Internet of Things-Based Food Delivery, Warehousing, and Logistics Management Methods and Systems

Abstract

The present invention discloses a food distribution, warehousing, and logistics management method and system based on the Internet of Things, relating to the field of logistics data management technology. The food distribution, warehousing, and logistics management method based on the Internet of Things includes the following steps: food preparation for delivery and delivery, food delivery and delivery; first food delivery quality logistics management based on a first food delivery quality assessment result; and second food delivery quality logistics management based on a second food delivery quality assessment result. The present invention achieves the effect of improving the accuracy of the food distribution, warehousing, and logistics management method based on the Internet of Things through graded self-inspection before food delivery, graded assessment of relay nodes along the food delivery route during food delivery, and graded management adjustment, thereby solving the problem of insufficient accuracy of food distribution, warehousing, and logistics management methods based on the Internet of Things in the prior art.

Description

Technical Field

[0001] This invention relates to the field of logistics data management technology, and in particular to a method and system for food distribution, warehousing and logistics management based on the Internet of Things. Background Technology

[0002] As catering businesses, schools, hospitals, and other institutions expand, the demand for food delivery is steadily increasing, with higher requirements for supply chain efficiency and service quality. Meanwhile, the introduction of IoT technology has significantly improved the efficiency and safety of food delivery, enabling real-time monitoring and tracking of ingredients. The application of smart devices further enhances delivery efficiency and reduces operating costs.

[0003] The IoT-based approach to food delivery, warehousing, and logistics management is achieved through the following technologies: Unmanned delivery technology: Enables food delivery to remote areas, breaking geographical limitations. Automated warehousing, outbound processing, and picking operations are achieved through RFID, sensors, and IoT devices. IoT technology enables real-time tracking and traceability of food products, ensuring their safety and traceability, and enhancing consumer trust.

[0004] For example, the invention patent with publication number CN110199304B discloses a food delivery system and method, comprising: at least one delivery unit group (10), each delivery unit group comprising: a first storage section (101) for transporting and storing food to be delivered, the first storage section being movable; a first sorting section (102) for moving the food to be delivered stored in the first storage section to a second storage section; a second storage section (103) for storing the food to be delivered provided by the first sorting section; and a second sorting section (104) for moving the food to be delivered stored in the second storage section to a target location. A food delivery method employing this system is also described.

[0005] For example, the food logistics supply chain model disclosed in invention patent CN104346710A includes four sub-modules: agricultural product production, transportation, warehousing, and distribution. The agricultural product production process / stage provides raw materials for the food supply chain; the transportation stage refers to transporting the results of the agricultural product production process / stage to food processing units; the warehousing process / stage refers to storing finished / semi-finished food products in warehouses; and the distribution process / stage refers to distributing the finished / semi-finished food products between various required units.

[0006] However, in the process of implementing the inventive technical solution in the embodiments of this application, it was found that the above-mentioned technology has at least the following technical problems:

[0007] In existing technologies, for the delivery of small commodities such as fruits and vegetables, and for the delivery of some chain supermarkets, because many types of ingredients are mixed together, there are many complex influencing factors. This can easily lead to problems such as damage or contamination of fruits, vegetables and fragile items during the specific delivery process. Therefore, the accuracy of the food delivery, warehousing and logistics management methods based on the Internet of Things is insufficient. Summary of the Invention

[0008] This application provides an IoT-based method and system for food distribution, warehousing, and logistics management, which solves the problem of insufficient accuracy in existing IoT-based food distribution, warehousing, and logistics management methods, and achieves the effect of improving the accuracy of IoT-based food distribution, warehousing, and logistics management methods.

[0009] This application provides an Internet of Things (IoT)-based method for food distribution, warehousing, and logistics management, including the following steps: conducting self-inspection of the quality of the corresponding stored food; if the self-inspection results are satisfactory, the food is prepared for outbound distribution; conducting self-inspection of the food to be outbound for distribution; if the self-inspection results are satisfactory, the food is outbound for distribution; setting relay nodes in the outbound distribution route; when the food is outbound and distributed to a certain relay node, performing a first evaluation of the food distribution quality; and performing first logistics management based on the first evaluation result; and performing a second evaluation of the food distribution quality after the first logistics management, and performing second logistics management based on the second evaluation result.

[0010] Furthermore, the self-inspection of the corresponding stored ingredients specifically includes: collecting and testing the corresponding stored ingredients according to a predefined stored ingredient plan to obtain the types of microbial units, the quantity of microbial units, the pesticide residue value, and the veterinary drug residue value of the stored ingredients; if the types of microbial units are less than the threshold for types of microbial units, the quantity of microbial units is less than the threshold for the quantity of microbial units, the pesticide residue value is less than the threshold for pesticide residue, and the veterinary drug residue value is less than the threshold for veterinary drug residue, then the ingredients are ready for shipment; otherwise, the ingredients are not ready for shipment and relevant personnel are notified for verification.

[0011] Furthermore, the process of conducting self-inspection on the corresponding warehoused ingredients prepared for outbound delivery is as follows: The corresponding warehoused ingredients are collected and tested according to a predefined delivery plan to obtain the airtightness value of the packaging, the surface temperature of the warehoused ingredients, the estimated delivery time of the warehoused ingredients, the types and quantities of microorganisms in the corresponding vehicle environment; if the airtightness value of the packaging is less than the airtightness threshold, the quantity of microorganisms is less than the microorganism quantity threshold, the surface temperature is less than the surface temperature threshold, the estimated delivery time is less than the estimated delivery time threshold, the types of microorganisms in the corresponding vehicle environment are less than the vehicle environment microorganism type threshold, and the quantity of microorganisms in the corresponding vehicle environment is less than the vehicle environment microorganism quantity threshold, then the ingredients are allowed to be delivered; otherwise, the ingredients cannot be delivered and relevant personnel are notified for verification.

[0012] Furthermore, the first evaluation of food delivery quality when food is delivered to a relay node in the food delivery route specifically includes: measuring the ambient temperature of the food using a temperature sensor, measuring the ambient humidity of the food using a humidity sensor, measuring the packaging pressure of the food using a pressure sensor, measuring the number of microorganisms in the food environment using a microbial sensor, and measuring the oxygen content of the food environment using an oxygen sensor; and obtaining a negative evaluation value of food delivery quality at the relay node in the food delivery route through comprehensive analysis of the ambient temperature, ambient humidity, packaging pressure, number of microorganisms, and oxygen content.

