A cold chain action multi-dimensional billing system and method based on logistics 4.0

Abstract

The application provides a cold chain action multi-dimensional billing system and method based on logistics 4.0, the system comprises a refrigeration unit, a sensing network and a multi-dimensional billing engine, the sensing network comprises a low-temperature-resistant radio frequency identification reader and a temperature and humidity sensor, and the multi-dimensional billing engine comprises a billing algorithm processor which is configured with a switch door heat load allocation algorithm model, an energy consumption allocation function and a unit electricity price; the method comprises collecting action event data and environmental disturbance data, calculating a temperature rise slope according to temperature data, obtaining an additional power consumption through the energy consumption allocation function, multiplying the additional power consumption by the unit electricity price to generate an environmental disturbance additional cost, calculating a basic action cost, and generating a multi-dimensional billing result after association. The application associates the door opening temperature change with the additional energy consumption of the refrigeration unit to allocate the environmental disturbance cost, automatically bills the value-added service action, and solves the problems of cold storage cost black box and income loss. The application relates to the technical field of intelligent logistics and cold chain warehouse management.

Description

Technical Field

[0001] This invention relates to the field of smart logistics and cold chain warehousing management technology, and in particular to a multi-dimensional billing system and method for cold chain operations based on Logistics 4.0. Background Technology

[0002] In the cold chain logistics sector, with the penetration of IoT, big data, and AI technologies, cold storage management has introduced equipment such as automated guided vehicles (AGVs), industrial-grade temperature and humidity sensors, and low-temperature RFID readers. These devices can record events related to goods entering and leaving the warehouse, handling, and picking, and collect real-time temperature and humidity data within the warehouse. Existing billing methods are mostly based on static factors such as the number of pallets, storage area, or number of operations. For example, storage fees are charged based on the number of pallets or the area of ​​the warehouse, while entry and picking fees are charged per piece or box.

[0003] However, this billing method fails to correlate the temperature rise caused by opening the cold storage door with the additional energy consumption of the refrigeration unit to offset the heat load. As a result, it cannot accurately allocate the environmental disturbance costs to the cargo owners who trigger the corresponding operations. It also lacks automatic billing triggers for value-added services such as unpacking and re-labeling, and refreezing. Furthermore, it does not dynamically adjust the operation rate based on the remaining shelf life of the goods to incentivize first-to-last-out delivery. This leads to energy cost black holes and value-added service revenue leakage for cold storage operators. Cargo owners frequently cause fee disputes because they cannot see the correspondence between various fees in the bill and specific actions and environmental events. It is difficult to determine liability for cargo damage in abnormal temperature control scenarios. At the same time, the lack of economic means to curb ineffective door opening and inefficient handling exacerbates energy waste and cargo damage risks.

[0004] Therefore, the inventors urgently need a multi-dimensional billing system and method for cold chain operations based on Logistics 4.0 to solve the above problems. Summary of the Invention

[0005] To address the shortcomings of the existing technologies, this invention provides a multi-dimensional billing system and method for cold chain operations based on Logistics 4.0. The aim is to solve the problems in existing cold chain logistics billing methods that fail to accurately allocate environmental disturbance costs by linking temperature changes caused by opening cold storage doors to the additional energy consumption of refrigeration units. Furthermore, these methods lack automatic billing triggers for value-added services and mechanisms for dynamically adjusting rates based on the shelf life of goods. Consequently, cold storage operators face energy cost black holes and revenue leaks, frequent disputes with cargo owners over fees, and the inability to curb ineffective door openings and inefficient handling through economic means.

[0006] To achieve the above objectives, the technical solution adopted by this invention is: a multi-dimensional billing system for cold chain operations based on Logistics 4.0, comprising a cold storage facility, at least one refrigeration unit deployed in the operating area of ​​the cold storage facility, a sensing network, and a multi-dimensional billing engine. The sensing network includes a low-temperature resistant RFID reader / writer and temperature and humidity sensors. The output terminals of the low-temperature resistant RFID reader / writer and the temperature and humidity sensors are respectively communicatively connected to the input terminal of the multi-dimensional billing engine. The low-temperature resistant RFID reader / writer is used to generate action event data in response to logistics operation actions. The temperature and humidity sensors are used to collect temperature and humidity data within the cold storage facility to generate environmental disturbance data. The multi-dimensional billing engine includes a billing algorithm processor. The billing algorithm processor is internally configured with a door opening and closing heat load allocation algorithm model, an energy consumption allocation function, and a unit electricity price. The billing algorithm processor receives temperature data collected by the temperature and humidity sensor before and after the cold storage door is opened, calculates the temperature rise slope, and substitutes it into the energy consumption allocation function to obtain the additional power consumption of the refrigeration unit caused by the opening of the cold storage door. Then, it multiplies the additional power consumption by the unit electricity price to generate an environmental disturbance surcharge. The billing algorithm processor calculates the basic action cost based on the action event data and associates the environmental disturbance surcharge with the corresponding action event data to generate a multi-dimensional billing result that includes the basic action cost and the environmental disturbance surcharge.

