Visual monitoring system and method

Abstract

The invention discloses a visual monitoring system and method, and the system comprises a temperature and humidity monitoring module, a transportation path optimization module, a cargo state monitoring module, a cold chain breakage detection module, an artificial intelligence optimization scheduling module, a temperature control equipment intelligent optimization module, a cargo life cycle tracing module, and an intelligent abnormal event prediction and response module. According to the cold-chain logistics system, multiple advanced technologies (such as AI, Internet of Things, RFID and big data) are comprehensively applied, many problems in an existing cold-chain logistics system can be solved, the monitoring precision and real-time performance are improved, the transportation path and resource scheduling are optimized, and the transportation efficiency is improved. And the integrity and safety of cold chain transportation are ensured. Compared with the prior art, the system has stronger data integration capability, a more intelligent abnormity early warning mechanism and more efficient resource utilization efficiency, and brings remarkable technical progress for the cold-chain logistics industry.

Description

Technical Field

[0001] The present invention relates to the technical field of visual monitoring of cold chain logistics, and in particular to a visual monitoring system and method. Background Art

[0002] The difference between cold chain logistics and other logistics methods is that it requires special refrigeration and transportation methods. Cold chain logistics not only meets people's demand for fresh food, but also strives to minimize food loss and waste during transportation. Therefore, cold chain logistics has entered the food manufacturing industry and the food trade industry. The social effect it brings is to bring the best fresh food into ordinary people's homes. The cold chain logistics process is to use cold storage as the starting point and transportation as the link to form a sunrise industry that is just beginning to rise. During cold chain transportation, cold chain logistics monitoring is required.

[0003] Although there are a number of cold chain logistics visual monitoring systems on the market, these systems usually have some defects and deficiencies, resulting in unsatisfactory results in practical applications:

[0004] The existing system only relies on a single sensor or data source (such as temperature and humidity sensors), lacking comprehensive and real-time data integration of all links in cold chain transportation. The system often does not fully integrate data from transportation, warehousing to distribution, resulting in information fragmentation and difficulty in forming global decision support;

[0005] Although some existing cold chain monitoring systems have path planning functions, most of them can only select routes based on simple traffic information. They lack dynamic adaptation and in-depth analysis of complex traffic conditions, weather changes, and the characteristics of different goods, resulting in rough route selection and optimization solutions that cannot effectively reduce transportation time and temperature fluctuations;

[0006] During cold chain transportation, cold chain break detection systems can usually only rely on limited sensors or physical monitoring methods to determine whether the cold chain has been interrupted, but lack a comprehensive and real-time verification mechanism. For example, existing cold chain monitoring systems may not be able to combine satellite positioning and sensor networks in a timely manner, and cannot accurately identify cold chain integrity issues on the transportation path, and are prone to missing chain break events. Summary of the invention

[0007] The purpose of the present invention is to provide a visual monitoring system and method to solve the problems raised in the above background technology.

[0008] To achieve the above purpose, a visual monitoring system includes a temperature and humidity monitoring module, a transportation route optimization module, a cargo status monitoring module, a cold chain break detection module, an artificial intelligence optimization scheduling module, a temperature control equipment intelligent optimization module, a cargo life cycle tracing module, and an intelligent abnormal event prediction and response module;

[0009] The temperature and humidity monitoring module is used to monitor the temperature and humidity during cold chain transportation in real time;

[0010] The transport path optimization module is used to optimize transport paths and routes, reduce transport time, reduce transport costs, and avoid unnecessary delays;

[0011] The cold chain break detection module is used to detect whether there is an interruption or failure in cold chain transportation, and to discover and handle abnormalities in a timely manner;

[0012] The artificial intelligence optimization scheduling module is used to optimize the scheduling of transportation and warehousing according to real-time data through artificial intelligence algorithms, ensure the maximum utilization of transportation resources, reduce empty loads or resource waste, and respond to emergencies;

[0013] The temperature control equipment intelligent optimization module is used to optimize the performance of the temperature control equipment and reduce the risk of equipment failure;

[0014] The cargo life cycle traceability module is used to record and trace data for each link in the cold chain transportation process, ensuring that each link from departure to arrival of the cargo can be traced, timely discovering potential problems and providing comprehensive compliance checks;

[0015] The intelligent abnormal event prediction and response module is used to predict abnormal events in the transportation process through intelligent algorithms, identify potential risks in advance, and take timely measures to prevent accidents. The intelligent abnormal event prediction and response module includes an abnormal event prediction unit and an adaptive response unit;

[0016] The abnormal event prediction unit is used to predict possible abnormal events by analyzing historical data and real-time monitoring data;

[0017] The adaptive response unit is used to automatically adjust the transportation plan, dispatch resources, or trigger a corresponding emergency response mechanism after predicting an abnormal event.