[0013] Furthermore, the first logistics management of food delivery quality based on the first assessment result of food delivery quality specifically includes: if the negative assessment value of food delivery quality is less than the food delivery quality assessment threshold, then the food delivery route relay nodes and the food delivery routes passed through are recorded as green relay nodes; if the negative assessment value of food delivery quality is equal to or greater than the food delivery quality assessment threshold, then the current food delivery route relay node is recorded as a red relay node, and the current food delivery monitoring time period is recorded, the carbon dioxide concentration in the corresponding delivery environment is increased, a food quality early warning alarm is issued, and relevant personnel are notified to manually verify the corresponding food.

[0014] Furthermore, after the first logistics management of food delivery quality, a second evaluation of food delivery quality is conducted, specifically including: if the relay node in the food delivery route is marked as a green relay node, the markers on the food packaging are tracked and calculated to obtain the maximum displacement of the food packaging; if the maximum displacement of the food packaging is equal to or greater than the maximum displacement threshold of the food packaging, the current relay node in the food delivery route is marked as a red relay node, the current food delivery monitoring time period is recorded, a food quality early warning alarm is issued, and relevant personnel are notified to manually verify the corresponding food; if the maximum displacement of the food packaging is less than the maximum displacement threshold of the food packaging, the peak acceleration of the food environment vibration is measured by a vibration sensor, and the microbial parameters of the food environment are measured by a microbial sensor. The peak acceleration of the food environment vibration and the microbial parameters of the food environment are comprehensively analyzed to obtain the food delivery quality anomaly assessment value.

[0015] Furthermore, the second evaluation of food delivery quality after the first logistics management of food delivery quality also includes: obtaining a comprehensive evaluation value of food delivery quality through a comprehensive analysis of negative evaluation values ​​and anomaly evaluation values ​​of food delivery quality. The specific analysis is as follows: The relay nodes in the food delivery route are numbered sequentially, the food delivery monitoring time periods are numbered sequentially, and the food delivery types are numbered sequentially; the weighting factor for the negative evaluation value of food delivery quality is directly extracted from the food delivery warehousing and logistics management database, and the weighting factor for the anomaly evaluation value of food delivery quality is also directly extracted from the food delivery warehousing and logistics management database; the negative evaluation value of food delivery quality for different food delivery relay nodes in different food delivery monitoring time periods is multiplied by the corresponding weighting factor for the negative evaluation value of food delivery quality for the food delivery relay node in the food delivery route during the corresponding food delivery monitoring time period to obtain a weighted value of the negative evaluation value of food delivery quality; The weighted value of the food delivery quality anomaly assessment is obtained by multiplying the food delivery quality anomaly assessment value of different food delivery types for different food delivery monitoring time periods at different food delivery relay nodes in the same food delivery route by the corresponding weighting factor of the food delivery quality anomaly assessment value for the same food delivery monitoring time period. The maximum value of the food ambient temperature for each food type under the food delivery monitoring time period at the food delivery relay node is subtracted from the corresponding minimum value of the food ambient temperature, and the result is divided by the corresponding average value of the food ambient temperature to obtain the food ambient temperature fluctuation value. The comprehensive food delivery quality assessment value is obtained by analyzing the weighted value of the food delivery quality anomaly assessment, the weighted value of the negative food delivery quality assessment, and the food ambient temperature fluctuation value. The comprehensive food delivery quality assessment value is used to quantify the relative comprehensive negative degree of food delivery quality under different food delivery relay nodes at different food delivery monitoring time periods.

[0016] Furthermore, the second logistics management of food delivery quality based on the second evaluation result of food delivery quality specifically includes: if the comprehensive evaluation value of food delivery quality is less than the comprehensive evaluation threshold of food delivery quality, no adjustment is made; if the intermediate node in the food delivery route is the end node in the food delivery route, the food delivery stage ends; if the comprehensive evaluation value of food delivery quality is equal to or greater than the comprehensive evaluation threshold of food delivery quality, the current intermediate node in the food delivery route is marked as a yellow intermediate node, the corresponding food is returned to its original position through intelligent adjustment equipment, and the temperature and humidity are recalibrated and adjusted to the predefined temperature and humidity through temperature and humidity adjustment equipment.

[0017] Furthermore, the second logistics management of food delivery quality based on the second assessment result of food delivery quality also includes: if the comprehensive assessment value of food delivery quality is equal to or greater than the comprehensive assessment threshold of food delivery quality, after a predefined food delivery time, a second assessment of food delivery quality is conducted after the first logistics management of food delivery quality to obtain the current comprehensive assessment value of food delivery quality; if the current comprehensive assessment value of food delivery quality is less than the comprehensive assessment threshold of food delivery quality, no adjustment is made; if the intermediate node in the food delivery route is the end node in the food delivery route, the food delivery stage ends; if the current comprehensive assessment value of food delivery quality is equal to or greater than the comprehensive assessment threshold of food delivery quality, the current intermediate node in the food delivery route is recorded as a red intermediate node, and the current food delivery monitoring time period and food delivery type are recorded, a food quality early warning alarm is issued, and relevant personnel are notified to manually check the food delivery route, check the location of the corresponding food, and reinforce the food packaging.

[0018] This application provides an IoT-based food delivery, warehousing, and logistics management system, including a food quality self-inspection module, a food delivery self-inspection module, a food delivery quality first assessment module, and a food delivery quality second assessment module: The food quality self-inspection module performs self-inspection of the corresponding stored food quality; if the self-inspection result is passed, the food is prepared for outbound delivery. The food delivery self-inspection module performs self-inspection of the corresponding stored food to be delivered; if the self-inspection result is passed, the food is delivered. The food delivery quality first assessment module sets relay nodes in the food delivery route; when food is delivered to a relay node, a first food delivery quality assessment is performed, and first-level logistics management is performed based on the first-level assessment result. The food delivery quality second assessment module performs a second-level assessment after the first-level logistics management, and second-level logistics management is performed based on the second-level assessment result.

[0019] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0020] 1. This invention improves the accuracy of IoT-based food distribution, warehousing, and logistics management methods by conducting graded self-inspection before food distribution, graded evaluation of relay nodes along the food distribution route, and graded management and adjustment. This solves the problem of insufficient accuracy in existing IoT-based food distribution, warehousing, and logistics management methods.

[0021] 2. By conducting self-inspection of food quality and food delivery, and through rigorous testing, intelligent management, and standardized operations, comprehensive assurance of food quality is achieved, thereby improving the level of food delivery quality and safety.