[0007] Based on the above, the beneficial effects of a multi-dimensional billing system for cold chain operations based on Logistics 4.0 are that it solves the problem that existing cold chain logistics billing methods cannot accurately allocate environmental disturbance costs by associating temperature changes caused by opening cold storage doors with the additional energy consumption of refrigeration units, and lack mechanisms for automatically triggering billing for value-added services and dynamically adjusting rates based on the shelf life of goods. This leads to energy cost black holes and revenue leakage for cold storage operators, frequent disputes with cargo owners, and the inability to curb ineffective door openings and inefficient handling through economic means. The main benefits are: 1. This invention collects temperature data in real time before and after the cold storage door is opened by temperature and humidity sensors in a sensing network. The billing algorithm processor of the multi-dimensional billing engine receives the temperature data and calculates the temperature rise slope using the door opening and closing heat load allocation algorithm model. The temperature rise slope is used as the core variable and input into the energy consumption allocation function to obtain the additional power consumption of the refrigeration unit caused by the opening of the cold storage door. The additional power consumption is then multiplied by the unit electricity price to generate an additional environmental disturbance cost. This additional environmental disturbance cost is associated with the action event data generated by the low-temperature resistant RFID reader in response to the cargo logistics operation. This achieves accurate traceability of environmental disturbance costs at the level of each action and allocation according to the actual heat load. The cost of cold air loss caused by opening the door is made explicit and charged. It also uses economic means to force the operation inside the cold storage to reduce ineffective door opening and inefficient handling. 2. This invention uses a low-temperature resistant RFID reader in a sensing network to automatically generate action event data in response to logistics operations such as warehousing, picking, and labeling of goods. The billing algorithm processor of the multi-dimensional billing engine receives the action event data and calculates the basic action fee based on it, realizing automated billing triggering for each value-added service action and routine operation, and eliminating revenue leakage caused by missed orders due to manual recording.

[0008] Furthermore, the sensing network also includes at least one current transformer, which is installed on the power supply line of the refrigeration unit and is used to monitor the current change of the refrigeration unit in real time to generate energy consumption verification data. The data input terminal of the billing algorithm processor is connected to the data output terminal of the current transformer, and the door opening and closing heat load sharing algorithm model is used to correct the additional power consumption based on the energy consumption verification data.

[0009] Based on the above, the beneficial effects of the current transformer are: real-time monitoring of current changes on the power supply line of the chiller unit to generate energy consumption verification data; providing electrical parameter references from the actual operating end of the unit for the door opening and closing heat load allocation algorithm model; enabling the door opening and closing heat load allocation algorithm model to correct the additional power consumption calculated based on the temperature rise slope; and making the calculation of environmental disturbance additional costs closer to the actual power consumption of the chiller unit. The beneficial effect of the energy consumption verification data is that it quantifies the actual current response of the chiller unit due to offsetting the door opening heat load into electrical parameters that can be input into the door opening and closing heat load allocation algorithm model, making the door opening and closing heat load... The allocation algorithm model can obtain the actual energy consumption feedback from the refrigeration unit based on the temperature rise slope estimation, thereby calibrating the calculated value of additional power consumption and reducing the billing deviation caused by relying solely on temperature fluctuations to estimate energy consumption. The beneficial effect of correcting the additional power consumption is that by using the actual work done by the refrigeration unit reflected in the energy consumption verification data, the additional power consumption obtained by the door opening and closing heat load allocation algorithm model based on the temperature rise slope can be adjusted, so that the final generated environmental disturbance additional cost can more accurately collect the actual additional energy consumption cost caused by opening the door, thereby enhancing the credibility of the multi-dimensional billing results and the cargo owner's acceptance of the energy consumption allocation cost.

[0010] Furthermore, the sensing network also includes at least one automated guided vehicle (AGV). The low-temperature resistant radio frequency identification (RFID) reader is fixedly installed on the body of the AGV and is used to automatically read the electronic tag attached to the target cargo when the AGV performs handling or picking actions, and generate action event data containing cargo identification information, action type, and timestamp.