[0018] Preferably, the temperature and humidity monitoring module includes a real-time temperature and humidity acquisition unit and an intelligent early warning unit;

[0019] The real-time temperature and humidity acquisition unit is used to obtain the temperature and humidity data of the goods in the cold chain transportation process in real time by integrating multiple sensors;

[0020] The intelligent early warning unit is used to automatically issue an early warning and notify relevant personnel when the temperature and humidity data exceed the set threshold.

[0021] Preferably, the transport path optimization module includes a real-time location tracking unit and a transport path optimization unit;

[0022] The real-time location tracking unit is used to achieve real-time location tracking of cold chain transportation vehicles by combining a satellite positioning system and a geographic information system;

[0023] The transport route optimization unit is used to analyze vehicle driving data and cargo characteristic factors, optimize driving routes, reduce transportation time, and reduce temperature fluctuations.

[0024] Preferably, the cargo status monitoring module includes an internal and external environment synchronous monitoring unit and a cold chain risk assessment unit;

[0025] The internal and external environment synchronous monitoring unit is used to monitor the temperature inside the goods and monitor changes in the external environment during the cold chain logistics process;

[0026] The cold chain risk assessment unit is used to assess the risk level of the cold chain according to the type of goods, transportation method and monitoring data.

[0027] Preferably, the cold chain break detection module includes a physical break detection unit and a cold chain integrity verification unit;

[0028] The physical chain break detection unit is used to monitor each link in the cold chain system through sensors to detect in real time whether there is equipment failure or chain break;

[0029] The cold chain integrity verification unit is used to use a distributed sensor network, combined with satellite positioning and sensor data, to verify the integrity of cold chain transportation in real time.

[0030] Preferably, the artificial intelligence optimization scheduling module includes a dynamic scheduling unit and a predictive scheduling unit;

[0031] The dynamic scheduling unit is used to automatically schedule the most suitable vehicles and storage resources according to transportation demand, cold chain equipment status and traffic conditions;

[0032] The forecasting and scheduling unit is used to forecast transportation demand and resource scheduling using historical data, and make adjustments and resource allocations in advance.

[0033] Preferably, the temperature control device intelligent optimization module includes a temperature control device status diagnosis unit and a temperature control adjustment optimization unit;

[0034] The temperature control equipment status diagnosis unit is used to monitor the working status of the temperature control equipment during cold chain transportation in real time;

[0035] The temperature control optimization unit is used to automatically adjust the working parameters of the temperature control equipment during transportation to keep the temperature within the most suitable range.

[0036] Preferably, the cargo life cycle tracing module includes a transportation process tracing unit and a life cycle analysis unit;

[0037] The transport process tracing unit is used to track the goods throughout the entire process through RFID tags and sensors, and record the temperature and humidity data of each link as well as the transport route;

[0038] The life cycle analysis unit is used to analyze the life cycle of the goods by combining the transportation process data, environmental data and goods characteristics, and predict the possible damage or quality degradation period.

[0039] A working method of a visual monitoring system according to any one of the above items comprises the following steps:

[0040] S1. The system collects temperature and humidity data of goods and the environment in the cold chain transportation process in real time through integrated multiple sensors. Temperature and humidity monitoring equipment is deployed in each transportation link (refrigerated trucks, warehouses, loading and unloading areas, etc.). Once the temperature and humidity data exceeds the preset threshold range, the system analyzes and triggers the early warning mechanism through intelligent algorithms. The system will display the abnormality through a visual interface, and relevant personnel will receive notifications and be able to make timely adjustments.

