Intelligent uncooked seafood and seafood unmanned transportation and sale system

Abstract

The invention discloses an intelligent uncooked seafood and seafood unmanned transportation and selling system, and relates to the field of unmanned automatic selling and distribution of commodities, and the system comprises an unmanned transportation and selling device which comprises a storage module, a positioning module, a display module, a driving module and a background management module; products are placed in a warehouse of the unmanned transportation and sale device and are classified and placed through the storage modules, information of the storage modules is monitored through the display module, the positioning module is used for determining the specific position of the unmanned transportation truck and uploading the position to the background management module in real time, and the driving module comprises a battery management unit and an obstacle avoidance unit. When the unmanned transportation and sale device encounters an obstacle, obstacle avoidance processing is carried out in time, and processing route data is uploaded to the background management module; in addition to goods transportation and circulation, the mobile goods selling vehicle can also be used as a mobile goods selling vehicle, and a novel commercial mode in which selling and logistics are combined and intercommunicated is created.

Description

Technical Field

[0001] The present invention relates to the technical field of logistics distribution, and in particular to a smart raw seafood and seafood unmanned transportation and sales system. Background Art

[0002] For the entire logistics industry, it is an irresistible trend to replace humans with machines. Currently, fully automated transportation operations have been achieved at the fourth phase of Yangshan Port in Shanghai. Next is to achieve full automation in the road transportation link. However, there is currently no system that can theoretically achieve this goal.

[0003] The transportation of raw and seafood products occupies a certain market share in the logistics industry. The automation of logistics for raw and seafood products has also become an urgent need. However, due to the particularity of the packaging and transportation of raw and seafood products, such as specific requirements for temperature, humidity, oxygen supply, anti-pollution performance, sealing performance, as well as refrigeration, freezing or constant temperature requirements, etc., the automated transportation equipment for raw and seafood products needs to have its particularity. Currently, the existing transportation equipment fails to meet the requirements of this field.

[0004] At the present stage, there is an urgent need for a technology for the automated transportation of raw and seafood products to solve the problems of reducing labor costs and realizing digital logistics information transmission. Summary of the Invention

[0005] The embodiments of the present application provide a smart raw seafood and seafood unmanned transportation and sales system, thereby solving the problem of reducing labor costs and realizing digital logistics information transmission in the case of transporting and storing seafood and raw food in related technologies.

[0006] Among them, according to one aspect of the embodiments of the present application, a smart raw seafood and seafood unmanned transportation and sales system is provided, including: an unmanned transportation and sales device and a background management module. The unmanned transportation and sales device includes a storage module, a positioning module, a display and monitoring module, an image acquisition module, and a driving module; The storage module classifies and places products in different areas according to the type information of the products. The storage module includes a refrigeration system, a humidification system, and a control system. The control system is used to control the refrigeration system and the humidification system to work according to the type information of the products. The refrigeration system is used to perform sub-thermal insulation treatment on frozen products. The storage module includes a water supply system and an oxygen supply system for storing and raising seafood. The storage module also includes a load-bearing module, an automatic fishing device, and a packaging module. The load-bearing module is used to protect the storage module. The automatic fishing device, the fishing device includes a fishing net. If the product purchased by the consumer is seafood, the background management module issues an instruction to the fishing device. The fishing device catches the seafood through the fishing net and weighs the seafood at the same time. The fishing device can also be used for fishing and weighing live river seafood and river seafood. The packaging module is used to automatically package the fished products; The positioning module is used to determine the position information of the unmanned vending device and upload the position information to the background management module in real time; The display and monitoring module is used to monitor the temperature and humidity in different areas of the storage module, upload the monitoring information to the background management module, and the background management module adjusts the temperature and humidity of this area according to the type information of the products through the control module. The display and monitoring module includes an automatic vending module for displaying purchase steps, payment method instructions, automatic vending, and change; The image acquisition module is used for face recognition and real-time monitoring of road conditions. When a consumer approaches the unmanned vending device, it automatically performs face recognition on the consumer and uploads the recognition information and road condition information to the background management module; The drive module includes a battery management unit, an ECU, an obstacle avoidance module, and a data analysis unit. The battery management unit is used to provide power for the unmanned vending device and monitor and protect the battery through sensors. The ECU includes an obstacle avoidance system. The data analysis unit uses the Kalman filter algorithm to fuse the information obtained by the sensors to quickly and accurately analyze and process the road conditions and judge the working state of the engine. The prediction stage of the Kalman filter algorithm: Among them, is the prior state estimation vector at time k; x k-1 is the posterior state estimation vector at time k-1; A is the state transition matrix; u k-1 is the control input vector at time k-1; is the prior estimation covariance matrix at time k; Pk-1 is the posterior estimation covariance matrix at time k-1; Q is the process noise covariance matrix; Update stage: where K k is the Kalman gain; z k is the measurement vector at time k; C is the measurement matrix; R is the measurement noise covariance matrix; x k is the posterior state estimation vector at time k; P k is the posterior estimation covariance matrix at time k; The background management module is used to save and organize all data transmitted by the storage module, positioning module, display and monitoring module, image acquisition module and driving module, and perform optimization and adjustment according to the data.

