Fresh food intelligent distribution method and distribution system

Abstract

The invention discloses a fresh food intelligent distribution method and distribution system, and the method comprises the steps: obtaining a distribution region range and real-time weather data, and deploying a sensor to monitor the transportation and storage environment of fresh food; acquiring historical purchase data of a user, and predicting purchase categories in a special period by using a machine learning algorithm; according to the area range, a distribution route is optimized by adopting an intelligent algorithm; according to purchase data in a special time period, notifying a user of pre-purchase through a short message in advance, and integrating orders to distribute and deliver in advance; the fresh food is automatically recognized, classified and marked by adopting image recognition and voice recognition technologies; an automatic goods shelf, intelligent goods picking and an unmanned aerial vehicle are adopted, and fast and flexible fresh food distribution is achieved; establishing a plurality of supply sources, setting an early warning system, and monitoring each link of a fresh food supply chain; according to the fresh food intelligent distribution method and distribution system, more data sources and advanced prediction models are integrated, intelligent machine learning is adopted, and the fresh food demand prediction accuracy is improved.

Description

Technical Field

[0001] The present invention belongs to the field of intelligent distribution of fresh food, and in particular relates to an intelligent distribution method and distribution system for fresh food. Background Art

[0002] With the advancement of science and technology and the development of the Internet, the fresh food industry is gradually realizing intelligent and efficient management and operation, and the intelligent distribution method of fresh food has emerged. It uses advanced technical means and intelligent algorithms to optimize and upgrade multiple links such as fresh food pricing, order management, procurement, classification and labeling, distribution route planning, data monitoring and analysis, and inventory management and control to improve operational efficiency, reduce costs, and provide consumers with a better shopping experience.

[0003] However, the demand for fresh food may be affected by factors such as seasonality and holidays, and consumer preferences may also change over time. The demand for fresh food may be affected by factors such as emergencies and natural disasters, which makes supply chain management more complicated. Summary of the invention

[0004] In view of the deficiencies in the prior art, the purpose of the present invention is to provide an intelligent fresh food distribution method and distribution system, integrating more data sources and more advanced prediction models, using intelligent machine learning to improve the accuracy of forecasting demand for fresh food, and building a flexible supply chain network with diversified supply sources to cope with the instability of demand and the impact of emergencies.

[0005] The technical solution adopted by the present invention to solve its technical problem is:

[0006] A method for intelligent distribution of fresh food, comprising:

[0007] Obtain data on the distribution area, obtain real-time weather data for the area, and deploy sensors to monitor the transportation and storage environment of fresh food in real time;

[0008] Obtain the user's historical purchase data, use machine learning algorithms to predict the categories that users purchase during weather changes or holidays based on historical purchase data, and generate special period purchase data;

[0009] Based on the data of the distribution area, the distribution section is monitored in real time, including real-time traffic conditions, road conditions, and the capacity of the distribution vehicle, and the distribution route is optimized using intelligent machine algorithms;

[0010] According to the purchase data during special periods, SMS messages are sent in advance to notify users whether to pre-order. After users pre-order, the orders are consolidated and distributed for delivery on the same day.

[0011] Use image recognition and voice recognition technologies to automatically identify, classify and label fresh food for real-time management and tracking;

[0012] Automated shelves and intelligent picking robot automated storage systems are used to package and process fresh food, and drones are installed on vehicles. When there is a destination that the vehicle cannot reach or in special circumstances, drones can be used to deliver the goods to the destination quickly and flexibly;

[0013] Establish multiple sources of supply, including suppliers from different regions, countries or areas, and monitor fresh food in real time and set up early warning systems to monitor the situation at each link of the supply chain.

[0014] As a preferred method, the method of obtaining the distribution area range data, obtaining the regional real-time weather data, and deploying sensors to monitor the transportation and storage environment of fresh food in real time is:

[0015] Obtain the assigned area range data through geographic information systems or relevant map service providers, including area boundaries, street networks, and building distribution information, and obtain regional real-time weather data through the meteorological department's API, including weather conditions, temperature, humidity, and precipitation information;

[0016] Temperature sensors, humidity sensors, and gas sensors are deployed in transport vehicles, warehouses, and cargo packaging to monitor the transportation and storage environment of fresh food in real time.

[0017] As a preferred method, the user's historical purchase data is obtained, and a machine learning algorithm is used to predict the categories purchased by the user during weather changes or holidays based on the historical purchase data to generate special period purchase data:

[0018] Obtain the user's purchase date, product category, quantity, and payment amount through sales records, order history of e-commerce platforms, and membership card purchase records;

[0019] Use machine learning algorithms to clean historical purchase data, remove outliers and missing values, and format them. Extract purchase date, product category, purchase quantity features, weather data, and holiday information external features from historical purchase data.

[0020] Adopt decision tree machine learning algorithm, and use historical purchase data and external features to train prediction models, use part of historical data for model training, and use another part of historical data for model verification and evaluation;

[0021] Use the trained prediction model, combined with weather changes or holiday information, to predict the product categories that users will purchase during a specific period in the future.