[0022] 3. Based on the first assessment results of food delivery quality, we conduct first-level logistics management for food delivery quality and second-level logistics management based on the second assessment results of food delivery quality. We use IoT technology to monitor the status of food in real time, thereby promptly identifying potential problems. By evaluating food delivery quality through multiple parameters and using smart devices and systems for automated adjustments, we improve the efficiency of food logistics and delivery. Attached Figure Description

[0023] Figure 1 A flowchart illustrating an IoT-based food delivery, warehousing, and logistics management method provided in this application embodiment;

[0024] Figure 2 This is a structural diagram of an IoT-based food delivery, warehousing, and logistics management system provided in an embodiment of this application. Detailed Implementation

[0025] This application provides an IoT-based food distribution, warehousing, and logistics management method and system, which solves the problem of insufficient accuracy in existing IoT-based food distribution, warehousing, and logistics management methods. By conducting graded self-inspection before food distribution, graded evaluation of relay nodes along the food distribution route, and graded management and adjustment, the accuracy of IoT-based food distribution, warehousing, and logistics management methods is improved.

[0026] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0027] like Figure 1The diagram shown is a flowchart of an IoT-based food distribution, warehousing, and logistics management method provided in this application embodiment. This method is applied in an IoT-based food distribution, warehousing, and logistics management system and includes the following steps: conducting a self-inspection of the quality of the corresponding stored food; if the self-inspection result is passed, the food is prepared for outbound delivery; conducting a self-inspection of the food to be outbound for delivery; if the self-inspection result is passed, the food is outbound for delivery; setting relay nodes in the food outbound delivery route; when the food is outbound delivered to a certain relay node, performing a first evaluation of the food delivery quality; and performing first logistics management based on the first evaluation result; and performing a second evaluation of the food delivery quality based on the second evaluation result.

[0028] Furthermore, the corresponding stored ingredients will undergo self-inspection of their quality. Specifically, this includes: collecting and testing the corresponding stored ingredients according to a predefined storage ingredient plan to obtain the types of microbial units, the quantity of microbial units, pesticide residue values, and veterinary drug residue values ​​of the stored ingredients. If the types of microbial units are less than the threshold for microbial unit types, the quantity of microbial units is less than the threshold for the quantity of microbial units, the pesticide residue values ​​are less than the threshold for pesticide residues, and the veterinary drug residue values ​​are less than the threshold for veterinary drug residues, then the ingredients are ready for shipment. Otherwise, the ingredients cannot be ready for shipment, and relevant personnel will be notified for verification.

[0029] In this embodiment, microbial sampling and testing are performed on the food ingredients to check for indicators such as bacteria and mold. A test report is issued to ensure that the food ingredients meet hygiene standards. Rapid testing equipment (such as a pesticide residue detector) is used to sample and test the food ingredients. Test data is recorded to ensure compliance with food safety standards.

[0030] In addition to the parameters mentioned above, the predefined warehousing food solution includes: visual inspection, checking the appearance of the food for any signs of decay, spoilage, or mold, and confirming the integrity of the packaging without damage or leaks; temperature and humidity monitoring, using thermometers and hygrometers to ensure the warehouse temperature and humidity are within suitable ranges, and for refrigerated or frozen food, using a thermometer to measure the food's temperature; shelf-life check, verifying the production date and shelf-life on the food label to ensure the food is within its shelf life, and checking the shelf-life information against the warehouse management system to ensure data accuracy; weight and quantity verification, using electronic scales to weigh the food to ensure the weight meets standards, and counting the quantity to ensure consistency with the order; odor and taste check, judging the freshness of the food by smell and checking for any off-odors; label and traceability information check, checking the integrity and clarity of food labels, and using QR codes or traceability systems to query the source and distribution information of the food to ensure traceability; through these steps, the quality of the food delivered from the warehouse can be ensured, guaranteeing food safety and consumer health.

[0031] Specific examples of the types and quantities of microbial units in stored food are as follows: the types and quantities of microbial units per square millimeter of stored food can be obtained through equipment sampling and testing.

[0032] Furthermore, the corresponding warehoused ingredients prepared for outbound delivery undergo self-inspection. The specific process is as follows: The corresponding warehoused ingredients are collected and tested according to a predefined delivery plan to obtain the airtightness value of the packaging, the surface temperature of the ingredients, the estimated delivery time, the types and quantities of microorganisms in the corresponding vehicle environment. If the airtightness value of the packaging is less than the airtightness threshold, the quantity of microorganisms is less than the microorganism quantity threshold, the surface temperature is less than the surface temperature threshold, the estimated delivery time is less than the estimated delivery time threshold, the types of microorganisms in the corresponding vehicle environment are less than the vehicle environment microorganism type threshold, and the quantity of microorganisms in the corresponding vehicle environment is less than the vehicle environment microorganism quantity threshold, then the ingredients are allowed to be delivered. Otherwise, the ingredients cannot be delivered, and relevant personnel are notified for verification.

[0033] In this embodiment, the integrity of the food packaging is checked to ensure there are no problems such as breakage or air leakage. It should be noted that in practical applications, many foods are bagged and sealed after harvesting and washing, but not necessarily vacuum-packed. Therefore, the pressure difference method can be used, placing the food packaging in a pressure difference testing device to test the airtightness of the packaging by creating a pressure difference, and recording the pressure changes to determine the degree of airtightness.

[0034] Pre-cooling of stored food, that is, pre-cooling of food that needs to be refrigerated or frozen, can ensure that the food reaches the appropriate temperature when it leaves the warehouse.

[0035] Record the temperature of ingredients when they leave the warehouse to ensure they meet the requirements.

[0036] Check the cleanliness and hygiene of delivery vehicles to ensure they meet food safety standards.

[0037] Based on order addresses and traffic conditions, optimize delivery routes to improve delivery efficiency. The software also provides the estimated delivery time for warehoused ingredients based on the expected delivery routes.

[0038] Furthermore, when food ingredients are delivered to a certain intermediate node in the food ingredient delivery route, a first assessment of the food ingredient delivery quality is conducted. This assessment includes: measuring the ambient temperature of the food ingredient using a temperature sensor; measuring the ambient humidity of the food ingredient using a humidity sensor; measuring the packaging pressure of the food ingredient using a pressure sensor; measuring the number of microorganisms in the food ingredient environment using a microbial sensor; and measuring the oxygen content of the food ingredient environment using an oxygen sensor. A negative assessment value of the food ingredient delivery quality at the intermediate node in the food ingredient delivery route is obtained through a comprehensive analysis of the ambient temperature, ambient humidity, packaging pressure, number of microorganisms, and oxygen content.

[0039] In this embodiment, the ingredients can be arranged in layers, with each layer separated by a partition to ensure that the pressure on each layer of ingredients is uniform.