[0007] Furthermore, for the intelligent raw seafood and seafood unmanned vending system, different areas of the storage module adopt partitioned storage cells for further classification of products. Each storage cell is equipped with a pressure sensor to calculate the weight and type of products selected by consumers and upload the data to the background management module. A threshold is set for the weight in the storage cell, and when the weight in the storage cell is less than the threshold, the background management module issues a replenishment instruction.

[0008] Furthermore, for the intelligent raw seafood and seafood unmanned vending system, the oxygen supply system is used for oxygen data monitoring and automatic adjustment of the oxygen supply amount, and the water supply system is used to monitor the water level in some storage modules and automatically supply water when the water level in the some storage modules is lower than the set threshold.

[0009] Furthermore, for the intelligent raw seafood and seafood unmanned vending system, the display and monitoring module includes a vending unit for displaying QR codes. Consumers can purchase products by scanning the QR codes with their mobile terminals to download the intelligent raw seafood and seafood unmanned vending vehicle APP, using mini-programs, searching for the intelligent raw seafood and seafood unmanned vending vehicle on cooperative third-party platforms, and clicking on the local display screen. The background management module will obtain the real-name information of consumers, as well as the parameter information and quantity information of the purchased products. Consumers can pay for the purchase funds through the APP, mini-programs, WeChat, Alipay, and other payment platforms on their mobile terminals. The mobile terminal will send a payment request to the corresponding payment platform. The payment platform will verify the information of the consumer's account balance and payment password, and then return a message indicating whether the payment is successful or failed to the background management module. The background management module will decide whether to ship the goods based on the feedback result, and at the same time collect transportation fees and seafood purchase fees. The unmanned vending device also includes an automatic vending unit. If the background management system issues a shipping instruction, the automatic vending unit will convey the goods to the shipping outlet through a conveyor belt. The automatic vending unit can automatically vend by package, piece, or strip. Consumers can directly pick up the products from the shipping outlet. The display and monitoring module also has a voice interaction module for realizing human-machine communication through voice interaction during use. The voice interaction module provides an operation interface for consumers. Consumers can select products through the operation interface. The operation interface has a customer service window. If consumers encounter problems that the system cannot solve, they can contact the staff through the customer service window.

[0010] Furthermore, for the intelligent raw seafood and seafood unmanned vending system, the image acquisition unit includes an image enhancement unit. The image enhancement unit obtains the grayscale component image in the original image. Through a CPLD processor, according to the relative brightness relationship between the pixel points of the grayscale component image and the pixel points of the grayscale component image after Gaussian smoothing, the pixel points of the grayscale component image are corrected for grayscale values, and the grayscale component image after grayscale value correction is synthesized to obtain an enhanced image.

