Product oil retail system

Abstract

The invention relates to the technical field of product oil retail, and provides a product oil retail system, which comprises an on-site service terminal deployed in a gas station site, a gas station management node arranged locally, a cloud data server connected remotely and a user mobile terminal, the field service terminal integrates an oiling machine, a payment terminal and a vehicle identification and environment monitoring module, executes oiling operation and collects data; the gas station management node gathers and processes data to realize inventory, sales and safety monitoring; the cloud data server aggregates multi-station data and is equipped with an energy efficiency evaluation module, a replenishment decision module, a data analysis module and a member management module. The system has the advantages that by constructing the field service terminal, the gas station management node and the cloud data server, the problem of data islands existing in a traditional system is effectively solved, and inventory dynamic early warning, accurate sales prediction, multi-mode payment, member management and three-dimensional safety monitoring are achieved; and the operation efficiency, the energy utilization rate and the user experience are remarkably improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of finished oil retail, in particular to a finished oil retail system. BACKGROUND

[0002] As the core link of energy supply chain, the operation efficiency and service quality of finished oil retail industry directly determine the market competitiveness and user satisfaction of enterprises. The gas station management system widely used in the current industry has significant defects, mainly manifested as the scattered operation architecture leading to isolated data of each site, and the information cannot be real-time interchanged and shared, forming a serious data island. This isolated state makes it difficult to realize cross-regional data aggregation and comprehensive analysis, thereby hindering the scientificity and timeliness of overall operation decision. In the inventory management link, most systems rely on manual experience or simple local calculation, lack real-time monitoring mechanism, and cannot dynamically warn inventory risks, which easily leads to stockout or resource waste; in the sales prediction aspect, the traditional method is only based on limited historical data or subjective judgment, and the accuracy is insufficient, which is difficult to support accurate replenishment plan making; in the energy efficiency evaluation field, due to the lack of systematic energy consumption monitoring and analysis tools, the gas station cannot effectively quantify the energy consumption per unit of sales, leading to low energy use efficiency; and in the member service, due to the independent operation of each site, the integral rules and promotion activities are not unified, which seriously weakens the user stickiness and experience coherence.

[0003] The payment mode of the existing system is limited to basic electronic payment or cash transaction, and cannot support diversified and convenient payment demand such as non-inductive payment or NFC interaction; the environmental safety monitoring equipment is simple, and the combustible gas concentration detection, fire warning and video monitoring capability are weak, and it is difficult to identify potential safety hazards in time; the remote service support function is missing, and users cannot realize operations such as reservation refueling and real-time inquiry through mobile terminals; in the advanced application scenarios such as multi-site collaborative operation, supply chain optimization and energy consumption management, the industry has not established a unified intelligent management platform, resulting in unbalanced resource allocation, high operating cost and delayed service response, etc., which cannot meet the urgent needs of modern retail scenarios for intelligent and integrated management. SUMMARY

[0004] Therefore, the embodiments of the present application aim to provide a finished oil retail system to solve or alleviate the technical problems in the prior art.

[0005] The technical scheme of the embodiments of the present application is implemented as follows: a finished oil retail system, comprising: a field service terminal deployed at a gas station site, used for performing refueling operation, completing transaction and collecting various types of field data; the field service terminal comprises a refueling machine, a payment terminal, a vehicle identification module and an environmental monitoring module; The gas station management node is located locally at the gas station and communicates with the field service terminal. It is used to collect and process data from the field service terminal to realize the station's inventory management, sales statistics and safety monitoring. The cloud-based data server connects remotely to multiple gas station management nodes via a communication network to aggregate and analyze gas station operation data across regions and provide centralized data services. The user's mobile terminal has an application installed, which interacts with the cloud data server and gas station management nodes to realize remote service functions; The cloud data server also includes: The energy efficiency assessment module is used to calculate energy efficiency indicators based on the energy consumption and sales data of each gas station. The replenishment decision module is used to generate intelligent replenishment suggestions based on inventory and sales dynamics; A data analytics engine used to predict sales trends based on historical data; The membership management module is used to uniformly manage membership information, points, and promotional activities for all networked gas stations.