[0022] As a preferred method, according to the data of the distribution area range, the distribution section is monitored in real time, and the section includes real-time traffic conditions, road conditions, and the capacity of the delivery vehicle, and the intelligent machine algorithm is used to optimize the distribution route:

[0023] By acquiring the distribution area data, including street network, distribution center, and distribution point information, the distribution road section is monitored in real time, including real-time traffic flow, congestion level, road construction, and traffic accident road status;

[0024] Using intelligent machine algorithms to build a route planning model, the assigned area is divided into road sections, and the road sections, traffic conditions, road status, and vehicle capacity information are used as input parameters of the model;

[0025] Based on real-time monitoring of traffic conditions and road conditions, route planning is dynamically adjusted, route execution is monitored in real time, actual driving data and delivery results of delivery vehicles are collected, and the model is adjusted and optimized in real time based on feedback information.

[0026] As a preferred method, according to the purchase data of the special period, a method is set to send a text message in advance via mobile phone text messages to notify the user whether to pre-order. After the user pre-orders in advance, the order is integrated into the method of pre-allocation and delivery on the same day:

[0027] According to the purchase data during special periods, use the SMS service provider to set up the function of automatically sending reminder SMS messages, and send pre-order SMS messages to users in advance. The SMS content includes reminder information, recommended products, and preferential activities during special periods;

[0028] When the user receives the reminder SMS, he / she can pre-order through the link or instructions provided in the SMS. On the pre-order page, the user selects the product, confirms the order, and chooses the delivery time.

[0029] Before the user's pre-order order information is allocated for delivery in advance on the day, the pre-order order and other orders are integrated, the orders are optimized and scheduled using intelligent algorithms, and before delivery begins, a delivery notification SMS is sent to the user, which includes the estimated delivery time and order details.

[0030] As a preferred method, the method of using image recognition and voice recognition technology to automatically identify, classify and mark fresh food and to manage and track it in real time is as follows:

[0031] By establishing partnerships with partners such as fresh food suppliers, farms, and supermarkets, we can obtain their fresh food image and voice data or hire photographers to take fresh food images. The images cover samples of various fresh food categories and in different states, including fresh, mature, and spoiled.

[0032] Use deep learning technology to build an image recognition model, use the collected image data to train the model, build a recurrent neural network or transcription model speech recognition model, and use the speech data to train the model;

[0033] Integrate image recognition and voice recognition technologies into one system. When there is fresh food to be identified, the user provides information by taking pictures or describing it by voice. The system uses image recognition technology to identify and classify the fresh food.

[0034] The identified and tagged information is stored in a database or cloud system, and users can view real-time information, including inventory status, product status, and procurement needs, through an application or web interface.

[0035] As a preferred method, fresh food is packaged and processed using automated shelves and intelligent picking robot automated storage systems, and drones are installed on vehicles. When there is a destination that the vehicle cannot reach or in special circumstances, the method of using drones to quickly and flexibly deliver the goods to the destination is as follows:

[0036] Set up automated shelves and intelligent picking robot systems to store, package and pick fresh food. Equip drones on delivery vehicles and integrate them with the warehouse system. When there is a destination that the vehicle cannot reach or special circumstances occur, the warehouse system automatically identifies and transfers the delivered goods to the drones.

[0037] The flight path of the drone is automatically planned through GPS and sensor technology and the location and environmental conditions of the destination. After the drone is loaded with cargo, the automatic flight program is started and it flies to the destination along the predetermined path.

[0038] The drone is equipped with obstacle avoidance sensors and an automatic return function safety system. During the flight, the drone maintains contact with the central system through wireless communication, and updates the flight information and cargo status in real time.

[0039] As a preferred method, multiple supply sources are established, including suppliers from different regions, countries or areas, and fresh food is monitored in real time and an early warning system is set up to monitor the situation of each link in the supply chain:

[0040] For the same type of products, select multiple suppliers with similar scale and quality standards, and use supply chain management software or platforms to achieve real-time monitoring and visualization of all links in the supply chain;

[0041] Establish digital connections with suppliers to achieve real-time data collection and information exchange, and establish a supply chain early warning system to set thresholds for various indicators. When an abnormality or deviation from expectations occurs in a certain link in the supply chain, the system automatically triggers an early warning and sends text messages to notify relevant personnel to handle the situation.

[0042] Regularly evaluate the reliability of suppliers, including production capacity, quality control, and delivery reliability, and dynamically adjust the supplier structure based on the evaluation results.