[0011] Furthermore, for the intelligent raw seafood and seafood unmanned vending system, the obstacle avoidance system uses a millimeter-wave radar to detect the distance, speed, and angle of obstacles using electromagnetic waves in the millimeter-wave band. The millimeter waves emitted by the millimeter-wave radar will be reflected back after encountering obstacles. By receiving the reflected waves and analyzing the data information of their frequency changes, the relative speed of the obstacles is calculated, and timely processing is carried out, and the processing route is uploaded to the background management module.

[0012] Furthermore, for the intelligent raw seafood and seafood unmanned vending system, the obstacle avoidance system makes avoidance decisions according to pre-set rules. A threshold X is set. When the radar detects a pedestrian ahead and the pedestrian is on the vehicle's driving path, the unmanned vending device will decelerate or stop according to regulations and wait for the pedestrian to pass before continuing to drive. The formula for judging whether to adopt the above decision is: , wherein, is the time to collision; is the speed of the unmanned vending device; is the distance to the obstacle; is the speed of the obstacle relative to the vehicle; If is less than the set threshold X, the unmanned vending device takes emergency braking or avoidance measures.

[0013] Furthermore, for the intelligent raw seafood and seafood unmanned vending system, the battery management unit is used to detect the voltage, current and temperature of the battery. The battery management unit can control the charging process of the battery, select a suitable charging method according to the type and status of the battery, and immediately stop charging when the battery voltage exceeds the set maximum value or the temperature is too high.

[0014] Furthermore, for the intelligent raw seafood and seafood unmanned vending system, the background management module plans the transportation route through the location module and the location information of the consumer's mobile phone, and identifies and collects the data information of traffic lights and zebra crossings on the collection route through the image acquisition module. If the data processing module determines that the unmanned vending device will run a red light, it controls the vehicle through the ECU; the data processing module is also connected to the cloud computing system. The data processing module can send the judgment result of whether the vehicle will run a red light to the cloud computing system, and the cloud computing system can feedback command instructions to the data processing module to control the vehicle through the data processing module connected to the ECU. In addition, the background management module also obtains weather data as the driving standard for vehicle driving data.

[0015] Furthermore, for the intelligent raw seafood and seafood unmanned vending system, the background management module also includes a learning library. The learning library continuously learns through the deep learning framework to improve the accuracy of the designed transportation route. The learning library adopts machine learning algorithms such as neural networks and support vector machines to continuously optimize the system design and consumer experience.

[0016] Furthermore, the display monitoring module supports face recognition + fingerprint + ID card scanning code + phone number verification.

[0017] Furthermore, when the consumer needs to open the storage module, the storage module is locked and unlocked through an electromagnetic lock.

[0018] Furthermore, the driving module further includes a cab. When the system encounters an emergency on the road that it cannot solve, the staff can switch from autonomous driving to active driving.

[0019] Compared with the prior art, the beneficial effects of the present invention are as follows: This system can achieve unmanned automatic retail, realize a new type of unmanned vending mode, and provide automatic door-to-door supply and selection of items for purchase. It can promote the sales share and sales method of fast-moving consumer goods in the market, and more importantly, it has created a new intelligent mobile sales mode in addition to online sales and offline physical sales. It fully combines the direct relationships among e-commerce, offline sales, physical stores, consumers, couriers or deliverymen, vehicles, etc. and realizes full mobilization, reduces labor costs, realizes digital logistics information transmission, and promotes the maximization and unmanned utilization rate of various resources.

[0020] Next, through the drawings and embodiments, the technical solutions of the present application will be further described in detail. Description of the Drawings

[0021] The drawings forming a part of the specification depict the embodiments of the present application and, together with the description, are used to explain the principles of the present application.

[0022] Referring to the drawings, the present application can be more clearly understood according to the following detailed description, where: Figure 1 is a structural block diagram of a smart raw seafood and seafood unmanned transportation and vending system proposed by the present application; Figure 2 is a structural block diagram of a storage module of a smart raw seafood and seafood unmanned transportation and vending system proposed by the present application; Figure 3 is a structural block diagram of a driving module of a smart raw seafood and seafood unmanned transportation and vending system proposed by the present application. Detailed Embodiments

[0023] Now, various exemplary embodiments of the present application will be described in detail with reference to the drawings. It should be noted that: Unless otherwise specifically stated, the relative arrangements, numerical expressions, and numerical values of the components and steps set forth in these embodiments do not limit the scope of the present application.