[0041] S2. The system combines satellite positioning (GPS) and geographic information system (GIS) to track the location of transport vehicles in real time. The real-time location, transport speed and estimated arrival time of the vehicle will be displayed on the visual interface. The system automatically optimizes the transport route by analyzing real-time data (such as traffic conditions, weather changes, traffic accidents, etc.) and combining the characteristics of the goods (such as transportation requirements, temperature control requirements, etc.). The system automatically selects the shortest and most suitable transport route to reduce time, reduce costs and keep temperature fluctuations to a minimum;

[0042] S3. The system monitors the status of the equipment in real time through sensors installed in various links of the cold chain (such as temperature control equipment sensors, door switch sensors, etc.). If a link has equipment failure or chain break (such as the refrigerated truck door is not closed or the temperature control equipment stops working), the system will detect and issue a warning in real time. The system uses a distributed sensor network and satellite positioning system to verify the integrity of the cold chain in the transportation path. Through data analysis, the system can determine whether the cold chain transportation meets the standards and promptly discover potential cold chain break risks;

[0043] S4. The system automatically dispatches the most suitable transport vehicles and storage resources based on real-time transport demand, vehicle status, storage conditions and traffic data using artificial intelligence algorithms. The system predicts transport demand in advance by analyzing historical data, demand trends and seasonal changes. Combined with real-time data, the system optimizes the dispatching strategy to ensure the rational allocation of transport and storage resources.

[0044] S5. The operating status of temperature control equipment (such as refrigerated trucks, cold storage temperature control equipment, etc.) is monitored in real time through sensors. Information such as equipment failure and abnormal alarms will be transmitted to the system in real time for staff to repair or replace in time. The system automatically adjusts the working status of the temperature control equipment based on real-time environmental data and cargo temperature control requirements. According to temperature fluctuations during transportation, the system will optimize the equipment operating parameters to ensure that the cargo is always in the optimal temperature range;

[0045] S6. The system uses RFID tags and sensors to automatically record the data of each link in the transportation process (such as temperature and humidity, location, time, etc.). Each link (loading, transportation, unloading) will generate a detailed data log to ensure the traceability of the goods status. The system combines the transportation process data, environmental data and goods characteristics to conduct life cycle analysis. Based on the data, the system can predict the period when the goods may be damaged or the quality will decline, and provide early warnings to managers;

[0046] S7. The system uses intelligent algorithms to analyze historical data and real-time monitoring data to predict abnormal events that may occur during cold chain transportation (such as equipment failure, temperature control failure, traffic accidents, etc.). The system will generate an abnormal prediction report and conduct a risk assessment of the transportation links in the next few hours or days. Once an abnormal event is predicted, the system will automatically activate the emergency response mechanism.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] 1. Through the temperature and humidity monitoring module, the system of the present invention can monitor the temperature and humidity conditions in the cold chain transportation process in real time. Once the set threshold is exceeded, the early warning mechanism is immediately triggered, which can effectively prevent the temperature control failure from having an adverse effect on the quality of the goods, especially for fresh food, medicine and other goods with strict requirements on temperature and humidity.

[0049] 2. The transportation path optimization module of the present invention automatically optimizes the transportation route according to real-time traffic conditions, weather changes and cargo requirements, reduces transportation time and temperature fluctuations, can reduce transportation costs, improve transportation efficiency, and ensure that the goods maintain the best temperature control state during transportation.

[0050] 3. The present invention uses a cold chain break detection module, and the system can monitor the status of each link in the cold chain in real time, detect cold chain interruptions or equipment failures in a timely manner, and avoid cargo quality problems caused by cold chain breaks. The module ensures the stability and continuity of the cold chain system through physical chain break detection and integrity verification.

[0051] 4. The artificial intelligence optimization and scheduling module of the present invention automatically schedules the most suitable transportation and storage resources based on real-time data and historical data, which can maximize the utilization of transportation resources, reduce empty loads and resource waste, optimize the coordination of storage and transportation, and reduce operating costs. The temperature control equipment intelligent optimization module monitors the equipment status and adjusts the temperature control parameters to ensure that the temperature control equipment is always in the best working state. This can not only extend the service life of the equipment, but also ensure that the goods are always in the ideal storage temperature range.

[0052] 5. The cargo life cycle tracing module of the present invention uses RFID tags and sensors to comprehensively record every link in the cold chain transportation process, ensuring the traceability of the cargo status, helping managers to monitor quality, and quickly trace the source of problems when they occur, ensuring that cold chain transportation meets compliance requirements.