[0043] A fresh food intelligent distribution system, comprising:

[0044] Data collection module, used to obtain distribution area range data, real-time weather data, user historical purchase data and data from all links of the supply chain;

[0045] Intelligent prediction and decision-making module, which uses machine learning algorithms to analyze users' historical purchase data and weather changes, and predict users' purchase preferences during special periods;

[0046] Route optimization and delivery management module, which uses intelligent machine algorithms to optimize delivery routes based on distribution area coverage data and real-time traffic conditions;

[0047] The user pre-order service module is used to send purchase notifications to users in advance via SMS based on purchase data during special periods, informing users to pre-order fresh food in advance. After users pre-order in advance, the orders are integrated into the delivery plan for the day;

[0048] Fresh food identification and management module, which uses image recognition and voice recognition technology to automatically identify, classify and mark fresh food, and monitor the transportation and storage environment of fresh food in real time;

[0049] Automated warehousing and drone delivery module, which is used to establish automated shelves and intelligent picking robot automated warehousing systems, package and process fresh food and manage warehousing. It also equips delivery vehicles with drones to deliver fresh food quickly and flexibly when special circumstances and delivery problems arise.

[0050] The supply chain monitoring and early warning module is used to establish multiple supply sources, monitor the situation of each link in the supply chain in real time, set up an early warning system, and monitor abnormal situations in the supply chain.

[0051] Another technical problem to be solved by the present invention is to provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, an intelligent fresh food distribution method and distribution system as described above is implemented.

[0052] Another technical problem to be solved by the present invention is to provide a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, a method and system for intelligent distribution of fresh food are implemented.

[0053] The beneficial effects of the present invention are:

[0054] By real-time monitoring of distribution area data and regional real-time weather data, and using intelligent machine algorithms to optimize distribution routes, the operational efficiency of the supply chain can be improved, and delivery time and costs can be reduced. According to the user's historical purchase data and weather changes, the user's purchase preferences can be predicted, and the purchase data for special time periods can be set. Pre-order notifications can be sent in advance via mobile phone text messages to improve the user's purchase experience and satisfaction. By deploying sensors to monitor the transportation and storage environment of fresh food in real time, and using drone rapid delivery technology, the flexibility and adaptability of delivery are enhanced to deal with destinations or special situations that vehicles cannot reach. According to the user's pre-order situation and purchase data for special time periods, the order is integrated into the same day for early distribution and delivery, which can reduce inventory backlogs and food waste and optimize inventory management. The use of image recognition and voice recognition technology to automatically identify, classify and mark fresh food, and the installation of drones on delivery vehicles improves the safety and reliability of fresh food. Establishing multiple supply sources and setting up a real-time monitoring and early warning system for fresh food can promptly detect and respond to abnormal situations in the supply chain, reducing risks and costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 The figure is a flow chart of a fresh food intelligent distribution system of the present invention. DETAILED DESCRIPTION

[0056] The principles and features of the present invention are described below, and the examples are only used to explain the present invention and are not used to limit the scope of the present invention. The present invention is described more specifically by way of example in the following paragraphs. According to the following description and claims, the advantages and features of the present invention will become clearer.

[0057] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0058] Example

[0059] A method for intelligent distribution of fresh food, comprising:

[0060] Obtain data on the distribution area, obtain real-time weather data for the area, and deploy sensors to monitor the transportation and storage environment of fresh food in real time;

[0061] Obtain the user's historical purchase data, use machine learning algorithms to predict the categories that users purchase during weather changes or holidays based on historical purchase data, and generate special period purchase data;

[0062] Based on the data of the distribution area, the distribution section is monitored in real time, including real-time traffic conditions, road conditions, and the capacity of the distribution vehicle, and the distribution route is optimized using intelligent machine algorithms;

[0063] According to the purchase data during special periods, SMS messages are sent in advance to notify users whether to pre-order. After users pre-order, the orders are consolidated and distributed for delivery on the same day.

[0064] Use image recognition and voice recognition technologies to automatically identify, classify and label fresh food for real-time management and tracking;

[0065] Automated shelves and intelligent picking robot automated storage systems are used to package and process fresh food, and drones are installed on vehicles. When there is a destination that the vehicle cannot reach or in special circumstances, drones can be used to deliver the goods to the destination quickly and flexibly;

[0066] Establish multiple sources of supply, including suppliers from different regions, countries or areas, and monitor fresh food in real time and set up early warning systems to monitor the situation at each link of the supply chain.

[0067] Deploy sensors to monitor environmental parameters such as temperature and humidity in real time to ensure that fresh food is in suitable conditions during transportation and storage; predict the categories that users will buy when the weather changes or on holidays based on their historical purchase data to provide personalized services; use machine learning algorithms to analyze historical purchase data and infer users' purchasing patterns so that corresponding adjustments can be made during specific time periods; optimize delivery routes and reduce delivery time and costs by monitoring distribution area range data and road section information in real time; set up pre-order notifications based on purchase data during special time periods, and use mobile phone text messages and other methods to remind users, so that orders are centralized and pre-processed; use image recognition and voice recognition technology to automatically identify, classify and mark fresh food for real-time management and tracking; equip delivery vehicles with drones to respond to destinations that vehicles cannot reach or special circumstances, and achieve fast and flexible delivery of goods; monitor suppliers in different regions, countries or regions through real-time monitoring and early warning systems to ensure supply chain stability and security.