[0024] At the same time, it should be understood that for the sake of description, the dimensions of the various parts shown in the drawings are not drawn in actual proportional relationships.

[0025] The following description of at least one exemplary embodiment is actually merely illustrative and does not constitute any limitation to the present application and its application or use.

[0026] Known technologies, methods, and devices that are well-known to those of ordinary skill in the relevant art may not be discussed in detail, but in appropriate cases, such technologies, methods, and devices should be regarded as part of the specification.

[0027] It should be noted that like reference numerals and letters denote like items in the following figures, and thus, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0028] In addition, the technical solutions between various embodiments of the present application can be combined with each other, but it must be based on the ability of those of ordinary skill in the art to implement. When the combination of technical solutions results in contradictions or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by the present application.

[0029] It should be noted that all directional indications (such as up, down, left, right, front, back...) in the embodiments of the present application are only used to explain the relative position relationship and movement conditions between components in a certain specific posture (as shown in the drawings). If the specific posture changes, the directional indications will also change accordingly.

[0030] The following is combined with Figure 1 to describe a smart raw seafood and seafood unmanned vending system according to an exemplary embodiment of the present application. It should be noted that the following application scenarios are only shown for the convenience of understanding the spirit and principle of the present application, and the embodiments of the present application are not limited in this regard. On the contrary, the embodiments of the present application can be applied to any applicable scenario.

[0031] The present application provides a smart raw seafood and seafood unmanned vending system.

[0032] Figure 1 - Figure 3 Schematically shows a structural block diagram of a smart raw seafood and seafood unmanned vending system according to an embodiment of the present application. As Figure 1 - Figure 3 shown, the solution includes: The unmanned vending device includes a storage module, a positioning module, a display and monitoring module, an image acquisition module, a driving module, and a background management module; The storage module classifies and places products in different areas according to the type information of the products. The storage module includes a refrigeration system, a humidification system, and a control system. The control system is used to control the refrigeration system and the humidification system to work according to the type information of the products. The storage module also includes a water supply system and an oxygen supply system for storing and raising seafood; The positioning module is used to determine the position information of the unmanned vending device and upload the position information to the background management module in real time; The display and monitoring module is used to monitor the temperature and humidity in different areas of the storage module, and upload the monitoring information to the background management module. The background management module adjusts the temperature and humidity in this area according to the product type information through the control module. The display and monitoring module is also used to display the purchase steps, payment method instructions, and change; The image acquisition module is used for face recognition and real-time monitoring of road conditions information, and uploads the information to the background management module; The drive module includes a battery management unit, an ECU, and a data analysis unit. The battery management unit is used to provide power for the unmanned vending device and monitor and protect the battery through sensors. The ECU includes an obstacle avoidance system. The data analysis unit uses the Kalman filter algorithm to fuse the information obtained by the sensors to quickly and accurately analyze and process the road conditions, and judge the working state of the engine. Kalman filter algorithm prediction stage: , Among them, is The prior state estimation vector at time; is The posterior state estimation vector at time; is the state transition matrix; is The control input vector at time; is The prior estimation covariance matrix at time; is The posterior estimation covariance matrix at time; is the process noise covariance matrix; Update stage: , Among them, is the Kalman gain; is The measurement vector at time; is the measurement matrix; is the measurement noise covariance matrix; is The posterior state estimation vector at time; is The posterior estimation covariance matrix at time; The background management module is used to save and organize all the data transmitted by the storage module, positioning module, display and monitoring module, image acquisition module, and driving module, and perform optimization and adjustment based on the data.