[0053] 6. The intelligent abnormal event prediction and response module of the present invention can predict potential abnormal events in advance by analyzing historical data and real-time data, and timely adjust transportation plans or initiate emergency response measures, which can effectively prevent accidents and respond quickly to emergencies to reduce risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 This is a schematic diagram of the system of the present invention. DETAILED DESCRIPTION

[0055] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] See also Figure 1 The present invention provides a technical solution: a visual monitoring system and method, characterized in that it includes a temperature and humidity monitoring module, a transportation path optimization module, a cargo status monitoring module, a cold chain break detection module, an artificial intelligence optimization scheduling module, a temperature control equipment intelligent optimization module, a cargo life cycle tracing module and an intelligent abnormal event prediction and response module.

[0057] The temperature and humidity monitoring module is used to monitor the temperature and humidity during cold chain transportation in real time. The temperature and humidity monitoring module includes a real-time temperature and humidity acquisition unit and an intelligent early warning unit; the real-time temperature and humidity acquisition unit is used to integrate multiple sensors to obtain real-time temperature and humidity data of goods during cold chain transportation; the intelligent early warning unit is used when the temperature and humidity data exceeds the set threshold. The system can automatically issue an early warning and notify relevant personnel.

[0058] The transport path optimization module is used to optimize transport paths and routes, reduce transport time, reduce transport costs, and avoid unnecessary delays. The transport path optimization module includes a real-time location tracking unit and a transport path optimization unit; the real-time location tracking unit is used to achieve real-time location tracking of cold chain transport vehicles through the combination of satellite positioning system and geographic information system; the transport path optimization unit is used to analyze vehicle driving data and cargo characteristic factors, optimize driving routes, reduce transportation time, and reduce temperature fluctuations.

[0059] The cargo status monitoring module is used to monitor various key states of the cargo during transportation in real time. The cargo status monitoring module includes an internal and external environment synchronous monitoring unit and a cold chain risk assessment unit; the internal and external environment synchronous monitoring unit is used to monitor the temperature inside the cargo and monitor changes in the external environment during the cold chain logistics process; the cold chain risk assessment unit is used to assess the risk level of the cold chain based on the type of cargo, mode of transportation and monitoring data.

[0060] The cold chain break detection module is used to detect whether there is any interruption or failure in the cold chain transportation, and to promptly discover and handle the anomalies. The cold chain break detection module includes a physical break detection unit and a cold chain integrity verification unit; the physical break detection unit is used to monitor each link in the cold chain system through sensors, and detect in real time whether there is equipment failure or chain break; the cold chain integrity verification unit is used to use a distributed sensor network, combined with satellite positioning and sensor data, to verify the integrity of the cold chain transportation in real time.

[0061] The artificial intelligence optimization scheduling module is used to optimize the transportation and warehousing scheduling arrangements based on real-time data through artificial intelligence algorithms, ensure the maximum utilization of transportation resources, reduce empty loads or resource waste, and respond to emergencies. The artificial intelligence optimization scheduling module includes a dynamic scheduling unit and a predictive scheduling unit; the dynamic scheduling unit is used to automatically schedule the most suitable vehicles and storage resources based on transportation demand, cold chain equipment status and traffic conditions; the predictive scheduling unit is used to use historical data to predict transportation demand and resource scheduling, and make adjustments and resource allocation in advance.

[0062] The temperature control equipment intelligent optimization module is used to optimize the performance of the temperature control equipment and reduce the risk of equipment failure. The temperature control equipment intelligent optimization module includes a temperature control equipment status diagnosis unit and a temperature control adjustment optimization unit; the temperature control equipment status diagnosis unit is used to monitor the working status of the temperature control equipment during cold chain transportation in real time; the temperature control adjustment optimization unit is used to automatically adjust the working parameters of the temperature control equipment during transportation to keep the temperature in the most appropriate range.

