noted that, in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various changes and variations. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

[0082] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for monitoring the circulation of refined oil products based on cloud-edge joint computing, characterized in that: The method comprises: Generate corresponding real-time information according to the refueling action identified by the edge device; wherein the number of the real-time information is multiple; Acquire sales data of refined oil products, and associate the sales data with the real-time information; The metering data obtained from the cloud is matched with the sales data to achieve the combined association between circulation and sales links.

2. A method for monitoring the circulation of refined oil products based on cloud-edge joint computing as claimed in claim 1, characterized in that: The generating corresponding real-time information according to the identified refueling action specifically includes: Based on the refueling process, the refueling actions are divided into vehicle entry, refueling start, refueling period, refueling end and vehicle exit; According to each refueling action, real-time information associated with the corresponding action is generated; wherein the real-time information includes a corresponding time mark, a fuel gun mark and a vehicle mark.

3. A method for monitoring the circulation of refined oil products based on cloud-edge joint computing as claimed in claim 2, characterized in that: The sales data includes corresponding time information, fuel gun information, label information and fuel quantity information; The real-time information is associated with the sales data, specifically including: firstly making a judgment based on the comparison between the time and the oil gun, if the comparison time between the two is within a preset time range and the oil gun matches, then associating the real-time information with the sales data; otherwise, putting the real-time information and the sales data into a pre-built exception database.

4. A method for monitoring the circulation of refined oil products based on cloud-edge joint computing as claimed in claim 3, characterized in that: When matching the metering data with the sales data, the process is performed through a preset text matching model, specifically including: Obtaining semantic representations of the metering data and the sales data, and comparing them; In the comparison process, the semantics of the two sentences are extracted respectively, and then the semantics of the two sentences are encoded and modeled in the same vector space; Finally, the calculated similarity is used to determine whether the match is successful.

5. A method for monitoring the circulation of refined oil products based on cloud-edge joint computing as claimed in claim 3, characterized in that: The method further comprises: Based on the real-time information, the vehicle data of the corresponding gas station is counted and classified; And based on the sales data, oil product sales analysis is performed, and based on the analysis results, refined oil sales volume forecast is performed.

6. A refined oil circulation supervision system based on cloud-edge joint computing, characterized in that: The system comprises: An identification module, used to generate corresponding real-time information according to the refueling action identified by the edge device; wherein the number of the real-time information is multiple; an association module, for obtaining sales data of refined oil products and associating the sales data with the real-time information; The processing module is used to match the metering data obtained from the cloud with the sales data to achieve the combined association between circulation and sales links.

7. A refined oil circulation monitoring system based on cloud-edge joint computing as claimed in claim 6, characterized in that: The generating corresponding real-time information according to the identified refueling action specifically includes: Based on the refueling process, the refueling actions are divided into vehicle entry, refueling start, refueling period, refueling end and vehicle exit; According to each refueling action, real-time information associated with the corresponding action is generated; wherein the real-time information includes a corresponding time mark, a fuel gun mark and a vehicle mark.

8. A refined oil circulation monitoring system based on cloud-edge joint computing as claimed in claim 7, characterized in that: The sales data includes corresponding time information, fuel gun information, label information and fuel quantity information; The real-time information is associated with the sales data, specifically including: firstly making a judgment based on the comparison between the time and the oil gun, if the comparison time between the two is within a preset time range and the oil gun matches, then associating the real-time information with the sales data; otherwise, putting the real-time information and the sales data into a pre-built exception database.

9. A refined oil circulation monitoring system based on cloud-edge joint computing as claimed in claim 8, characterized in that: When matching the metering data with the sales data, the process is performed through a preset text matching model, specifically including: Obtaining semantic representations of the metering data and the sales data, and comparing them; In the comparison process, the semantics of the two sentences are extracted respectively, and then the semantics of the two sentences are encoded and modeled in the same vector space; Finally, the calculated similarity is used to determine whether the match is successful.

10. A refined oil circulation monitoring system based on cloud-edge joint computing as claimed in claim 9, characterized in that: The processing module is also used for: Based on the real-time information, the vehicle data of the corresponding gas station is counted and classified; And based on the sales data, oil product sales analysis is performed, and based on the analysis results, refined oil sales volume forecast is performed.

Images