[0033] Specifically, first, the power system of the vehicle is detected. If it is an electric unmanned vending vehicle, the battery power, charging interface, and whether the battery management system can effectively monitor the battery status need to be checked. Secondly, for some products that need to be refrigerated or insulated, it is necessary to ensure that the refrigeration or insulation equipment of the vehicle can work properly, and at the same time, the vehicle system is detected to ensure that the vehicle can perform stable data transmission with the background management system. Finally, after the product is sold, the sales information, including the product type, quantity, sales time, etc., is recorded and these data are sent to the background management module for inventory management and sales statistics, etc.

[0034] It can be understood that the unmanned vending vehicle does not require human resources such as drivers and salespersons and can operate continuously for 24 hours. The unmanned vending vehicle is not restricted by working hours. Whether it is day or night, as long as there is a demand, the unmanned vending vehicle can respond at any time to meet the needs of consumers to shop at any time, maximizing sales opportunities and service efficiency, saving a large amount of human resources, and thus reducing operating costs. Specifically, the storage module uses partitioned storage cells in different areas to further classify products. Each storage cell is equipped with a pressure sensor to calculate the weight and type of products selected by consumers and upload the data to the background management module. A threshold is set for the weight in the storage cell, and when the weight in the storage cell is less than the threshold, the background management module issues a replenishment instruction.

[0035] It can be understood that the storage cell can store different types and specifications of seafood and raw food in an orderly manner, facilitating consumers to view and select. It is a relatively enclosed space with good sealing performance to prevent cross - contamination between different types of seafood and is also convenient for inventory management.

[0036] Specifically, the oxygen supply system is used for oxygen data monitoring and automatically adjusting the oxygen supply amount, and the water supply system is used for monitoring the water level in some storage modules and automatically supplying water when the water level in some storage modules is lower than the set threshold.

[0037] Specifically, the display and monitoring module is also used to display a QR code. After a consumer scans it with a payment application on their mobile phone, the mobile application will send a payment request to the corresponding payment platform. The payment platform will verify information such as the consumer's account balance and payment password, and then return a message indicating whether the payment is successful or failed to the background management module. The background management module decides whether to ship the goods based on the feedback result. The unmanned vending device also includes an automatic vending unit. If the background management system issues a shipping instruction, the automatic vending unit will convey the goods to the shipping outlet through a conveyor belt, and the consumer can directly pick up the product from the shipping outlet. The display and monitoring module is also equipped with a voice interaction module for realizing human-machine communication through voice interaction during use. The voice interaction module provides an operation interface for the consumer. The consumer can select products through the operation interface. The operation interface is provided with a customer service window. If the consumer encounters a problem that the system cannot solve, they can contact the staff through the customer service window.

[0038] It can be understood that the display and monitoring module can clearly display detailed information about seafood, such as species, price, origin, and shelf life, etc., enabling consumers to fully understand the product situation when purchasing. This information transparency helps consumers make informed purchasing decisions. Consumers can judge the quality and flavor of seafood based on the origin information and choose the freshest products according to the shelf life, thereby enhancing their satisfaction with the purchase.

[0039] Specifically, the image acquisition unit includes an image enhancement unit. The image enhancement unit obtains the grayscale component image in the original image. Through a CPLD processor, according to the relative brightness relationship between the pixel points of the grayscale component image and the pixel points of the grayscale component image after Gaussian smoothing, the pixel points of the grayscale component image are corrected for grayscale values, and the grayscale component images after grayscale value correction are synthesized to obtain an enhanced image.

[0040] Specifically, the obstacle avoidance system uses a millimeter-wave radar to detect the distance, speed, and angle of obstacles using electromagnetic waves in the millimeter-wave band. The millimeter waves emitted by the millimeter-wave radar will be reflected back after encountering obstacles. By receiving the reflected waves and analyzing the data information of their frequency changes, the relative speed of the obstacles is calculated, and timely processing is carried out, and the processed route is uploaded to the background management module.