[0011] Based on the above, the beneficial effects of the automated guided vehicle (AGV) are that it carries a low-temperature resistant RFID reader for mobile data collection during handling or retrieval operations within the cold storage, enabling the generation of action event data to occur synchronously with the actual logistics operations, achieving automatic recording of cargo movement trajectories and action types without human intervention; the beneficial effect of fixing the low-temperature resistant RFID reader to the AGV body is that the RFID reader can flexibly move between different areas of the cold storage along the AGV's operating path, instantly targeting and reading the electronic tags on the target cargo during each handling or retrieval operation, achieving comprehensive capture of cargo identity information in dynamic operating scenarios; the beneficial effect of cargo identity information is that a unique tag bound to the target cargo is output along with the action event data. The recognition feature enables the multi-dimensional billing engine to establish a correspondence between each action event and a specific cargo owner and cargo batch, achieving accurate billing of basic action costs and environmental disturbance surcharges to the correct cargo owner. The beneficial effect of action type is that it identifies the current operation as belonging to handling, picking, or other specified logistics operation categories in the action event data, enabling the billing algorithm processor to distinguish different operations and apply the corresponding billing rules to calculate basic action costs, achieving refined pricing based on actual business actions. The beneficial effect of timestamp is that it marks the precise occurrence time of each action event, enabling the multi-dimensional billing engine to align action event data with environmental disturbance data within the same time period in the time dimension, achieving accurate correlation and allocation between environmental disturbance surcharges and the action events that caused the disturbances.

[0012] Furthermore, the multi-dimensional billing engine also includes an expiration date-sensitive pricing module. The data input terminal of the expiration date-sensitive pricing module is communicatively connected to the data output terminal of the low-temperature resistant RFID reader. The expiration date-sensitive pricing module internally stores expiration date tiered discount rules, which are used to obtain the percentage of the remaining shelf life of the goods and dynamically adjust the billing according to the expiration date tiered discount rules.

[0013] Based on the above, the beneficial effects of the expiration date-sensitive pricing module are: receiving action event data output from the low-temperature RFID reader to obtain the percentage of remaining shelf life of the goods, and calling the internally stored expiration date-based tiered discount rules, enabling the multi-dimensional billing engine to dynamically adjust the billing based on the current expiration date status of the goods, thus automatically linking warehousing operation costs with the risk of the remaining shelf life of the goods; the beneficial effect of the expiration date-based tiered discount rules is that the expiration date-sensitive pricing module has a pre-set rate adjustment logic that increases with the percentage of remaining shelf life of the goods, enabling the billing system to automatically trigger differentiated pricing strategies such as discounts or additional management fees when the goods are nearing their expiration date, thereby using economic means to guide cargo owners to prioritize first-to-expires shipments and reduce the amount of near-expiration goods. Long-term storage loss; the beneficial effect of the percentage of remaining shelf life of goods is that it quantifies the urgency of the goods' expiration date into a calculable ratio and inputs it into the expiration date-sensitive pricing module. This allows the expiration date-sensitive pricing module to accurately determine which billing adjustment range the goods currently fall into based on pre-configured expiration date tiered discount rules, thus achieving objectivity and automation in expiration date-based billing adjustments. The beneficial effect of dynamic billing adjustments is that it introduces a rate factor that changes in real time with the goods' expiration date status, in addition to basic operating costs and environmental disturbance surcharges. This allows multi-dimensional billing results to comprehensively reflect operating costs, environmental loss costs, and near-expiration risk costs of goods. This enables cold storage operators to automatically collect near-expiration storage management fees and to provide incentives to owners who cooperate in quickly clearing out their goods.

[0014] Furthermore, the tiered discount rule based on shelf life is as follows: when the percentage of remaining shelf life of the goods is lower than a preset threshold and the cargo owner selects FEFO priority outbound, the shelf life-sensitive pricing module reduces the unit price of the basic operation fee to a preset discount ratio of the original price; when the percentage of remaining shelf life of the goods is lower than the preset threshold and the cargo owner requests mandatory retention, the shelf life-sensitive pricing module generates a near-expiry storage management fee based on the daily rate.