[0068] The method of obtaining the range data of the distribution area, obtaining the real-time weather data of the area, and deploying sensors to monitor the transportation and storage environment of fresh food in real time is as follows;

[0069] Obtain the assigned area range data through geographic information systems or relevant map service providers, including area boundaries, street networks, and building distribution information, and obtain regional real-time weather data through the meteorological department's API, including weather conditions, temperature, humidity, and precipitation information;

[0070] Temperature sensors, humidity sensors, and gas sensors are deployed in transport vehicles, warehouses, and cargo packaging to monitor the transportation and storage environment of fresh food in real time.

[0071] By real-time monitoring of the temperature, humidity and gas conditions in the transportation and storage environment, environmental problems can be discovered and resolved in a timely manner, ensuring that fresh food is in suitable conditions and reducing food losses and quality problems. By obtaining distribution area data and real-time weather data, combined with sensor monitoring data, real-time monitoring and analysis of the entire supply chain can be achieved, improving the visualization of the supply chain, and facilitating timely adjustment of distribution strategies and response to emergencies. By ensuring the quality and safety of fresh food and making adjustments in advance based on weather conditions, the user purchasing experience can be improved and user trust and loyalty can be increased.

[0072] The method of obtaining the user's historical purchase data and using a machine learning algorithm to predict the categories purchased by the user during weather changes or holidays based on the historical purchase data to generate purchase data for special periods is as follows:

[0073] Obtain the user's purchase date, product category, quantity, and payment amount through sales records, order history of e-commerce platforms, and membership card purchase records;

[0074] Use machine learning algorithms to clean historical purchase data, remove outliers and missing values, and format them. Extract purchase date, product category, purchase quantity features, weather data, and holiday information external features from historical purchase data.

[0075] Adopt decision tree machine learning algorithm, and use historical purchase data and external features to train prediction models, use part of historical data for model training, and use another part of historical data for model verification and evaluation;

[0076] Use the trained prediction model, combined with weather changes or holiday information, to predict the product categories that users will purchase during a specific period in the future.

[0077] By predicting the categories that users will buy when the weather changes or during holidays, companies can adjust marketing strategies and product recommendations in advance, provide users with a personalized shopping experience, and increase purchase conversion rates and user satisfaction. By predicting user purchasing behavior during special periods, inventory management and product supply can be more accurate, avoiding excess or out-of-stock situations, and maximizing sales and profitability. By predicting user purchasing behavior, companies can more effectively plan production, distribution, and marketing resources, reduce resource waste and costs, and improve operational efficiency. Through sales records, order history of e-commerce platforms, membership card purchase records, etc., users' historical purchase data, including purchase date, product category, purchase quantity, payment amount, etc., can be obtained. information; clean the historical purchase data, remove outliers and missing values, and format it to make it suitable for the input of the machine learning algorithm; extract features such as purchase date, product category, and purchase quantity from the historical purchase data, and also extract external features such as weather data and holiday information to establish associations with user purchase behavior; use machine learning algorithms such as decision trees, use historical purchase data and external features to train the model, and then use another part of historical data to verify and evaluate the model to ensure the accuracy and generalization ability of the model; use the trained prediction model, combined with weather changes or holiday information, to predict the product categories that users will purchase in a specific period of time in the future, and provide decision support and action guidance for enterprises.

[0078] Based on the data of the distribution area, the distribution section is monitored in real time. The section includes real-time traffic conditions, road conditions, and the capacity of the distribution vehicle. The method of optimizing the distribution route using intelligent machine algorithms is as follows:

[0079] By acquiring the distribution area data, including street network, distribution center, and distribution point information, the distribution road section is monitored in real time, including real-time traffic flow, congestion level, road construction, and traffic accident road status;

[0080] Using intelligent machine algorithms to build a route planning model, the assigned area is divided into road sections, and the road sections, traffic conditions, road status, and vehicle capacity information are used as input parameters of the model;

[0081] Based on real-time monitoring of traffic conditions and road conditions, route planning is dynamically adjusted, route execution is monitored in real time, actual driving data and delivery results of delivery vehicles are collected, and the model is adjusted and optimized in real time based on feedback information.

[0082] By monitoring traffic conditions and road conditions in real time, the system can adjust delivery routes in a timely manner to respond to emergencies such as traffic jams or road construction, thereby ensuring delivery efficiency and on-time delivery. The route planning model established using intelligent machine algorithms can dynamically optimize the allocation route based on real-time traffic conditions and vehicle capacity information, so that delivery vehicles can travel the shortest distance and time, thereby reducing delivery costs. By monitoring route execution in real time and collecting actual driving data of delivery vehicles, the system can continuously optimize delivery strategies, improve delivery efficiency, and reduce delivery time and costs. Timely acquisition of information such as traffic accidents or road construction can avoid vehicle obstructions or delays, reduce delivery risks, and improve delivery reliability.

[0083] According to the purchase data during special periods, set up SMS messages to notify users in advance whether to pre-order. After users pre-order in advance, the order will be integrated into the distribution and delivery method of the day:

[0084] According to the purchase data during special periods, use the SMS service provider to set up the function of automatically sending reminder SMS messages, and send pre-order SMS messages to users in advance. The SMS content includes reminder information, recommended products, and preferential activities during special periods;

[0085] When the user receives the reminder SMS, he / she can pre-order through the link or instructions provided in the SMS. On the pre-order page, the user selects the product, confirms the order, and chooses the delivery time.