[0041] It can be understood that the automatic obstacle avoidance system makes it more flexible and safe when adjusting its position. The operator can more conveniently optimize the layout of the unmanned vending device according to factors such as the number of people and sales data, without worrying about causing damage to the surrounding environment and the device itself during the movement process. This helps to better exert the commercial value of the unmanned vending device and improve the sales efficiency.

[0042] Specifically, the obstacle avoidance system makes avoidance decisions according to pre-set rules. A threshold value X is set. When the radar detects a pedestrian in front and the pedestrian is on the vehicle's driving path, the unmanned vending device will decelerate or stop as required and wait for the pedestrian to pass before continuing to drive. The formula for determining whether to adopt the above decision is: , wherein, is the time to collision; is the speed of the unmanned vending device; is the distance to the obstacle; is the speed of the obstacle relative to the vehicle; If is less than the set threshold value X, the unmanned vending device takes emergency braking or avoidance measures.

[0043] Specifically, the battery management unit is used to detect the voltage, current and temperature of the battery. The battery management unit can control the charging process of the battery and select a suitable charging method according to the type and state of the battery. When the battery voltage exceeds the set maximum value or the temperature is too high, the charging will be stopped immediately.

[0044] Specifically, the battery management module can precisely control the charging process of the battery. In the initial stage of charging, it charges with a constant current to avoid damage to the battery caused by excessive charging current. When the battery voltage reaches a certain value, it switches to constant voltage charging to gradually charge the battery, and can effectively prevent overcharging in the later stage of charging. This precise charging control method can greatly extend the cycle life of the battery, enabling the battery to experience more charge and discharge cycles.

[0045] It can be understood that the battery management module can improve the energy conversion efficiency of the battery. During the charging process, by optimizing the control of the charging current and voltage, it reduces the energy loss during charging; during the discharging process, it ensures that the battery can supply power to the device with a stable voltage and current, avoiding energy waste caused by the decline of battery performance, thereby improving the energy efficiency of the entire system.

[0046] Specifically, the background management module plans the transportation route through the location information of the positioning module and the consumer's mobile phone, and identifies and collects the data information of traffic lights and zebra crossings on the collection route through the image acquisition module. If the data processing module determines that the unmanned vending device will run a red light, it controls the vehicle through the ECU; the data processing module is also connected to the cloud computing system. The data processing module can send the judgment result of whether the vehicle will run a red light to the cloud computing system, and the cloud computing system can feedback command instructions to the data processing module to control the vehicle through the data processing module connected to the ECU.

[0047] Specifically, the background management module can monitor the operating status of devices in real time with each system of the unmanned vending device. For the refrigeration part of the seafood vending machine, the background can obtain temperature data and send an alarm in a timely manner to notify the operator when the temperature exceeds the normal range. This helps to quickly detect equipment failures or abnormal conditions, take corresponding measures for repair, reduce equipment downtime, and ensure the normal operation of the unmanned vending device. The operator can remotely control and update the configuration of the unmanned vending device through the background, and can adjust parameters such as the price of the unmanned vending device, update the advertising content, and set the refrigeration temperature without having to go to the site. This remote operation function greatly improves the convenience of operation and management. Especially when the unmanned vending devices are distributed in multiple different locations, it can save a large amount of time and labor costs.

[0048] Specifically, the background management module also includes a learning library. The learning library continuously learns through a deep learning framework to improve the accuracy of designing transportation routes. The learning library adopts machine learning algorithms such as neural networks and support vector machines to continuously optimize system design and consumer experience.

[0049] Specifically, the operator can obtain the latest market operation knowledge through the learning library, which helps the operator optimize the layout of the unmanned vending device, the selection of commodity types, and marketing strategies, and improve operation efficiency.

[0050] Those skilled in the art will readily conceive of other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any variations, uses, or adaptations of the present application, which follow the general principles of the present application and include known common knowledge or conventional technical means in the technical field not disclosed in the present application. The specification and examples are only regarded as exemplary, and the true scope and spirit of the present application are pointed out by the following claims.

[0051] It should be understood that the present application is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present application is only limited by the appended claims.