[0006] Furthermore, this application also proposes that when the gas station management node manages the gas station's inventory in real time, an alarm will be triggered when the inventory is insufficient, and the instruction will be determined by the following formula:

[0007] in, This represents the real-time inventory level of the oil tank. This represents the average daily sales volume. For safe days.

[0008] Furthermore, this application also proposes that the data analysis engine predicts sales based on historical data using the following formula:

[0009] in, For the first Actual daily sales For the first Daily sales forecast It is the smoothing coefficient, and .

[0010] Furthermore, this application also proposes that the membership management module calculates points based on the user's spending amount, with points awarded for each transaction. The calculation method is as follows:

[0011] in, This refers to the points redemption rate. The actual amount paid for the transaction. This is the floor function.

[0012] Furthermore, this application also proposes an energy efficiency assessment module for calculating the energy consumption per unit sales volume of a gas station to assess its operational energy efficiency, using the following formula:

[0013] in, Energy consumption per unit of sales The total energy consumption within a specified period. This represents the total sales volume within the corresponding period.

[0014] Furthermore, this application also proposes a replenishment decision module that generates suggested replenishment quantities. The calculation formula is:

[0015] in, This is the maximum capacity of the oil tank. This represents the current inventory level. The estimated delivery time for oil products.

[0016] Furthermore, this application also proposes that the cloud data server is also communicatively connected to an operations monitoring center for real-time monitoring and management of the operational status, equipment status, and safety status of all networked gas stations.

[0017] Furthermore, this application also proposes that the payment terminal supports multiple payment methods, including bank card payment, QR code payment, NFC payment, and contactless payment based on the user's mobile terminal.

[0018] Furthermore, this application also proposes that the environmental monitoring module includes an oil and gas concentration sensor for monitoring the concentration of combustible gases, a smoke alarm for fire early warning, and video surveillance equipment for recording on-site conditions.

[0019] Furthermore, this application also proposes that the gas station management node is also equipped with a local data caching unit, which is used to temporarily store local data when the network is interrupted, and automatically synchronize the data to the cloud data service after the network is restored.

[0020] The beneficial effects of this invention are as follows: by constructing an integrated operation architecture that coordinates on-site service terminals, gas station management nodes, and cloud data servers, the problem of data silos in traditional systems is effectively solved; intelligent algorithms are used to achieve dynamic inventory early warning and accurate replenishment; sales forecasting based on historical data improves the scientific nature of decision-making; unified membership management enhances user stickiness; integration of multiple payment methods significantly improves transaction efficiency and user experience; a comprehensive environmental monitoring system ensures operational safety; local data caching units ensure business continuity under network anomalies; and the operation monitoring center realizes centralized management of cross-regional sites. Attached Figure Description

[0021] Figure 1 This is a diagram of a refined oil retail system architecture according to the present invention; Figure 2 This is a timing diagram of refueling operations in a refined oil retail system according to the present invention; Figure 3 This is a cloud data server architecture diagram for a refined oil retail system according to the present invention. Detailed Implementation

[0022] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0023] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0024] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0025] This invention provides a refined oil retail system, comprising: a field service terminal deployed at a gas station for performing refueling operations, completing transactions, and collecting various types of field data; the field service terminal includes a fuel dispenser, a payment terminal, a vehicle identification module, and an environmental monitoring module; The gas station management node is located locally at the gas station and communicates with the field service terminal. It is used to collect and process data from the field service terminal to realize the station's inventory management, sales statistics and safety monitoring. The cloud-based data server connects remotely to multiple gas station management nodes via a communication network to aggregate and analyze gas station operation data across regions and provide centralized data services. The user's mobile terminal has an application installed, which interacts with the cloud data server and gas station management nodes to realize remote service functions; The cloud data server also includes: The energy efficiency assessment module is used to calculate energy efficiency indicators based on the energy consumption and sales data of each gas station. The replenishment decision module is used to generate intelligent replenishment suggestions based on inventory and sales dynamics; A data analytics engine used to predict sales trends based on historical data; The membership management module is used to uniformly manage membership information, points, and promotional activities for all networked gas stations.