[0040] The relay nodes in the food delivery route are numbered sequentially, with PS0 representing the number of the relay node in the food delivery route, PS0 = 1, 2, ..., PS, and PS representing the total number of relay nodes in the food delivery route.

[0041] The food delivery monitoring time periods are numbered sequentially, with SC0 representing the number of the food delivery monitoring time period, SC0 = 1, 2, ..., SC, and SC representing the total number of food delivery monitoring time period numbers.

[0042] The food delivery categories are numbered sequentially, with ZL0 representing the food delivery category number, ZL0 = 1, 2, ..., ZL, and ZL representing the total number of food delivery category numbers.

[0043] This represents the negative evaluation value of food delivery quality for the SC0th food delivery monitoring time period at the PS0th food delivery relay node. The negative evaluation value of food delivery quality is used to quantify the relative negative degree of food delivery quality for different food delivery monitoring time periods under different food delivery relay nodes. The larger the negative evaluation value of food delivery quality, the higher the relative degree of negative environmental threat to actual food delivery.

[0044]

[0045] e represents the natural constant.

[0046] This represents the ambient temperature of the food during the SC0th food delivery monitoring period at the PS0th food delivery relay node. Excessively high temperatures may cause food spoilage or thawing, while excessively low temperatures may cause food to freeze.

[0047] This represents the standard value of the ambient temperature of the food at the PS0th food delivery relay node. The standard value of the ambient temperature of the food is directly extracted from the food delivery warehousing and logistics management database, set by prior knowledge of food delivery, or set independently by relevant personnel.

[0048] This represents the number of environmental microorganisms in the food during the SC0th food delivery monitoring period at the PS0th food delivery relay node. A higher number of environmental microorganisms indicates a higher risk of contamination and spoilage of the food.

[0049] WSWYZ represents the threshold for the number of microorganisms in the food environment. This threshold is directly extracted from the food distribution, warehousing, and logistics management database and is either set based on prior knowledge of food distribution or determined independently by relevant personnel.

[0050] This represents the ambient humidity of the food delivery type for the ZL0th food delivery category during the SC0th food delivery monitoring period at the PS0th food delivery relay node in the outbound delivery route.

[0051] This represents the standard value of the ambient humidity for the ZL0th food delivery category. The standard value of the ambient humidity is directly extracted from the food delivery warehousing and logistics management database, set by prior knowledge of food delivery, or set independently by relevant personnel.

[0052] Pressure sensors can detect changes in pressure inside packaging; leakage causes a pressure drop. By installing pressure sensors inside sealed containers and monitoring pressure changes, the leakage rate can be calculated. The closer the pressure is to the standard value for food packaging, the better the airtightness; conversely, the further away, the worse.

[0053] This represents the packaging pressure of the food delivery type for the ZL0th food delivery category during the SC0th food delivery monitoring period at the PS0th food delivery relay node in the outbound delivery route.

[0054] This represents the standard value of food packaging pressure for the ZL0th food delivery category. The standard value of food packaging pressure is directly extracted from the food delivery warehousing and logistics management database, set by prior knowledge of food delivery, or determined by relevant personnel.

[0055] This represents the environmental oxygen content correction factor at the PS0th food outbound delivery relay node. As the airtightness changes, the change in environmental oxygen content will also affect the oxidation rate of the food. The value range is (1, 2), which is used to represent the degree of influence of the environmental oxygen content on the oxidation rate of the food due to the change in airtightness. The environmental oxygen content correction factor is directly extracted from the food delivery, warehousing and logistics management database.

[0056] For example, an experiment can be designed to determine the oxidation rate of food under different environmental oxygen levels. This can be achieved by changing and controlling the environmental oxygen level, observing the degree of oxidation of the food over a certain period, and constructing a mapping set between environmental oxygen levels and corresponding correction factors. The real-time environmental oxygen level can be input into this mapping set to obtain the corresponding correction factors. The mapping relationship can be one-to-one or many-to-one.

[0057] This represents the food environmental temperature weighting factor of the PS0th food outbound delivery relay node. The food environmental temperature weighting factor is directly extracted from the food distribution, warehousing and logistics management database.

[0058] This represents the weighting factor of the number of microorganisms in the food environment at the PS0th food outbound delivery relay node. The weighting factor of the number of microorganisms in the food environment is directly extracted from the food distribution, warehousing and logistics management database.

[0059] Light can affect the surface temperature of food, thereby influencing microbial growth. Furthermore, ultraviolet radiation has a bactericidal effect, reducing the number of microorganisms on the surface of food.

[0060] For example, a mapping set of real-time light intensity and its corresponding food environment temperature weight factor and food environment microbial quantity weight factor can be constructed. The real-time light intensity is input into the mapping set to obtain its corresponding food environment temperature weight factor and food environment microbial quantity weight factor. The mapping relationship is either one-to-one or many-to-one.

[0061] Furthermore, based on the first assessment results of food delivery quality, the first logistics management of food delivery quality is carried out, specifically including: if the negative assessment value of food delivery quality is less than the food delivery quality assessment threshold, then the food outbound delivery and the relay nodes along the food outbound delivery route are marked as green relay nodes; if the negative assessment value of food delivery quality is equal to or greater than the food delivery quality assessment threshold, then the current food outbound delivery route relay node is marked as a red relay node, and the current food delivery monitoring time period is recorded, the carbon dioxide concentration in the corresponding delivery environment is increased, a food quality early warning alarm is issued, and relevant personnel are notified to manually verify the corresponding food.

[0062] In this embodiment, the relay nodes along the food outbound delivery route are recorded as green relay nodes. This means that the relay nodes along the food outbound delivery route are also recorded as green relay nodes. For example, if the food outbound delivery has reached the ninth food outbound delivery route relay node and the ninth food outbound delivery route relay node is recorded as a green relay node, then the previous eight food outbound delivery route relay nodes are also recorded as green relay nodes.

[0063] By monitoring the quality of food delivery in real time, potential problems can be identified promptly, preventing them from escalating. Red relay nodes and early warning alarms can alert relevant personnel to take swift action to prevent food spoilage or contamination.

[0064] Green relay nodes indicate high-quality food delivery, and these nodes can be prioritized for delivery, improving efficiency. Green relay nodes reduce the frequency of manual checks, saving labor costs. By promptly identifying and addressing problems, the risk of food spoilage and contamination can be reduced, ensuring food safety.

[0065] Data from green and red relay nodes can be used to analyze problems and identify improvement measures in the food delivery process. Marking relay nodes along the food delivery route as green or red and taking corresponding measures based on negative evaluation values ​​of food delivery quality can effectively improve food delivery quality, ensure food safety, and enhance customer satisfaction.