Claims

1. A smart raw seafood and seafood unmanned transportation and sales system, characterized in that: include: An unmanned transport and sales device and a background management module, wherein the unmanned transport and sales device includes a storage module, a positioning module, a display monitoring module, an image acquisition module and a driving module; The storage module is used to place products in different areas according to the product type information. The storage module includes a refrigeration system, a humidification system and a control system. The control system is used to control the operation of the refrigeration system and the humidification system according to the product type information. The refrigeration system is used to perform heat preservation treatment on frozen products. The storage module includes a water supply system and an oxygen supply system for storing seafood. The storage module also includes a load-bearing module, an automatic salvaging device and a packaging module. The load-bearing module is used to protect the storage module. The automatic salvaging device includes a salvaging net. If the product purchased by the consumer is seafood, the background management module issues an instruction to the salvaging device. The salvaging device catches the seafood through the salvaging net and weighs the seafood at the same time. The salvaging device can also be used to catch and weigh live river seafood and river seafood. The packaging module is used to automatically package the salvaged products. The positioning module is used to determine the location information of the unmanned transportation and vending device and upload the location information to the background management module in real time; The display monitoring module is used to monitor the temperature and humidity of different areas of the storage module, and upload the monitoring information to the background management module. The background management module adjusts the temperature and humidity of the area according to the product type information through the control module. The display monitoring module includes an automatic vending module for displaying purchase steps, payment method instructions, automatic vending and change; The image acquisition module is used for face recognition and real-time monitoring of road conditions. When a consumer approaches the unmanned vending device, the consumer's face is automatically recognized and the recognition information and road condition information are uploaded to the background management module. The driving module includes a battery management unit, an ECU, an obstacle avoidance module and a data analysis unit. The battery management unit is used to provide power to the unmanned transport and vending device and monitor and protect the battery through sensors. The ECU includes an obstacle avoidance system. The data analysis unit uses a Kalman filter algorithm to fuse the information obtained by the sensor to quickly and accurately analyze and process the road conditions and judge the working state of the engine. The Kalman filter algorithm predicts the following phases: in, is the prior state estimate vector at time k; x k-1 is the posterior state estimate vector at time k-1; A is the state transfer matrix; u k-1 is the control input vector at time k-1; is the prior estimated covariance matrix at time k; P k-1 is the posterior estimated covariance matrix at time k-1; Q is the process noise covariance moment; Update phase: Among them, K k is the Kalman gain; z k is the measurement vector at time k; C is the measurement matrix; R is the measurement noise covariance matrix; x k is the posterior state estimate vector at time k; P k is the posterior estimated covariance matrix at time k; The background management module is used to save and organize all data transmitted by the storage module, positioning module, display monitoring module, image acquisition module and driving module, and perform optimization and adjustment based on the data.

2. The smart raw seafood and seafood unmanned transportation and sales system according to claim 1 is characterized in that: The storage module uses separate storage compartments in different areas to further classify the products. Each of the storage compartments is equipped with a pressure sensor for calculating the weight and type of the products selected by the consumer, and uploading the data to the background management module. A threshold is set for the weight in the storage compartment. When the weight in the storage compartment is less than the threshold, the background management module issues a replenishment instruction.

3. The smart raw seafood and seafood unmanned transportation and sales system according to claim 1 is characterized in that: The oxygen supply system is used to monitor oxygen data and automatically adjust the oxygen supply. The water supply system is used to monitor the water level in some storage modules and automatically supply water when the water level in some storage modules is lower than a set threshold.