[0086] Before the user's pre-order order information is allocated for delivery in advance on the day, the pre-order order and other orders are integrated, the orders are optimized and scheduled using intelligent algorithms, and a delivery notification SMS is sent to the user before delivery begins. The SMS includes the estimated delivery time and order details.

[0087] By sending SMS messages in advance to inform users of purchase opportunities during special periods, users are guided to pre-order in advance, increasing user participation and purchase intention; users can select products, confirm orders, and choose a delivery time that suits them in advance, which improves the user's shopping experience and reduces uncertainty in the delivery process; integrating users' pre-order orders with other orders and using intelligent algorithms to optimize order scheduling can improve delivery efficiency and reduce delivery costs and time; by providing purchase opportunities, recommended products and preferential activities during special periods, sales can be promoted and sales volume can be increased; based on purchase data during special periods, data analysis and prediction can be performed to determine the best SMS sending time and content, as well as product promotion recommendations and promotions; use SMS service providers to set up the function of automatically sending reminder SMS messages, and send pre-order SMS messages to users in advance, which include reminder information for special periods, product recommendations and promotions; after receiving the reminder SMS, users can enter the pre-order page through the link or instructions provided in the SMS, select products, confirm the order, and choose a suitable delivery time; integrate the user's pre-order order with other orders, and use intelligent algorithms to optimize the scheduling of orders before the start of delivery on the same day to ensure delivery efficiency and on-time delivery; before the start of delivery, send a delivery notification SMS to users, including the estimated delivery time and order details, providing visual information on delivery, enhancing user trust and satisfaction.

[0088] The method of using image recognition and voice recognition technology to automatically identify, classify and mark fresh food for real-time management and tracking is as follows:

[0089] By establishing partnerships with partners such as fresh food suppliers, farms, and supermarkets, we can obtain their fresh food image and voice data or hire photographers to take fresh food images. The images cover samples of various fresh food categories and in different states, including fresh, mature, and spoiled.

[0090] Use deep learning technology to build an image recognition model, use the collected image data to train the model, build a recurrent neural network or transcription model speech recognition model, and use the speech data to train the model;

[0091] Integrate image recognition and voice recognition technologies into one system. When there is fresh food to be identified, the user provides information by taking pictures or describing it by voice. The system uses image recognition technology to identify and classify the fresh food.

[0092] The identified and marked information is stored in a database or cloud system, and users can view real-time information, including inventory status, product status, and procurement needs, through an application or web interface.

[0093] Automatic identification, classification and labeling can greatly improve the efficiency of fresh food management and reduce labor costs and time costs. Based on image recognition and voice recognition technology, fresh food can be accurately identified and classified to avoid human misjudgment and wrong labeling. Storing the identified and labeled information in a database or cloud system can achieve real-time fresh food management and tracking, and timely grasp the inventory situation, product status and procurement needs. Users can provide information by taking images or voice description, which is simple and convenient to operate and improves the user experience. Establish cooperative relationships with suppliers, farms, supermarkets and other partners to obtain image and voice data of fresh food to ensure that samples of various categories and different states are covered. Use deep learning technology to establish image recognition models and voice recognition models, train image data and voice data respectively, so that the models can accurately identify and classify fresh food. Integrate image recognition and voice recognition technologies into one system, users provide information by taking images or voice description, and the system uses image recognition technology to identify and classify fresh food. Storing the identified and labeled information in a database or cloud system, users can view real-time information, including inventory situation, product status and procurement needs, through applications or network interfaces to achieve real-time management and tracking.

[0094] Fresh food is packaged and processed using automated shelves and intelligent picking robot automated storage systems, and drones are installed on vehicles. When there is a destination that the vehicle cannot reach or special circumstances occur, the method of using drones to quickly and flexibly deliver the goods to the destination is as follows:

[0095] Set up automated shelves and intelligent picking robot systems to store, package and pick fresh food. Equip drones on delivery vehicles and integrate them with the warehouse system. When there is a destination that the vehicle cannot reach or special circumstances occur, the warehouse system automatically identifies and transfers the delivered goods to the drones.

[0096] The flight path of the drone is automatically planned through GPS and sensor technology and the location and environmental conditions of the destination. After the drone is loaded with cargo, the automatic flight program is started and it flies to the destination along the predetermined path.

[0097] The drone is equipped with obstacle avoidance sensors and an automatic return function safety system. During the flight, the drone maintains contact with the central system through wireless communication, and updates the flight information and cargo status in real time.