[0063] The cargo life cycle traceability module is used to record and trace data for each link in the cold chain transportation process, ensuring that each link from departure to arrival of the cargo can be traced, timely discovering potential problems, and providing comprehensive compliance checks. The cargo life cycle traceability module includes a transportation process traceability unit and a life cycle analysis unit; the transportation process traceability unit is used to track the cargo throughout the entire process through RFID tags and sensors, recording the temperature and humidity data of each link and the transportation route; the life cycle analysis unit is used to combine the transportation process data, environmental data and cargo characteristics to analyze the life cycle of the cargo and predict possible damage or quality degradation periods.

[0064] The intelligent abnormal event prediction and response module is used to predict abnormal events in the transportation process through intelligent algorithms, identify potential risks in advance, and take timely measures to prevent accidents. The intelligent abnormal event prediction and response module includes an abnormal event prediction unit and an adaptive response unit; the abnormal event prediction unit is used to predict possible abnormal events by analyzing historical data and real-time monitoring data; the adaptive response unit is used to automatically adjust the transportation plan, dispatch resources, or trigger the corresponding emergency response mechanism after predicting an abnormal event.

[0065] A working method of a visual monitoring system according to any one of the above items comprises the following steps:

[0066] S1. The system collects temperature and humidity data of goods and the environment in the cold chain transportation process in real time through integrated multiple sensors. Temperature and humidity monitoring equipment is deployed in each transportation link (refrigerated trucks, warehouses, loading and unloading areas, etc.). Once the temperature and humidity data exceeds the preset threshold range, the system analyzes and triggers the early warning mechanism through intelligent algorithms. The system will display the abnormality through a visual interface, and relevant personnel will receive notifications and be able to make timely adjustments.

[0067] S2. The system combines satellite positioning (GPS) and geographic information system (GIS) to track the location of transport vehicles in real time. The real-time location, transport speed and estimated arrival time of the vehicle will be displayed on the visual interface. The system automatically optimizes the transport route by analyzing real-time data (such as traffic conditions, weather changes, traffic accidents, etc.) and combining the characteristics of the goods (such as transportation requirements, temperature control requirements, etc.). The system automatically selects the shortest and most suitable transport route to reduce time, reduce costs and keep temperature fluctuations to a minimum;

[0068] S3. The system monitors the status of the equipment in real time through sensors installed in various links of the cold chain (such as temperature control equipment sensors, door switch sensors, etc.). If a link has equipment failure or chain break (such as the refrigerated truck door is not closed or the temperature control equipment stops working), the system will detect and issue a warning in real time. The system uses a distributed sensor network and satellite positioning system to verify the integrity of the cold chain in the transportation path. Through data analysis, the system can determine whether the cold chain transportation meets the standards and promptly discover potential cold chain break risks;

[0069] S4. The system automatically dispatches the most suitable transport vehicles and storage resources based on real-time transport demand, vehicle status, storage conditions and traffic data using artificial intelligence algorithms. The system predicts transport demand in advance by analyzing historical data, demand trends and seasonal changes. Combined with real-time data, the system optimizes the dispatching strategy to ensure the rational allocation of transport and storage resources.

[0070] S5. The operating status of temperature control equipment (such as refrigerated trucks, cold storage temperature control equipment, etc.) is monitored in real time through sensors. Information such as equipment failure and abnormal alarms will be transmitted to the system in real time for staff to repair or replace in time. The system automatically adjusts the working status of the temperature control equipment based on real-time environmental data and cargo temperature control requirements. According to temperature fluctuations during transportation, the system will optimize the equipment operating parameters to ensure that the cargo is always in the optimal temperature range;

[0071] S6. The system uses RFID tags and sensors to automatically record the data of each link in the transportation process (such as temperature and humidity, location, time, etc.). Each link (loading, transportation, unloading) will generate a detailed data log to ensure the traceability of the goods status. The system combines the transportation process data, environmental data and goods characteristics to conduct life cycle analysis. Based on the data, the system can predict the period when the goods may be damaged or the quality will decline, and provide early warnings to managers;

[0072] S7. The system uses intelligent algorithms to analyze historical data and real-time monitoring data to predict abnormal events that may occur during cold chain transportation (such as equipment failure, temperature control failure, traffic accidents, etc.). The system will generate an abnormal prediction report and conduct a risk assessment of the transportation links in the next few hours or days. Once an abnormal event is predicted, the system will automatically activate the emergency response mechanism.