[0026] During implementation, when the gas station management node manages the gas station's inventory in real time, an alarm will be triggered when the inventory is insufficient. The instruction is determined using the following formula:

[0027] in, This represents the real-time inventory level of the oil tank. This represents the average daily sales volume. For safe days.

[0028] Specifically, This refers to the average daily sales volume, which can be calculated using the arithmetic average based on historical sales data. For example, by periodically summarizing the sales records of the past few days and calculating the average value, the purpose is to dynamically reflect the recent sales fluctuation pattern and avoid the problem of threshold rigidity caused by sales peaks or troughs. This can be understood as the number of safe days, which can be determined based on the gas station's supply chain characteristics and replenishment history data.

[0029] In practice, the data analytics engine uses historical data to predict sales using the following formula:

[0030] in, For the first Actual daily sales For the first Daily sales forecast It is the smoothing coefficient, and .

[0031] Specifically, the current predicted sales volume Ft refers to the sales volume forecast value generated by the system at time t. It can be calculated using a weighted average based on historical data, with the aim of providing a dynamic estimate of future sales. The actual sales volume At-1 of the previous day can be understood as the real sales data recorded at time t-1. It can be obtained through real-time sales records collected by the gas station management node, with the aim of reflecting the latest market dynamics. The predicted sales volume Ft-1 of the previous day refers to the forecast value generated by the system at time t-1. It can be calculated iteratively based on earlier historical data, with the aim of maintaining the continuity and trend stability of the forecast. The smoothing coefficient α can be understood as an adjustment parameter between 0 and 1. It can be manually set through the user configuration interface or automatically adjusted based on the sales model algorithm, with the aim of dynamically controlling the contribution ratio of new and old data, so that the forecast model can adapt to the fluctuation characteristics of different sales scenarios.

[0032] In implementation, the membership management module calculates points based on the user's spending amount, with points awarded for each transaction. The calculation method is as follows:

[0033] in, This refers to the points redemption rate. The actual amount paid for the transaction. This is the floor function.

[0034] The points redemption ratio R refers to the system's preset conversion ratio between points and consumption amount. It can be implemented using a fixed constant or dynamically adjusted according to promotional strategies, aiming to ensure the standardization of points calculation and the configurability of business rules. The actual payment amount A refers to the monetary amount actually paid by the user when completing the transaction. It can be directly extracted from the transaction data obtained from the payment terminal, aiming to ensure that points calculation is strictly based on the actual data of the current consumption. The floor function ⌊⋅⌋ is a mathematical function that rounds a real number down to the largest integer not greater than that number. It can be implemented through software algorithms, aiming to eliminate the decimal part of the points value and avoid system storage, transmission, and display obstacles caused by decimal processing.

[0035] During implementation, the energy efficiency assessment module is used to calculate the energy consumption per unit of sales at gas stations to evaluate their operational energy efficiency. The calculation formula is as follows:

[0036] in, Energy consumption per unit of sales The total energy consumption within a specified period. This represents the total sales volume within the corresponding period.

[0037] Specifically, the energy efficiency assessment module refers to the core component used to quantitatively assess the energy efficiency of gas stations, which can be achieved through a combination of data processing units and storage media; unit sales energy consumption refers to the amount of energy consumed per unit volume of oil sold, which can be calculated in a standardized manner based on the ratio of total energy consumption to total sales volume; specifically, The total energy consumption within a specified period can include the sum of energy consumption such as electricity and fuel. The total sales volume within the corresponding period can be derived from the sales data recording system of the field service terminal.

[0038] During implementation, the replenishment decision module generates a suggested replenishment quantity. The calculation formula is:

[0039] in, This is the maximum capacity of the oil tank. This represents the current inventory level. The estimated delivery time for oil products.