[0066] Furthermore, after the initial logistics management of food delivery quality, a second assessment of food delivery quality is conducted. This includes: if a relay node in the food delivery route is marked as a green relay node, the markers on the food packaging are tracked and calculated to obtain the maximum displacement of the food packaging; if the maximum displacement of the food packaging is equal to or greater than the maximum displacement threshold, the current relay node in the food delivery route is marked as a red relay node, the current food delivery monitoring period is recorded, a food quality early warning alarm is issued, and relevant personnel are notified to manually verify the corresponding food; if the maximum displacement of the food packaging is less than the maximum displacement threshold, the peak ground acceleration of the food environment is measured by a vibration sensor, and the microbial parameters of the food environment are measured by a microbial sensor. The peak ground acceleration of the food environment and the microbial parameters of the food environment are comprehensively analyzed to obtain an assessment value for food delivery quality anomalies.

[0067] In this embodiment, the marker can be an RFID tag. An RFID reader is used to track the displacement of the RFID tag, thereby calculating the maximum displacement of the food packaging.

[0068] In specific food delivery processes, even if the food itself is not contaminated or its freshness is maintained appropriately, fragile items (such as eggs and watermelons) are easily damaged during transportation due to squeezing and collisions. Insufficient protective measures, improper placement, or inadequate protection can easily lead to an increased breakage rate.

[0069] Vibration sensors can be installed on food packaging.

[0070] The relay nodes in the food delivery route are numbered sequentially, with PS0 representing the number of the relay node in the food delivery route, PS0 = 1, 2, ..., PS, and PS representing the total number of relay nodes in the food delivery route.

[0071] The food delivery monitoring time periods are numbered sequentially, with SC0 representing the number of the food delivery monitoring time period, SC0 = 1, 2, ..., SC, and SC representing the total number of food delivery monitoring time period numbers.

[0072] The food delivery categories are numbered sequentially, with ZL0 representing the food delivery category number, ZL0 = 1, 2, ..., ZL, and ZL representing the total number of food delivery category numbers.

[0073] This represents the food delivery quality anomaly assessment value for the ZL0 food delivery type during the ZL0th food delivery monitoring time period at the PS0th food delivery relay node. The food delivery quality anomaly assessment value is used to quantify the relative negative anomaly degree of food delivery quality at different food delivery monitoring time periods under different food delivery relay nodes. The larger the food delivery quality anomaly assessment value, the higher the relative degree of negative sudden impact of external environmental factors on the actual food delivery.

[0074]

[0075] e represents the natural constant.

[0076] This represents the peak environmental acceleration of the food delivery type during the monitoring period of the SC0th food delivery time at the PS0th food delivery relay node. It indicates the maximum acceleration value reached during the vibration process. High peak acceleration may cause instantaneous impact damage to the food.

[0077] This represents the historical average value of the peak environmental acceleration of food ingredients for the ZL0 food ingredient delivery category during the SC0th food ingredient delivery monitoring period at the PS0th food ingredient outbound delivery relay node. The historical average value of the peak environmental acceleration of food ingredients refers to the average value of the peak environmental acceleration of food ingredients in historical data, which is directly extracted from the food ingredient delivery warehousing and logistics management database.

[0078] This represents the maximum displacement of the food item of the ZL0th type during the SC0th food delivery monitoring time period at the PS0th food item outbound delivery relay node. It also refers to the maximum food item displacement reached during the vibration process.

[0079] This represents the maximum displacement threshold for the food packaging of the ZL0th food delivery category. The maximum displacement threshold for food packaging is directly extracted from the food delivery, warehousing, and logistics management database.

[0080] This represents the vibration transmission rate of the food packaging for the ZL0th food delivery category. It indicates the efficiency with which vibration is transmitted to the food through packaging or transportation equipment. A higher transmission rate means the food is more affected by vibration. The food packaging vibration transmission rate is directly extracted from the food delivery, warehousing, and logistics management database. The food packaging vibration transmission rate represents the proportion of environmental vibration transmitted to the food packaging. It can be obtained by conducting multiple vibration tests and averaging the results; the value range is (0, 1).

[0081] This represents the food packaging cushioning coefficient for the ZL0th food delivery category. It indicates how well appropriate packaging materials (such as pearl cotton, bubble wrap, etc.) can absorb impact forces during transportation and reduce vibration transmission. The food packaging cushioning coefficient is directly extracted from the food delivery warehousing and logistics management database. The food packaging cushioning coefficient represents the ratio of the vibration intensity experienced without packaging to the actual vibration intensity experienced due to packaging, with a value range of (1, 10).

[0082] This represents the maximum number of environmental microorganisms in the food delivery environment for the ZL0th food delivery type during the Z0th food delivery monitoring period at the PS0th food delivery relay node in the outbound delivery route.

[0083] This represents the minimum number of environmental microorganisms in the food delivery environment for the ZL0th food delivery type during the Z0th food delivery monitoring period at the PS0th food delivery relay node in the outbound delivery route.

[0084] This represents the average number of environmental microorganisms in the food delivery environment for the ZL0th food delivery type during the SC0th food delivery monitoring period at the PS0th food delivery relay node. The average number of environmental microorganisms is directly extracted from the food delivery warehousing and logistics management database.

[0085] This represents the peak environmental acceleration weighting factor of food environmental vibration during the SC0th food delivery monitoring period at the PS0th food outbound delivery relay node. The peak environmental acceleration weighting factor of food environmental vibration is directly extracted from the food delivery warehousing and logistics management database.

[0086] This represents the weight factor of the maximum displacement of the food during the SC0th food delivery monitoring period of the PS0th food delivery relay node. The weight factor of the maximum displacement of the food is directly extracted from the food delivery warehousing and logistics management database.

[0087] The hardness of food refers to its ability to resist external forces such as indentation, penetration, cutting, or friction. It is an important indicator of the physical properties of food and is closely related to its texture, taste, processing characteristics, and transportation and storage conditions. Hard foods generally have better resistance to vibration; therefore, their peak ground acceleration (PGA) weighting factor may be relatively low during delivery. Soft foods are easily damaged by vibration, such as deformation or cracking; therefore, their PGA weighting factor may be higher, requiring stricter vibration control. Hard foods are less prone to deformation during displacement and have relatively lower sensitivity to displacement; therefore, their maximum displacement weighting factor may be smaller. Soft foods are easily deformed during displacement and are more sensitive to displacement; therefore, their maximum displacement weighting factor may be larger, requiring stricter displacement control.