[0073] In summary, the visual monitoring system of the present invention can solve many problems in the existing cold chain logistics system by comprehensively using multiple advanced technologies (such as AI, Internet of Things, RFID, big data, etc.), improve monitoring accuracy and real-time performance, optimize transportation routes and resource scheduling, and ensure the integrity and safety of cold chain transportation. Compared with the existing technology, the system has stronger data integration capabilities, more intelligent abnormal warning mechanisms, and more efficient resource utilization efficiency, bringing significant technological progress to the cold chain logistics industry.

[0074] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A visual monitoring system, characterized in that: It includes temperature and humidity monitoring module, transportation route optimization module, cargo status monitoring module, cold chain break detection module, artificial intelligence optimization scheduling module, temperature control equipment intelligent optimization module, cargo life cycle tracing module and intelligent abnormal event prediction and response module; The temperature and humidity monitoring module is used to monitor the temperature and humidity during cold chain transportation in real time; The transport path optimization module is used to optimize transport paths and routes, reduce transport time, reduce transport costs, and avoid unnecessary delays; The cargo status monitoring module is used to monitor various key states of cargo during transportation in real time; The cold chain break detection module is used to detect whether there is an interruption or failure in cold chain transportation, and to discover and handle abnormalities in a timely manner; The artificial intelligence optimization scheduling module is used to optimize the scheduling of transportation and warehousing according to real-time data through artificial intelligence algorithms, ensure the maximum utilization of transportation resources, reduce empty loads or resource waste, and respond to emergencies; The temperature control equipment intelligent optimization module is used to optimize the performance of the temperature control equipment and reduce the risk of equipment failure; The cargo life cycle traceability module is used to record and trace data for each link in the cold chain transportation process, ensuring that each link from departure to arrival of the cargo can be traced, timely discovering potential problems and providing comprehensive compliance checks; The intelligent abnormal event prediction and response module is used to predict abnormal events in the transportation process through intelligent algorithms, identify potential risks in advance, and take timely measures to prevent accidents. The intelligent abnormal event prediction and response module includes an abnormal event prediction unit and an adaptive response unit; The abnormal event prediction unit is used to predict possible abnormal events by analyzing historical data and real-time monitoring data; The adaptive response unit is used to automatically adjust the transportation plan, dispatch resources, or trigger a corresponding emergency response mechanism after predicting an abnormal event.

2. A visual monitoring system according to claim 1, characterized in that: The temperature and humidity monitoring module includes a real-time temperature and humidity acquisition unit and an intelligent early warning unit; The real-time temperature and humidity acquisition unit is used to obtain the temperature and humidity data of the goods in the cold chain transportation process in real time by integrating multiple sensors; The intelligent early warning unit is used to automatically issue an early warning and notify relevant personnel when the temperature and humidity data exceed the set threshold.

3. A visual monitoring system according to claim 1, characterized in that: The transport path optimization module includes a real-time location tracking unit and a transport path optimization unit; The real-time location tracking unit is used to achieve real-time location tracking of cold chain transportation vehicles by combining a satellite positioning system and a geographic information system; The transport route optimization unit is used to analyze vehicle driving data and cargo characteristic factors, optimize driving routes, reduce transportation time, and reduce temperature fluctuations.

4. A visual monitoring system according to claim 1, characterized in that: The cargo status monitoring module includes an internal and external environment synchronous monitoring unit and a cold chain risk assessment unit; The internal and external environment synchronous monitoring unit is used to monitor the temperature inside the goods and monitor changes in the external environment during the cold chain logistics process; The cold chain risk assessment unit is used to assess the risk level of the cold chain according to the type of goods, transportation method and monitoring data.

5. A visual monitoring system according to claim 1, characterized in that: The cold chain break detection module includes a physical break detection unit and a cold chain integrity verification unit; The physical chain break detection unit is used to monitor each link in the cold chain system through sensors to detect in real time whether there is equipment failure or chain break; The cold chain integrity verification unit is used to use a distributed sensor network, combined with satellite positioning and sensor data, to verify the integrity of cold chain transportation in real time.

6. A visual monitoring system according to claim 1, characterized in that: The artificial intelligence optimization scheduling module includes a dynamic scheduling unit and a prediction scheduling unit; The dynamic scheduling unit is used to automatically schedule the most suitable vehicles and storage resources according to transportation demand, cold chain equipment status and traffic conditions; The forecasting and scheduling unit is used to forecast transportation demand and resource scheduling using historical data, and make adjustments and resource allocations in advance.