[0098] When the delivery vehicle cannot reach the destination or special circumstances arise, the use of drones for fast and flexible delivery can respond in a timely manner to ensure the delivery of goods; drones can cover areas that are difficult for delivery vehicles to reach, expand the delivery range, and meet a wider range of delivery needs, especially in remote areas or places with inconvenient transportation; drones have the characteristics of fast flight, and when combined with automated shelves and intelligent picking robot systems, they can greatly improve delivery efficiency, shorten delivery time, and enhance customer experience; automated warehousing systems and intelligent picking robots can reduce labor costs, while the operating costs of drones are relatively low, which can reduce delivery costs overall; using automated shelves and intelligent picking robots to store and sort fresh food Packaging and picking ensure automated handling of goods within the warehouse; when the vehicle is unable to reach the destination or special circumstances occur, the warehousing system automatically identifies and transfers the delivered goods to the drone to ensure timely delivery of the goods; using GPS and sensor technology, the drone can communicate with the location and environmental conditions of the destination, automatically plan the flight path, and ensure safe and efficient delivery of goods; the drone is equipped with obstacle avoidance sensors and an automatic return function safety system to ensure that it can avoid collisions with obstacles during flight and return safely when necessary, ensuring the safe delivery of goods; the drone maintains contact with the central system through wireless communication, and updates flight information and cargo status in real time to ensure real-time monitoring and management of the delivery process.

[0099] Establish multiple sources of supply, including suppliers from different regions, countries or areas, and monitor fresh food in real time and set up early warning systems to monitor the situation at each link of the supply chain:

[0100] For the same type of products, select multiple suppliers with similar scale and quality standards, and use supply chain management software or platforms to achieve real-time monitoring and visualization of all links in the supply chain;

[0101] Establish digital connections with suppliers to achieve real-time data collection and information exchange, and establish a supply chain early warning system to set thresholds for various indicators. When an abnormality or deviation from expectations occurs in a certain link in the supply chain, the system automatically triggers an early warning and sends text messages to notify relevant personnel to handle the situation.

[0102] Regularly evaluate the reliability of suppliers, including production capacity, quality control, and delivery reliability, and dynamically adjust the supplier structure based on the evaluation results.

[0103] Establishing multiple sources of supply can reduce the risks caused by problems with a certain supplier, such as supply interruptions, quality problems, etc., and enhance the stability and reliability of the supply chain; diversifying supply sources can improve the company's ability to respond to market changes. For example, when the supply of a certain region or country is affected by force majeure, it can quickly turn to other suppliers; by comparing the prices, quality and delivery capabilities of different suppliers, it is possible to optimize procurement costs and ensure that there are alternatives at different price points; establishing a real-time monitoring and early warning system can promptly detect abnormal situations in the supply chain, such as raw material shortages, production delays, etc., which helps to take timely remedial measures to avoid serious impact on the business; for the same type of products, choose multiple suppliers with similar scale and quality standards suppliers to ensure that there are alternative options in terms of quality and price; use supply chain management software or platforms to achieve real-time monitoring and visualization of all links in the supply chain, including raw material procurement, production and processing, logistics and distribution, etc.; establish digital connections with suppliers to achieve real-time data collection and information exchange, and ensure timely monitoring of data and conditions in all links of the supply chain; establish a supply chain early warning system, set thresholds for various indicators, and when a link in the supply chain is abnormal or deviates from expectations, the system automatically triggers an early warning and notifies relevant personnel to handle it by sending text messages; regularly evaluate the reliability of suppliers, including production capacity, quality control, delivery reliability, etc., and dynamically adjust the supplier structure according to the evaluation results to ensure the stability and reliability of the supply chain.

[0104] A fresh food intelligent distribution system, comprising:

[0105] Data collection module, used to obtain distribution area range data, real-time weather data, user historical purchase data and data from all links of the supply chain;

[0106] Intelligent prediction and decision-making module, which uses machine learning algorithms to analyze users' historical purchase data and weather changes, and predict users' purchase preferences during special periods;

[0107] Route optimization and delivery management module, which uses intelligent machine algorithms to optimize delivery routes based on distribution area coverage data and real-time traffic conditions;

[0108] The user pre-order service module is used to send purchase notifications to users in advance via SMS based on purchase data during special periods, informing users to pre-order fresh food in advance. After users pre-order in advance, the orders are integrated into the delivery plan for the day;

[0109] Fresh food identification and management module, which uses image recognition and voice recognition technology to automatically identify, classify and mark fresh food, and monitor the transportation and storage environment of fresh food in real time;

[0110] Automated warehousing and drone delivery module, which is used to establish automated shelves and intelligent picking robot automated warehousing systems, package and process fresh food and manage warehousing. It also equips delivery vehicles with drones to deliver fresh food quickly and flexibly when special circumstances and delivery problems arise.

[0111] The supply chain monitoring and early warning module is used to establish multiple supply sources, monitor the situation of each link in the supply chain in real time, set up an early warning system, and monitor abnormal situations in the supply chain.