[0088] For example, a mapping set can be constructed that includes real-time predefined food hardness and its corresponding peak acceleration weight factor and maximum displacement weight factor of the food environment. The real-time predefined food hardness can be input into the mapping set to obtain its corresponding peak acceleration weight factor and maximum displacement weight factor of the food environment. The mapping relationship is either one-to-one or many-to-one.

[0089] Furthermore, after the first logistics management of food delivery quality, a second evaluation of food delivery quality is conducted, which includes: obtaining a comprehensive evaluation value of food delivery quality through a comprehensive analysis of negative evaluation values ​​and anomaly evaluation values. The specific analysis is as follows: The relay nodes in the food delivery route are numbered sequentially, the food delivery monitoring time periods are numbered sequentially, and the food delivery types are numbered sequentially; the weighting factors for the negative evaluation values ​​and anomaly evaluation values ​​of food delivery quality are directly extracted from the food delivery warehousing and logistics management database; the negative evaluation values ​​of food delivery quality for different relay nodes in the food delivery route and different food delivery monitoring time periods are multiplied by the corresponding weighting factors for the negative evaluation values ​​of food delivery quality for the food delivery route relay nodes in the food delivery route and different food delivery monitoring time periods to obtain a weighted value for the negative evaluation values ​​of food delivery quality; the anomaly evaluation values ​​of food delivery quality for different food delivery types for different relay nodes in the food delivery route and different food delivery monitoring time periods are multiplied by the corresponding weighting factors for the food delivery routes and different food delivery types in the food delivery route and different food delivery monitoring time periods. The weighted value of the food delivery quality anomaly assessment is obtained by considering the weighting factors of the food delivery quality anomaly assessment value during the food delivery monitoring period. The maximum value of the food's ambient temperature for each food type during the food delivery monitoring period at a relay node in the food delivery route is subtracted from the corresponding minimum value, and the result is divided by the corresponding average ambient temperature to obtain the food's ambient temperature fluctuation value. The comprehensive food delivery quality assessment value is obtained by analyzing the weighted value of the food delivery quality anomaly assessment, the weighted value of the negative food delivery quality assessment, and the food's ambient temperature fluctuation value. This comprehensive food delivery quality assessment value quantifies the relative overall negative degree of food delivery quality during different food delivery monitoring periods at different relay nodes in the food delivery route. A higher comprehensive food delivery quality assessment value indicates a higher overall relative degree of negative environmental threat to the actual food delivery. Based on the above information, the correlation between the comprehensive food delivery quality assessment value, the negative food delivery quality assessment value, and the food delivery quality anomaly assessment value is obtained by combining these two assessment values ​​through a weighted summation. Specifically, the comprehensive quality assessment value for food delivery is obtained by summing the negative quality assessment value and the anomaly assessment value for food delivery by multiplying them by their respective weighting factors. The negative quality assessment value reflects the degree of negative environmental impact on the food during delivery, while the anomaly assessment value reflects the degree of impact from sudden external factors. In this way, the comprehensive quality assessment value can more comprehensively reflect the overall quality status of the food during delivery, considering both continuous environmental impacts and sudden external impacts. This comprehensive assessment helps to more accurately identify and respond to various risks in the food delivery process, ensuring food safety.

[0090] This represents the negative evaluation value of food delivery quality during the SC0th food delivery monitoring period at the PS0th food delivery relay node in the outbound delivery route; This represents the food delivery quality anomaly assessment value for the ZL0 food delivery type during the ZL0th food delivery monitoring period at the PS0th food delivery relay node in the outbound delivery route. This represents the maximum ambient temperature of the food delivery type for the ZL0th food delivery category during the ZL0th food delivery monitoring period at the PS0th food delivery relay node in the outbound delivery route. This represents the minimum ambient temperature of the food delivery type for the ZL0th food delivery category during the ZL0th food delivery monitoring period at the PS0th food delivery relay node in the outbound delivery route. This represents the average ambient temperature of the food delivery type for the ZL0th food delivery category during the ZL0th food delivery monitoring period at the PS0th food delivery relay node in the outbound delivery route. This represents the negative evaluation value weight factor of the food delivery quality at the PS0th food delivery relay node. The negative evaluation value weight factor of the food delivery quality is directly extracted from the food delivery warehousing and logistics management database. This represents the weighting factor of the food delivery quality anomaly assessment value at the PS0th food delivery relay node in the outbound delivery route. The weighting factor of the negative food delivery quality assessment value is directly extracted from the food delivery warehousing and logistics management database.

[0091] In this embodiment, significant temperature changes, especially those exceeding the suitable storage temperature range for food ingredients, can lead to a decline in food quality, thereby increasing the negative evaluation value. For example, high temperatures may cause food spoilage and bacterial growth, while low temperatures may cause food to freeze and lose nutrients. Significant temperature changes may also cause changes in food ingredients, such as changes in color, deterioration in taste, and loss of nutrients, thereby increasing the change evaluation value.

[0092] Light intensity affects the color and nutritional content of food. Excessive light can accelerate surface oxidation and color changes, increasing the risk of adverse reaction.

[0093] For example, a mapping set is constructed that includes real-time light intensity and its corresponding negative evaluation value weight factor and abnormal evaluation value weight factor for food delivery quality. The real-time light intensity is input into the mapping set to obtain its corresponding negative evaluation value weight factor and abnormal evaluation value weight factor for food delivery quality. The mapping relationship is either one-to-one or many-to-one.

[0094] Furthermore, based on the second assessment results of food delivery quality, second logistics management of food delivery quality is carried out, specifically including: if the comprehensive assessment value of food delivery quality is less than the comprehensive assessment threshold of food delivery quality, no adjustment is made; if the intermediate node in the food delivery route is the end node in the food delivery route, the food delivery stage ends; if the comprehensive assessment value of food delivery quality is equal to or greater than the comprehensive assessment threshold of food delivery quality, the current intermediate node in the food delivery route is marked as a yellow intermediate node, and the corresponding food is returned to its original position through intelligent adjustment equipment, and the temperature and humidity are recalibrated and adjusted to the predefined temperature and humidity through temperature and humidity adjustment equipment.

[0095] In this embodiment, intelligent adjustment devices are used to position the corresponding ingredients. For example, an automated handling robot is installed inside the transport vehicle to adjust the placement of the ingredients according to instructions, thereby reducing the impact of vibration. Adjustable packaging materials or structures are used to automatically adjust the tightness or shape of the packaging according to instructions, providing better support and cushioning. Adjustment devices, such as movable partitions or brackets, are installed on the transport vehicle to automatically adjust the way the ingredients are secured according to instructions.