7. A visual monitoring system according to claim 1, characterized in that: The temperature control equipment intelligent optimization module includes a temperature control equipment status diagnosis unit and a temperature control adjustment optimization unit; The temperature control equipment status diagnosis unit is used to monitor the working status of the temperature control equipment during cold chain transportation in real time; The temperature control optimization unit is used to automatically adjust the working parameters of the temperature control equipment during transportation to keep the temperature within the most suitable range.

8. A visual monitoring system according to claim 1, characterized in that: The cargo life cycle tracing module includes a transportation process tracing unit and a life cycle analysis unit; The transport process tracing unit is used to track the goods throughout the entire process through RFID tags and sensors, and record the temperature and humidity data of each link as well as the transport route; The life cycle analysis unit is used to analyze the life cycle of the goods by combining the transportation process data, environmental data and goods characteristics, and predict the possible damage or quality degradation period.

9. A working method of a visual monitoring system according to any one of claims 1 to 8, characterized in that: The steps include: S1. The system collects temperature and humidity data of goods and the environment in the cold chain transportation process in real time through integrated multiple sensors. Temperature and humidity monitoring equipment is deployed in each transportation link (refrigerated trucks, warehouses, loading and unloading areas, etc.). Once the temperature and humidity data exceeds the preset threshold range, the system analyzes and triggers the early warning mechanism through intelligent algorithms. The system will display the abnormality through a visual interface, and relevant personnel will receive notifications and be able to make timely adjustments. S2. The system combines satellite positioning (GPS) and geographic information system (GIS) to track the location of transport vehicles in real time. The real-time location, transport speed and estimated arrival time of the vehicle will be displayed on the visual interface. The system automatically optimizes the transport route by analyzing real-time data (such as traffic conditions, weather changes, traffic accidents, etc.) and combining the characteristics of the goods (such as transportation requirements, temperature control requirements, etc.). The system automatically selects the shortest and most suitable transport route to reduce time, reduce costs and keep temperature fluctuations to a minimum; S3. The system monitors the status of the equipment in real time through sensors installed in various links of the cold chain (such as temperature control equipment sensors, door switch sensors, etc.). If a link has equipment failure or chain break (such as the refrigerated truck door is not closed or the temperature control equipment stops working), the system will detect and issue a warning in real time. The system uses a distributed sensor network and satellite positioning system to verify the integrity of the cold chain in the transportation path. Through data analysis, the system can determine whether the cold chain transportation meets the standards and promptly discover potential cold chain break risks; S4. The system automatically dispatches the most suitable transport vehicles and storage resources based on real-time transport demand, vehicle status, storage conditions and traffic data using artificial intelligence algorithms. The system predicts transport demand in advance by analyzing historical data, demand trends and seasonal changes. Combined with real-time data, the system optimizes the dispatching strategy to ensure the rational allocation of transport and storage resources. S5. The operating status of temperature control equipment (such as refrigerated trucks, cold storage temperature control equipment, etc.) is monitored in real time through sensors. Information such as equipment failure and abnormal alarms will be transmitted to the system in real time for staff to repair or replace in time. The system automatically adjusts the working status of the temperature control equipment based on real-time environmental data and cargo temperature control requirements. According to temperature fluctuations during transportation, the system will optimize the equipment operating parameters to ensure that the cargo is always in the optimal temperature range; S6. The system uses RFID tags and sensors to automatically record the data of each link in the transportation process (such as temperature and humidity, location, time, etc.). Each link (loading, transportation, unloading) will generate a detailed data log to ensure the traceability of the goods status. The system combines the transportation process data, environmental data and goods characteristics to conduct life cycle analysis. Based on the data, the system can predict the period when the goods may be damaged or the quality will decline, and provide early warnings to managers; S7. The system uses intelligent algorithms to analyze historical data and real-time monitoring data to predict abnormal events that may occur during cold chain transportation (such as equipment failure, temperature control failure, traffic accidents, etc.). The system will generate an abnormal prediction report and conduct a risk assessment of the transportation links in the next few hours or days. Once an abnormal event is predicted, the system will automatically activate the emergency response mechanism.

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