[0040] Specifically, the recommended replenishment quantity Q refers to the volume of oil that the system recommends replenishing. This can be achieved through dynamic calculation based on real-time data, aiming to ensure that the replenishment quantity meets future demand without exceeding physical capacity limitations; the maximum capacity of the oil tank... This refers to the maximum storage volume allowed by the design of the oil tank. It can be achieved using preset fixed parameters or automatically obtained based on the oil tank model. The purpose is to prevent the risk of overflow due to over-replenishment; current inventory level. This refers to the real-time available volume of oil in the tank, which can be obtained through real-time monitoring using level sensors or periodic manual entry, aiming to reflect the actual on-site inventory status; average daily sales. This refers to the average daily sales volume calculated based on historical sales data. It can be calculated using a sliding window average or weighted historical data, with the aim of scientifically predicting future sales demand and estimated delivery cycle. This refers to the estimated time from order placement to delivery of the oil. It can be determined by using historical delivery time statistics or by combining real-time traffic data forecasts, with the aim of covering sales consumption during the delivery period.

[0041] During implementation, the cloud data server is also connected to the operations monitoring center to monitor and manage the operational status, equipment status, and safety status of all networked gas stations in real time.

[0042] The operation monitoring center refers to a centralized monitoring entity, which can be implemented using server clusters or dedicated monitoring software systems. Its purpose is to conduct unified real-time monitoring of the status of multiple gas stations, thereby promptly detecting anomalies and proactively intervening.

[0043] Specifically, the cloud data server transmits aggregated cross-regional operational data to the operations monitoring center in real time. Based on this data, the monitoring center dynamically analyzes operational indicators such as sales trends and inventory changes, and performs fault diagnosis by combining the equipment operating parameters of the field service terminals. At the same time, it integrates combustible gas concentration and fire early warning data from the environmental monitoring module to identify safety risks. Once an anomaly is detected, a linkage response mechanism is immediately triggered, avoiding decision-making delays caused by relying solely on local nodes to report at each level.

[0044] During implementation, the payment terminal supports multiple payment methods, including bank card payment, QR code payment, NFC payment, and contactless payment based on the user's mobile terminal.

[0045] Among them, bank card payment refers to the method of completing transaction verification using financial cards, which can be implemented using magnetic stripe cards, chip cards, or contactless bank cards. The purpose is to provide widely compatible payment options based on existing financial infrastructure and avoid transaction interruptions caused by incompatibility of payment tools. QR code payment refers to the method of completing fund transfer by parsing dynamically generated QR codes through optical recognition technology. It can be implemented using QR codes generated by mobile devices or QR codes displayed on the terminal. The purpose is to reduce the steps of users manually entering information and make the payment process more in line with mobile operating habits. NFC payment refers to the method of contactless security authentication based on near-field communication technology. It can be implemented using smartphones with NFC function or dedicated radio frequency tags. The purpose is to eliminate the need for physical card insertion and removal, and improve transaction speed and security. Seamless payment based on user mobile terminals refers to the method of completing payment without active operation after the system automatically confirms the user's identity and vehicle information. It can be implemented through background authentication of mobile applications or triggering in conjunction with vehicle recognition modules. The purpose is to eliminate the need for manual intervention and achieve a truly seamless payment experience.

[0046] Specifically, the solution proposed in this application integrates a multimodal payment interface into the payment terminal, forming an organic whole among various payment methods: When a user performs a refueling operation, the payment terminal dynamically calls the corresponding payment module to process the transaction request based on the user's selection or the system's preset strategy. The bank card payment module transmits card information to the payment gateway through an encrypted channel to complete authorization; the QR code payment module generates or scans a dynamic QR code in real time to trigger fund settlement; the NFC payment module activates radio frequency signals for short-range security authentication; and the contactless payment module works in conjunction with the vehicle recognition module, completing the payment process in the mobile terminal backend after the user's identity and vehicle information are automatically confirmed by the system. This multi-path parallel payment architecture ensures seamless switching between payment methods in different scenarios, avoids transaction interruptions caused by the failure of a single payment method, and optimizes the user interaction sequence through modular design, making the payment process closely integrated with the refueling operation.

[0047] In practice, the environmental monitoring module includes an oil and gas concentration sensor for monitoring the concentration of combustible gases, a smoke alarm for fire early warning, and video surveillance equipment for recording the situation on site.