4. The smart raw seafood and seafood unmanned transportation and sales system according to claim 1 is characterized in that: The display monitoring module includes a sales unit for displaying a QR code. Consumers scan the QR code through a mobile phone terminal to download the smart raw seafood and seafood unmanned transportation vehicle APP, use mini-programs and cooperative third-party platforms to search for smart raw seafood and seafood unmanned transportation vehicles, and purchase products by clicking on the local display screen. The background management module will obtain the consumer's real-name information and parameter information and quantity information of the purchased products. Consumers can pay for the purchase through the APP, mini-programs, WeChat, Alipay and other payment platforms on the mobile phone terminal. The mobile phone terminal will send the payment request to the corresponding payment platform, and the payment platform will verify the consumer's account balance and payment password information, and then return the payment success or failure message to the background management module. The background management module decides whether to ship the goods according to the feedback results, and collects the transportation fee and the seafood purchase fee at the same time; the unmanned transportation and sales device also includes an automatic vending unit. If the background management system issues a shipping instruction, the automatic vending unit transports the goods to the shipping port through a conveyor belt. The automatic vending unit can automatically sell by package, by piece and by piece, and consumers can take the products directly from the shipping port. The display monitoring module is also provided with a voice interaction module for realizing human-computer communication through voice interaction during use. The voice interaction module provides an operation interface for consumers, and consumers can select products through the operation interface. The operation interface is provided with a customer service window. If consumers encounter problems that the system cannot solve, they can contact the staff through the customer service window.

5. The smart raw seafood and seafood unmanned transportation and sales system according to claim 1 is characterized in that: The image acquisition unit includes an image enhancement unit, which obtains a gray component image in an original image, performs gray value correction on the pixel points of the gray component image according to the relative light and dark relationship between the pixel points of the gray component image and the pixel points in the gray component image after Gaussian smoothing through a CPLD processor, and synthesizes the gray component image after gray value correction to obtain an enhanced image.

6. The smart raw seafood and seafood unmanned transportation and sales system according to claim 1 is characterized in that: The obstacle avoidance system uses millimeter wave radar to detect the distance, speed and angle of obstacles using electromagnetic waves in the millimeter wave frequency band. The millimeter waves emitted by the millimeter wave radar will be reflected back after encountering an obstacle. By receiving the reflected wave and analyzing the data information of its frequency change, the relative speed of the obstacle is calculated, and timely processing is made, and the processing route is uploaded to the background management module.

7. The smart raw seafood and seafood unmanned transportation and sales system according to claim 6 is characterized in that: The obstacle avoidance system makes avoidance decisions based on pre-set rules and sets a threshold value X. When the radar detects a pedestrian ahead and the pedestrian is on the vehicle's driving path, the unmanned vending machine will slow down or stop according to regulations and wait for the pedestrian to pass before continuing to drive. The formula for determining whether the above decision needs to be adopted is: , in, is the collision time; The speed of the unmanned vending device; is the distance to the obstacle; is the speed of the obstacle relative to the vehicle; if When the speed is less than the set threshold value X, the unmanned transport and vending device takes emergency braking or avoidance measures.

8. The smart raw seafood and seafood unmanned transportation and sales system according to claim 1 is characterized in that: The battery management unit is used to detect the voltage, current and temperature of the battery. The battery management unit can control the charging process of the battery and select a suitable charging method according to the type and status of the battery. When the battery voltage exceeds the set maximum value or the temperature is too high, charging will be stopped immediately.

9. The smart raw seafood and seafood unmanned transportation and sales system according to claim 1 is characterized in that: The background management module plans the transportation route through the positioning module and the location information of the consumer's mobile phone, and identifies and collects the data information of traffic lights and zebra crossings on the route through the image acquisition module. If the data processing module determines that the unmanned transportation and sales device will run a red light, the vehicle is controlled by the ECU; the data processing module is also connected to the cloud computing system, and the data processing module can send the judgment result of whether the vehicle will run a red light to the cloud computing system. The cloud computing system can feedback command instructions to the data processing module, and control the vehicle by connecting the ECU through the data processing module. In addition, the background management module also obtains weather data to be used as the driving standard for vehicle driving data.

10. The smart raw seafood and seafood unmanned transportation and sales system according to claim 1 is characterized in that: The background management module also includes a learning library, which continuously learns through a deep learning framework to improve the accuracy of designing transportation routes. The learning library uses machine learning algorithms such as neural networks and support vector machines to continuously optimize system design and consumer experience.

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