[0112] Through the intelligent prediction and decision-making module, the system can predict the user's purchase preferences based on the user's historical purchase data and weather changes, provide personalized purchase suggestions, and enhance the user experience; the route optimization and delivery management module uses intelligent algorithms to optimize the delivery route, combined with real-time traffic conditions, to improve delivery efficiency and reduce delivery costs; the user pre-order service module can send purchase notifications to users via mobile phone text messages to encourage users to pre-order fresh food in advance, thereby smoothly allocating demand and reducing temporary supply chain pressure; the fresh food identification and management module uses image recognition and voice recognition technology to automatically identify, classify and mark fresh food, and monitor the transportation and storage environment of fresh food in real time, thereby improving management efficiency and product quality; the automated warehousing and distribution module combines automated shelves, intelligent picking robots and drone technology to achieve packaging processing, warehousing management and fast and flexible cargo delivery of fresh food to deal with special situations and delivery problems; through the supply chain monitoring and early warning module, multiple supply sources are established, the situation of each link in the supply chain is monitored in real time, and an early warning system is set up to promptly detect and respond to abnormal situations in the supply chain to ensure the stability and reliability of the supply chain.

[0113] This embodiment also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, an intelligent fresh food distribution method and distribution system as described above are implemented.

[0114] This embodiment also provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the above-mentioned intelligent distribution method and distribution system for fresh food are implemented.

[0115] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0116] Those skilled in the art will clearly understand that for the sake of convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above.

[0117] The above embodiments of the present invention are not intended to limit the protection scope of the present invention, and the implementation modes of the present invention are not limited thereto. All other modifications, replacements or changes made to the above structures of the present invention based on the above contents of the present invention, in accordance with common technical knowledge and customary means in the art, without departing from the above basic technical ideas of the present invention, should fall within the protection scope of the present invention.

Claims

1. A method for intelligent distribution of fresh food, characterized in that: Included are: Obtain data on the distribution area, obtain real-time weather data for the area, and deploy sensors to monitor the transportation and storage environment of fresh food in real time; Obtain the user's historical purchase data, use machine learning algorithms to predict the categories that users purchase during weather changes or holidays based on historical purchase data, and generate special period purchase data; Based on the data of the distribution area, the distribution section is monitored in real time, including real-time traffic conditions, road conditions, and the capacity of the distribution vehicle, and the distribution route is optimized using intelligent machine algorithms; According to the purchase data during special periods, SMS messages are sent in advance to notify users whether to pre-order. After users pre-order, the orders are consolidated and distributed for delivery on the same day. Use image recognition and voice recognition technologies to automatically identify, classify and label fresh food for real-time management and tracking; Automated shelves and intelligent picking robot automated storage systems are used to package and process fresh food, and drones are installed on vehicles. When there is a destination that the vehicle cannot reach or in special circumstances, drones can be used to deliver the goods to the destination quickly and flexibly; Establish multiple sources of supply, including suppliers from different regions, countries or areas, and monitor fresh food in real time and set up early warning systems to monitor the situation at each link of the supply chain.

2. The method for intelligent distribution of fresh food according to claim 1, characterized in that: The method of obtaining the range data of the distribution area, obtaining the real-time weather data of the area, and deploying sensors to monitor the transportation and storage environment of fresh food in real time is as follows; Obtain the assigned area range data through geographic information systems or relevant map service providers, including area boundaries, street networks, and building distribution information, and obtain regional real-time weather data through the meteorological department's API, including weather conditions, temperature, humidity, and precipitation information; Temperature sensors, humidity sensors, and gas sensors are deployed in transport vehicles, warehouses, and cargo packaging to monitor the transportation and storage environment of fresh food in real time.

3. The method for intelligent distribution of fresh food according to claim 2, characterized in that: The method of obtaining the user's historical purchase data and using a machine learning algorithm to predict the categories purchased by the user during weather changes or holidays based on the historical purchase data to generate purchase data for special periods is as follows: Obtain the user's purchase date, product category, quantity, and payment amount through sales records, order history of e-commerce platforms, and membership card purchase records; Use machine learning algorithms to clean historical purchase data, remove outliers and missing values, and format them. Extract purchase date, product category, purchase quantity features, weather data, and holiday information external features from historical purchase data. Adopt decision tree machine learning algorithm, and use historical purchase data and external features to train prediction models, use part of historical data for model training, and use another part of historical data for model verification and evaluation; Use the trained prediction model, combined with weather changes or holiday information, to predict the product categories that users will purchase during a specific period in the future.

4. The method for intelligent distribution of fresh food according to claim 3, characterized in that: Based on the data of the distribution area, the distribution section is monitored in real time. The section includes real-time traffic conditions, road conditions, and the capacity of the distribution vehicle. The method of optimizing the distribution route using intelligent machine algorithms is as follows: By acquiring the distribution area data, including street network, distribution center, and distribution point information, the distribution road section is monitored in real time, including real-time traffic flow, congestion level, road construction, and traffic accident road status; Using intelligent machine algorithms to build a route planning model, the assigned area is divided into road sections, and the road sections, traffic conditions, road status, and vehicle capacity information are used as input parameters of the model; Based on real-time monitoring of traffic conditions and road conditions, route planning is dynamically adjusted, route execution is monitored in real time, actual driving data and delivery results of delivery vehicles are collected, and the model is adjusted and optimized in real time based on feedback information.