[0048] Among them, the oil and gas concentration sensor refers to the device used to monitor the concentration of combustible gas in the gas station environment in real time. It can be implemented using a catalytic combustion sensor or an infrared optical sensor. Its purpose is to accurately identify the potential explosion risk caused by oil and gas volatilization. The smoke alarm can be understood as a fire early warning device based on smoke particle detection. It can be implemented using a photoelectric or ionization smoke detector. Its purpose is to quickly trigger an alarm when a fire hazard first appears to prevent the fire from spreading. The video surveillance equipment is specifically a device used to continuously record the scene. It can be implemented using a high-definition network camera or an infrared night vision camera. Its purpose is to provide real-time visual monitoring and post-event retrospective analysis.

[0049] Specifically, the solution in this application continuously monitors the concentration of combustible gases using an oil and gas concentration sensor, issuing an early warning signal when the concentration exceeds a safety threshold. Simultaneously, a smoke detector monitors smoke particles in the environment in real time, triggering an alarm immediately upon the initial appearance of a fire hazard. Video surveillance equipment records dynamic images of the scene and transmits the data to an environmental monitoring module for comprehensive processing. These components work together to form a complete monitoring chain from risk perception and early warning to event recording, achieving three-dimensional and real-time monitoring of the gas station's safety environment.

[0050] During implementation, the gas station management node is also equipped with a local data caching unit, which is used to temporarily store local data when the network is interrupted and automatically synchronize the data to the cloud data service after the network is restored.

[0051] The local data cache unit refers to a temporary storage medium, which can be implemented using solid-state drives, dynamic random access memory, or flash memory. Its purpose is to reliably save critical operational data during network communication anomalies and prevent data loss. This unit is configured as a localized storage component independent of the cloud data server. It can receive and temporarily store transaction records, inventory status, and environmental monitoring data from field service terminals. Its introduction ensures the integrity and traceability of data under unstable communication link conditions.

[0052] Specifically, the solution proposed in this application integrates a gas station management node with a local data caching unit. When the network connection is interrupted, this unit immediately takes over the data flow, temporarily storing the refueling operations, payment information, and environmental monitoring data uploaded by the on-site service terminal in the local storage area. At the same time, the unit continuously monitors the network status, and once communication is detected to be restored, it automatically triggers a data synchronization mechanism to upload the temporarily stored data to the cloud data server in a complete time sequence without manual intervention. During this process, the gas station management node, as the data processing hub, forms a closed-loop management system with the local data caching unit, ensuring the continuous operation of core functions such as inventory warning, sales statistics, and safety monitoring under abnormal network conditions, thereby maintaining the real-time performance and consistency of the system data.

[0053] In practice: When a vehicle enters the gas station, the vehicle identification module automatically captures the vehicle's identification information and matches it with the user profile in the membership management module. The user selects the fuel type and quantity through the fuel dispenser at the on-site service terminal and begins the refueling process. The fuel dispenser collects data such as refueling volume, time, and amount in real time and transmits it to the gas station management node. Simultaneously, the payment terminal activates the corresponding payment module based on the user's selection: if the user chooses bank card payment, the payment terminal completes authorization with the bank gateway through encrypted communication; if the user chooses QR code payment, the terminal generates a dynamic QR code for the user to scan, or scans the payment code on the user's mobile terminal; if the user chooses NFC payment, the terminal performs near-field communication verification with the user's device; if contactless payment is enabled, the system automatically associates the user's account based on the vehicle identification result and deducts the payment from the pre-linked payment channel after refueling is completed. All transaction data is recorded and uploaded to the gas station management node in real time.

[0054] The gas station management node aggregates data from multiple field service terminals, including sales records, inventory status, and environmental monitoring information. Regarding inventory management, the node continuously monitors the real-time inventory level V in the tanks and uses the formula:

[0055] Assess inventory risk. When certain conditions are met, the system triggers an inventory alert and calculates the recommended replenishment quantity using the replenishment decision module. The formula is as follows:

[0056] A smart replenishment order is generated and sent to the supplier. Simultaneously, the data analytics engine, based on historical sales data, uses the following formula:

[0057] The module predicts future sales, optimizes inventory planning and promotional strategies, and periodically calculates energy consumption per unit of sales using the following formula:

[0058] Generate energy efficiency reports for operators' reference. After each transaction is completed, the member management module uses the following formula:

[0059] The system calculates user points and updates the points balance and spending history in member accounts. Users can remotely check their points, participate in promotional activities, or book refueling via an application on their mobile devices. The environmental monitoring module monitors the concentration of combustible gases in real time using oil and gas concentration sensors, and issues audible and visual alarms if the concentration exceeds a safety threshold. Smoke detectors detect fire hazards, and video surveillance equipment records the scene. All safety data is transmitted to the gas station management node and cloud data server.