[0096] Temperature-controlled compartments and humidity control systems are used to ensure that food is transported under suitable temperature and humidity conditions.

[0097] Use refrigeration or heating equipment to adjust the ambient temperature according to the needs of the ingredients.

[0098] Refrigeration equipment: compression refrigeration units, absorption refrigeration units, evaporative condensers; heating equipment: electric heaters, fuel oil heaters; humidity control equipment: humidifiers, dehumidifiers.

[0099] Furthermore, the second logistics management of food delivery quality based on the second assessment results of food delivery quality also includes: if the comprehensive assessment value of food delivery quality is equal to or greater than the comprehensive assessment threshold of food delivery quality, after a predefined food delivery time, a second assessment of food delivery quality is conducted after the first logistics management of food delivery quality to obtain the current comprehensive assessment value of food delivery quality; if the current comprehensive assessment value of food delivery quality is less than the comprehensive assessment threshold of food delivery quality, no adjustment is made; if the intermediate node in the food delivery route is the end node in the food delivery route, the food delivery stage ends; if the current comprehensive assessment value of food delivery quality is equal to or greater than the comprehensive assessment threshold of food delivery quality, the current intermediate node in the food delivery route is marked as a red intermediate node, and the current food delivery monitoring time period and food delivery type are recorded, a food quality early warning alarm is issued, and relevant personnel are notified to manually check the food delivery route, check the location of the corresponding food, and reinforce the food packaging.

[0100] In this embodiment, for example, high-performance shockproof packaging materials, such as air cushion film and foam plastic, are used to reduce the direct impact of vibration on the food.

[0101] We use professional cargo securing devices, such as straps and racks, to ensure that the food does not move during transportation.

[0102] Using advanced route optimization algorithms, considering road conditions, traffic conditions, and food characteristics, the most suitable delivery route is planned.

[0103] like Figure 2 As shown in the diagram, the IoT-based food distribution, warehousing, and logistics management system provided in this application embodiment includes: a food quality self-inspection module, a food distribution self-inspection module, a food distribution quality first assessment module, and a food distribution quality second assessment module. The food quality self-inspection module is used to perform self-inspection of the corresponding stored food quality. If the food quality self-inspection result is passed, the food is prepared for outbound distribution. The food distribution self-inspection module is used to perform self-inspection of the corresponding stored food prepared for outbound distribution. If the food distribution self-inspection result is passed, the food is outbound distribution. The food distribution quality first assessment module is used to set relay nodes in the food outbound distribution route. When the food is outbound distributed to a certain food outbound distribution route relay node, a first food distribution quality assessment is performed, and first food distribution quality logistics management is performed based on the first food distribution quality assessment result. The food distribution quality second assessment module is used to perform a second food distribution quality assessment after the first food distribution quality logistics management, and second food distribution quality logistics management is performed based on the second food distribution quality assessment result.

[0104] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0105] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0106] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0107] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0108] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0109] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for food distribution, warehousing, and logistics management based on the Internet of Things, characterized in that: Includes the following steps: The corresponding stored ingredients undergo self-inspection for quality. If the self-inspection results are satisfactory, the ingredients are ready for shipment. The corresponding warehouse ingredients to be shipped out will undergo self-inspection. If the self-inspection results are satisfactory, the ingredients will be shipped out. Set up relay nodes in the food outbound delivery route. When the food outbound delivery reaches a certain food outbound delivery route relay node, conduct a first evaluation of food delivery quality, and conduct first-level logistics management of food delivery quality based on the results of the first evaluation of food delivery quality. The first assessment of food delivery quality is conducted when food is delivered to a relay node in the food delivery route. This assessment specifically includes: The ambient temperature of the food is obtained by measuring the ambient temperature of the food using a temperature sensor, the ambient humidity of the food is obtained by measuring the ambient humidity of the food using a humidity sensor, the packaging pressure of the food is obtained by measuring the packaging pressure of the food using a pressure sensor, the number of microorganisms in the food environment is obtained by measuring the number of microorganisms in the food environment using a microbial sensor, and the oxygen content of the food environment is obtained by measuring the number of microorganisms in the food environment using an oxygen sensor. The negative evaluation value of food delivery quality at relay nodes in the food delivery route is obtained by comprehensively analyzing the food environment temperature, food environment humidity, food packaging pressure, food environment microbial quantity and food environment oxygen content. The aforementioned food delivery quality-first logistics management based on the first assessment results of food delivery quality specifically includes: If the negative evaluation value of food delivery quality is less than the food delivery quality evaluation threshold, then the food outbound delivery and the relay nodes along the food outbound delivery route will be recorded as green relay nodes. If the negative evaluation value of food delivery quality is equal to or greater than the food delivery quality evaluation threshold, the current food outbound delivery route relay node will be marked as a red relay node, and the current food delivery monitoring time period will be recorded. The carbon dioxide concentration in the corresponding delivery environment will be increased, a food quality early warning alarm will be issued, and relevant personnel will be notified to manually check the corresponding food. After the first logistics management of food delivery quality, a second evaluation of food delivery quality is conducted, and second logistics management of food delivery quality is carried out based on the results of the second evaluation.

2. The method for food distribution, warehousing, and logistics management based on the Internet of Things as described in claim 1, characterized in that, The process of conducting self-inspection of the quality of the corresponding stored ingredients specifically includes: The corresponding stored food was collected and tested according to the predefined stored food plan to obtain the types of microbial units, the number of microbial units, the pesticide residue value, and the veterinary drug residue value of the stored food. If the number of microbial units in the stored food is less than the threshold for the number of microbial units in the stored food, the number of microbial units in the stored food is less than the threshold for the number of microbial units in the stored food, the pesticide residue value in the stored food is less than the threshold for pesticide residue in the stored food, and the veterinary drug residue value in the stored food is less than the threshold for veterinary drug residue in the stored food, then the food is ready for shipment. Otherwise, the ingredients cannot be prepared for shipment and relevant personnel cannot be notified for verification.