[0015] Based on the above, the beneficial effects of FEFO priority outbound are as follows: when the percentage of remaining shelf life of goods is lower than a preset threshold, the expiration date-sensitive pricing module identifies the cargo owner's strategy of prioritizing the clearance of near-expiration goods. This allows the expiration date-sensitive pricing module to reduce the unit price of basic operating fees to a preset discount percentage of the original price. This incentivizes cargo owners to actively cooperate with first-to-expiration outbound pricing through fee discounts, accelerating the turnover of near-expiration inventory and reducing the risk of goods spoiling in cold storage. The beneficial effect of the preset threshold is that it sets a critical value within the expiration date-sensitive pricing module to measure whether goods are entering a near-expiration state, thus making the expiration date-sensitive pricing module more sensitive to the remaining shelf life percentage. The expiration-sensitive pricing module can automatically distinguish between regular goods and near-expiration goods and trigger corresponding billing adjustment logic accordingly, achieving precise and manual execution of the near-expiration differentiated pricing strategy. The beneficial effect of the unit price of basic operation fees is that the unit pricing standard of basic operation fees can be independently adjusted in the expiration-sensitive pricing module, ensuring that discounts only apply to the unit price of operation fees and not other cost items. This achieves precise economic guidance for cargo owners' outbound decisions without affecting the independent accounting of environmental disturbance surcharges. The beneficial effect of the preset discount ratio of the original price is that the unit price of basic operation fees can be pre-set in the expiration-sensitive pricing module. The preferential treatment ensures that the billing adjustment for near-expiry goods when FEFO (Free On Demand) is prioritized for release is automatically executed at a fixed and transparent discount rate, achieving predictability of the discount for cargo owners and controllability of the profit concessions made by cold storage operators. The beneficial effect of mandatory retention is that when the percentage of remaining shelf life of goods falls below a preset threshold and the cargo owner refuses priority release, the expiration date-sensitive pricing module identifies this retention instruction that violates the FEFO principle. Based on this, the expiration date-sensitive pricing module triggers a mechanism of daily rate billing, thus using economic means to constrain long-term retention behavior that occupies cold storage resources and increases the risk of expiration; the daily rate... The beneficial effects include setting a daily cumulative pricing unit in the expiration-sensitive pricing module, which makes the near-expiration storage management fee generated by the forced retention of near-expiration goods proportional to the length of time that cold storage space and temperature control resources are occupied, thus achieving accurate cost recovery for the continuous occupation of scarce cold chain storage resources; the beneficial effect of the near-expiration storage management fee is that the expiration-sensitive pricing module automatically generates additional fees on a daily basis for goods that are below the preset threshold and are forcibly retained by the cargo owner, enabling cold storage operators to manage the long-term storage behavior of near-expiration goods in a paid manner, realizing the use of economic means to make up for the potential expiration losses of near-expiration goods and urging cargo owners to dispose of them as soon as possible.

[0016] Furthermore, the multidimensional billing engine also includes a three-dimensional overlay billing module. The data input terminal of the three-dimensional overlay billing module is connected to the data output terminal of the billing algorithm processor and the expiration date sensitive pricing module, respectively. The three-dimensional overlay billing module is used to receive the basic action fee, the environmental disturbance additional fee, and the fee output by the expiration date sensitive pricing module, and sum the above fees to generate the multidimensional billing result.

[0017] Based on the above, the beneficial effects of the three-dimensional overlay billing module are that it aggregates the basic action costs and environmental disturbance surcharges from the billing algorithm processor, as well as the costs from the expiration date sensitive pricing module, and sums the costs of the above three dimensions to generate a multi-dimensional billing result. This realizes the integrated synthesis of action costs, environmental damage costs, and expiration date risk costs in a single billing, ending the situation where various costs in cold storage billing are calculated in isolation and cannot form a complete cost view. The beneficial effect of the multi-dimensional billing result is that it outputs a comprehensive bill containing basic action costs, environmental disturbance surcharges, and expiration date sensitive pricing costs in the form of a single cost data package. This allows both cargo owners and cold storage operators to obtain a complete cost composition covering the three billing dimensions of action, environment, and expiration date at one time, realizing transparent delivery of all elements of cold storage costs to customers.

[0018] Furthermore, the billing algorithm processor is also configured with a disturbance threshold. The billing algorithm processor is also used to: when it is detected that the frequency of occurrence of the action event data in a predetermined area within the cold storage exceeds the disturbance threshold within a unit time, activate the door opening and closing heat load sharing algorithm model to calculate the environmental disturbance surcharge, and allocate the calculated environmental disturbance surcharge to the bill of the cargo owner based on the identity of the cargo owner who triggered the action event data.