[0060] When network communication is interrupted, the local data caching unit of the gas station management node temporarily stores all local data and continuously monitors the network status. Once the network is restored, the caching unit automatically synchronizes the backlogged data to the cloud data server to ensure data integrity. After the cloud data server aggregates the data from each gas station, the operations monitoring center analyzes cross-regional operational indicators, equipment status, and safety events in real time, achieving centralized monitoring and rapid response. Through the above implementation process, the system achieves seamless integration from on-site operations to cloud management, improving the automation level and operational efficiency of refined oil retail.

[0061] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A refined oil retail system, characterized in that, include: On-site service terminals are deployed at gas stations to perform refueling operations, complete transactions, and collect various types of on-site data. The on-site service terminal includes a fuel dispenser, a payment terminal, a vehicle identification module, and an environmental monitoring module; The gas station management node is located locally at the gas station and is connected to the field service terminal for communication. It is used to collect and process data from the field service terminal to realize the station's inventory management, sales statistics and safety monitoring. A cloud-based data server, remotely connected to multiple gas station management nodes via a communication network, is used to aggregate and analyze cross-regional gas station operation data and provide centralized data services. The user's mobile terminal has an application installed, which interacts with the cloud data server and the gas station management node to realize remote service functions; The cloud data server also includes: The energy efficiency assessment module is used to calculate energy efficiency indicators based on the energy consumption and sales data of each gas station. The replenishment decision module is used to generate intelligent replenishment suggestions based on inventory and sales dynamics; A data analytics engine used to predict sales trends based on historical data; The membership management module is used to uniformly manage membership information, points, and promotional activities for all networked gas stations.

2. The refined oil retail system according to claim 1, characterized in that, When the gas station management node manages the gas station's inventory in real time, an alarm will be triggered when the inventory is insufficient. The instruction is determined by the following formula: ； in, This represents the real-time inventory level of the oil tank. This represents the average daily sales volume. For safe days.

3. The refined oil retail system according to claim 1, characterized in that, The data analysis engine predicts sales based on historical data using the following formula: ； in, For the first Actual daily sales For the first Daily sales forecast It is the smoothing coefficient, and .

4. The refined oil retail system according to claim 1, characterized in that, The membership management module calculates points based on the user's spending amount, with points awarded for each transaction. The calculation method is as follows: ； in, This refers to the points redemption rate. The actual amount paid for the transaction. This is the floor function.

5. A refined oil retail system according to claim 1, characterized in that, The energy efficiency assessment module is used to calculate the energy consumption per unit sales volume of a gas station to assess its operational energy efficiency. The calculation formula is as follows: ； in, Energy consumption per unit of sales The total energy consumption within a specified period. This represents the total sales volume within the corresponding period.

6. The refined oil retail system according to claim 1, characterized in that, The replenishment decision module generates the suggested replenishment quantity. The calculation formula is: ； in, This is the maximum capacity of the oil tank. This represents the current inventory level. The estimated delivery time for oil products.

7. A refined oil retail system according to claim 1, characterized in that, The cloud data server is also connected to an operations monitoring center, which is used to monitor and manage the operational status, equipment status, and safety status of all networked gas stations in real time.

8. A refined oil retail system according to claim 1, characterized in that, The payment terminal supports multiple payment methods, including bank card payment, QR code payment, NFC payment, and contactless payment based on the user's mobile terminal.

9. A refined oil retail system according to claim 1, characterized in that, The environmental monitoring module includes an oil and gas concentration sensor for monitoring the concentration of combustible gases, a smoke alarm for fire early warning, and video monitoring equipment for recording on-site conditions.

10. A refined oil retail system according to claim 1, characterized in that, The gas station management node is also equipped with a local data caching unit, which is used to temporarily store local data when the network is interrupted, and automatically synchronize the data to the cloud data service after the network is restored.

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