3. The method for food distribution, warehousing, and logistics management based on the Internet of Things as described in claim 1, characterized in that, The process of conducting self-inspection of the corresponding warehouse ingredients prepared for outbound delivery is as follows: The corresponding stored food is collected and tested according to the predefined food delivery plan to obtain the airtightness value of the food packaging, the surface temperature of the food, the estimated delivery time of the food, the types and quantities of microorganisms in the vehicle environment corresponding to the food. If the airtightness value of the storage food packaging is less than the airtightness threshold of the storage food packaging, the number of microbial units in the storage food is less than the threshold of the number of microbial units in the storage food, the surface temperature of the storage food is less than the threshold of the surface temperature of the storage food, the estimated delivery time of the storage food is less than the threshold of the estimated delivery time of the storage food, the types of microbial units in the corresponding vehicle environment are less than the threshold of the types of microbial units in the vehicle environment, and the number of microbial units in the corresponding vehicle environment is less than the threshold of the number of microbial units in the vehicle environment, then the food will be shipped out. Otherwise, the ingredients cannot be shipped out and relevant personnel will be notified for verification.

4. The Internet of Things-based food delivery, warehousing, and logistics management method as described in claim 3, characterized in that, Following the initial logistics management of food delivery quality, a second evaluation of food delivery quality is conducted, specifically including: If the relay node in the food delivery route is marked as a green relay node, the maximum displacement of the food packaging can be obtained by tracking and calculating the markers on the food packaging. If the maximum displacement of the food packaging is equal to or greater than the maximum displacement threshold of the food packaging, then the current food outbound delivery route relay node is marked as a red relay node, and the current food delivery monitoring time period is recorded. A food quality early warning alarm is issued and relevant personnel are notified to manually check the corresponding food. If the maximum displacement of the food packaging is less than the maximum displacement threshold of the food packaging, the peak acceleration of the food environment is measured by a vibration sensor, and the microbial parameters of the food environment are measured by a microbial sensor. By comprehensively analyzing the peak acceleration of the food environment vibration and the microbial parameters of the food environment, an assessment value for the quality change of food delivery is obtained.

5. The Internet of Things-based food delivery, warehousing, and logistics management method as described in claim 4, characterized in that, The second evaluation of food delivery quality, following the initial logistics management, also includes: The comprehensive evaluation value of food delivery quality is obtained by combining the negative evaluation value and the abnormal evaluation value of food delivery quality. The specific analysis is as follows: The relay nodes in the food delivery route are numbered sequentially, the food delivery monitoring time periods are numbered sequentially, and the types of food delivered are numbered sequentially. The weighting factor for the negative evaluation value of food delivery quality is directly extracted from the food delivery warehousing and logistics management database. The weighting factor for the anomaly evaluation value of food delivery quality is also directly extracted from the food delivery warehousing and logistics management database. The negative evaluation value of food delivery quality for different food delivery monitoring time periods at different food delivery relay nodes in the food delivery route is multiplied by the corresponding weighting factor for the negative evaluation value of food delivery quality at the food delivery relay node in the food delivery route during the food delivery monitoring time period to obtain the weighted value of the negative evaluation value of food delivery quality. The weighted value of the food delivery quality variation assessment is obtained by multiplying the food delivery quality variation assessment value of different types of food delivery at different food delivery monitoring time periods at different relay nodes in the food delivery route, by the weighting factor of the food delivery quality variation assessment value of the corresponding food delivery monitoring time period. The maximum value of the ambient temperature of the food delivery type under the food delivery monitoring time period under the relay node of the food delivery route is subtracted from the minimum value of the corresponding ambient temperature of the food delivery type, and the resulting value is divided by the average value of the corresponding ambient temperature of the food to obtain the value of the fluctuation of the ambient temperature of the food. The comprehensive evaluation value of food delivery quality is obtained by analyzing the weighted values ​​of the quality variation assessment value, the negative assessment value of food delivery quality, and the fluctuation value of the ambient temperature of the food. The comprehensive evaluation value of food delivery quality is used to quantify the relative overall negative degree of food delivery quality at different food delivery monitoring time periods under different food delivery relay nodes in the food delivery route.

6. The Internet of Things-based food delivery, warehousing, and logistics management method as described in claim 5, characterized in that, The second logistics management of food delivery quality based on the second assessment results of food delivery quality specifically includes: If the overall quality assessment value of food delivery is less than the overall quality assessment threshold of food delivery, no adjustment will be made; If the intermediate node in the food delivery route is the end node in the food delivery route, then the food delivery phase ends. If the comprehensive evaluation value of food delivery quality is equal to or greater than the comprehensive evaluation threshold of food delivery quality, the current food delivery route relay node will be marked as a yellow relay node. The corresponding food will be returned to its original position through intelligent adjustment equipment, and the temperature and humidity will be recalibrated and adjusted to the predefined temperature and humidity through temperature and humidity adjustment equipment.

7. The Internet of Things-based food delivery, warehousing, and logistics management method as described in claim 6, characterized in that, The second logistics management of food delivery quality based on the second assessment results of food delivery quality also includes: If the comprehensive evaluation value of food delivery quality is equal to or greater than the comprehensive evaluation threshold of food delivery quality, after a predefined food delivery time, the first logistics management of food delivery quality is carried out again, followed by the second evaluation of food delivery quality, to obtain the current comprehensive evaluation value of food delivery quality. If the intermediate node in the food delivery route is the end node in the food delivery route, then the food delivery phase ends. If the current comprehensive evaluation value of food delivery quality is less than the comprehensive evaluation threshold of food delivery quality, no adjustment will be made; If the current comprehensive quality assessment value of food delivery is equal to or greater than the comprehensive quality assessment threshold of food delivery, then the current food delivery route relay node will be marked as a red relay node, and the current food delivery monitoring time period and food delivery type will be recorded. A food quality early warning alarm will be issued and relevant personnel will be notified to manually check the food delivery route, check the location of the corresponding food, and reinforce the food packaging.

8. An Internet of Things (IoT)-based food distribution, warehousing, and logistics management system, employing the IoT-based food distribution, warehousing, and logistics management method as described in any one of claims 1-7, characterized in that, It includes a food quality self-inspection module, a food delivery self-inspection module, a food delivery quality first assessment module, and a food delivery quality second assessment module. Food quality self-inspection module: Used to perform self-inspection of the quality of the corresponding stored food. If the food quality self-inspection result is passed, the food is ready to be shipped out. Food delivery self-inspection module: Used to perform food delivery self-inspection on the corresponding warehouse food that is ready for outbound delivery. If the food delivery self-inspection result is passed, the food will be delivered. The first quality assessment module for food delivery is used to set up relay nodes in the food delivery route. When food is delivered to a certain food delivery route relay node, the first quality assessment of food delivery is carried out, and the first logistics management of food delivery quality is carried out based on the results of the first quality assessment. The second evaluation module for food delivery quality is used to conduct a second evaluation of food delivery quality after the first logistics management of food delivery quality, and to conduct second logistics management of food delivery quality based on the results of the second evaluation.

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