5. The method for intelligent distribution of fresh food according to claim 4, characterized in that: According to the purchase data during special periods, set up SMS messages to notify users in advance whether to pre-order. After users pre-order in advance, the order will be integrated into the distribution and delivery method of the day: According to the purchase data during special periods, use the SMS service provider to set up the function of automatically sending reminder SMS messages, and send pre-order SMS messages to users in advance. The SMS content includes reminder information, recommended products, and preferential activities during special periods; When the user receives the reminder SMS, he / she can pre-order through the link or instructions provided in the SMS. On the pre-order page, the user selects the product, confirms the order, and chooses the delivery time. Before the user's pre-order order information is allocated for delivery in advance on the day, the pre-order order and other orders are integrated, the orders are optimized and scheduled using intelligent algorithms, and before delivery begins, a delivery notification SMS is sent to the user, which includes the estimated delivery time and order details.

6. The method for intelligent distribution of fresh food according to claim 5, characterized in that: The method of using image recognition and voice recognition technology to automatically identify, classify and mark fresh food for real-time management and tracking is as follows: By establishing partnerships with partners such as fresh food suppliers, farms, and supermarkets, we can obtain their fresh food image and voice data or hire photographers to take fresh food images. The images cover samples of various fresh food categories and in different states, including fresh, mature, and spoiled. Use deep learning technology to build an image recognition model, use the collected image data to train the model, build a recurrent neural network or transcription model speech recognition model, and use the speech data to train the model; Integrate image recognition and voice recognition technologies into one system. When there is fresh food to be identified, the user provides information by taking pictures or describing it by voice. The system uses image recognition technology to identify and classify the fresh food. The identified and marked information is stored in a database or cloud system, and users can view real-time information, including inventory status, product status, and procurement needs, through an application or web interface.

7. The method for intelligent distribution of fresh food according to claim 6, characterized in that: Fresh food is packaged and processed using automated shelves and intelligent picking robot automated storage systems, and drones are installed on vehicles. When there is a destination that the vehicle cannot reach or special circumstances occur, the method of using drones to quickly and flexibly deliver the goods to the destination is as follows: Set up automated shelves and intelligent picking robot systems to store, package and pick fresh food. Equip drones on delivery vehicles and integrate them with the warehouse system. When there is a destination that the vehicle cannot reach or special circumstances occur, the warehouse system automatically identifies and transfers the delivered goods to the drones. The flight path of the drone is automatically planned through GPS and sensor technology and the location and environmental conditions of the destination. After the drone is loaded with cargo, the automatic flight program is started and it flies to the destination along the predetermined path. The drone is equipped with obstacle avoidance sensors and an automatic return function safety system. During the flight, the drone maintains contact with the central system through wireless communication, and updates the flight information and cargo status in real time.

8. The method for intelligent distribution of fresh food according to claim 7, characterized in that: Establish multiple sources of supply, including suppliers from different regions, countries or areas, and monitor fresh food in real time and set up early warning systems to monitor the situation at each link of the supply chain: For the same type of products, select multiple suppliers with similar scale and quality standards, and use supply chain management software or platforms to achieve real-time monitoring and visualization of all links in the supply chain; Establish digital connections with suppliers to achieve real-time data collection and information exchange, and establish a supply chain early warning system to set thresholds for various indicators. When an abnormality or deviation from expectations occurs in a certain link in the supply chain, the system automatically triggers an early warning and sends text messages to notify relevant personnel to handle the situation. Regularly evaluate the reliability of suppliers, including production capacity, quality control, and delivery reliability, and dynamically adjust the supplier structure based on the evaluation results.

9. A fresh food intelligent distribution system, characterized in that: Included are: Data collection module, used to obtain distribution area range data, real-time weather data, user historical purchase data and data from all links of the supply chain; Intelligent prediction and decision-making module, which uses machine learning algorithms to analyze users' historical purchase data and weather changes, and predict users' purchase preferences during special periods; Route optimization and delivery management module, which uses intelligent machine algorithms to optimize delivery routes based on distribution area coverage data and real-time traffic conditions; The user pre-order service module is used to send purchase notifications to users in advance via SMS based on purchase data during special periods, informing users to pre-order fresh food in advance. After users pre-order in advance, the orders are integrated into the delivery plan for the day; Fresh food identification and management module, which uses image recognition and voice recognition technology to automatically identify, classify and mark fresh food, and monitor the transportation and storage environment of fresh food in real time; Automated warehousing and drone delivery module, which is used to establish automated shelves and intelligent picking robot automated warehousing systems, package and process fresh food and manage warehousing, and equip delivery vehicles with drones to deliver fresh food quickly and flexibly when special circumstances and delivery problems arise; The supply chain monitoring and early warning module is used to establish multiple supply sources, monitor the situation of each link in the supply chain in real time, set up an early warning system, and monitor abnormal situations in the supply chain.

10. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for intelligently distributing fresh food as claimed in any one of claims 1 to 8 is implemented; A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the fresh food intelligent distribution method as described in any one of claims 1 to 8 is implemented.

Images