[0019] Based on the above, the beneficial effect of the disturbance threshold is that it sets a frequency limit within the billing algorithm processor to determine whether the intensity of operations is sufficient to cause significant environmental impact. This allows the billing algorithm processor to automatically distinguish between sporadic operations and high-frequency entry and exit operations, triggering the calculation of environmental disturbance surcharges only for operation scenarios exceeding this limit. This avoids the waste of billing resources caused by frequent activation of the allocation algorithm due to occasional, low-intensity door opening actions. The beneficial effect of activating the door opening and closing heat load allocation algorithm model is that it establishes a conditional correlation between the running time of the door opening and closing heat load allocation algorithm model and the operation density of a predetermined area within the cold storage. This ensures that the door opening and closing heat load allocation algorithm model only activates when the frequency of action events exceeds the disturbance threshold, i.e., when the cumulative heat load effect is significant. The activation and allocation calculation enables on-demand generation of environmental disturbance surcharges, rather than indiscriminate calculation around the clock. The beneficial effect of cargo owner identity is that the cargo owner's identifier that triggers the operation is recorded along with the action event data. This allows the billing algorithm processor to accurately allocate the environmental disturbance surcharge to the corresponding cargo owner based on this identifier when allocating the environmental disturbance surcharge, thus achieving accurate attribution of disturbance costs in scenarios where multiple cargo owners operate in parallel within the same predetermined area. The beneficial effect of the bill is that it accepts the environmental disturbance surcharge allocated according to cargo owner identity and combines it with the basic action cost. This allows each cargo owner to clearly see the details of the additional energy consumption costs generated by their operation triggering high-frequency entry and exit in their own bill, thus achieving cost traceability to the specific cargo owner and specific operation period.

[0020] Furthermore, when several of the cargo owner identities trigger several action event data within the predetermined area during the same period, the billing algorithm processor allocates the environmental disturbance surcharge to the bills of each cargo owner identity in a weighted average manner according to the proportion of the number of action events triggered by each cargo owner identity.

[0021] Based on the above, the beneficial effect of the proportion of action events is that, when multiple cargo owners trigger different numbers of work events in the same time period and within the same predetermined area, it provides the billing algorithm processor with a quantitative allocation basis that uses the actual contribution frequency of each cargo owner to the cumulative heat load as the weight. This makes the allocation result of environmental disturbance surcharges positively correlated with the work intensity of each cargo owner, achieving a fair distribution of the environmental damage costs caused by the joint incidents according to the degree of responsibility. The beneficial effect of weighted allocation is that, after calculating the total environmental disturbance surcharges, the billing algorithm processor does not use a simple equal distribution method, but instead uses the proportion of action events triggered by each cargo owner as the weight. The cost allocation is based on factors, ensuring that cargo owners with high operational frequency and significant contributions to temperature disturbance bear a correspondingly higher proportion of the cost. This achieves a precise match between the allocation results and the actual impact of each cargo owner's actions on the cold storage environment, avoiding the unreasonable phenomenon of high-frequency operation costs being borne by low-frequency cargo owners. The beneficial effect of the bills for each cargo owner's identity is that the weighted allocation of environmental disturbance surcharges is separately attributed to the corresponding cargo owner's independent bill. This allows each cargo owner to see only the energy consumption surcharges caused by their own operational activities, weighted by the proportion of the number of actions, in their own exclusive bill. This achieves cost isolation and independent transparency at the billing level in scenarios where multiple cargo owners share cold storage.

[0022] Furthermore, the system also includes a digital twin visualization module. The data input end of the digital twin visualization module is communicatively connected to the data output end of the sensing network and the multidimensional billing engine. The digital twin visualization module is used to generate an interactive interface for customer terminals. On the interactive interface, the historical movement trajectory of goods in the cold storage is overlaid at least in the form of a heat map, and a replay list of each action event that triggers the multidimensional billing result and its corresponding cost details are displayed in the form of an event list.

[0023] Based on the above, the beneficial effects of the digital twin visualization module are as follows: it integrates action event data and environmental disturbance data collected by the sensing network with multi-dimensional billing results generated by the multi-dimensional billing engine into a visual view for the client terminal. This allows cargo owners to intuitively view the complete operational trajectory and cost composition of goods within the cold storage on a single interactive interface, achieving transparent delivery of cold storage operation services and autonomous resolution of cost disputes throughout the entire process. The interactive interface provides an operable information presentation window on the client terminal, integrating heat maps, historical movement trajectories, event lists, and cost details into a single view. This allows cargo owners to obtain cargo status and billing details in one stop without switching between different systems, achieving convenience and completeness in obtaining cold storage service information. The heat map presents the historical movement trajectory of goods within the cold storage in a color gradient overlay on the interactive interface, enabling cargo owners to intuitively identify high-frequency activity areas and hotspots within the storage, achieving visual analysis of the rationality of cargo handling paths and the intensity of operations. The historical movement trajectory also provides a way to visualize the cargo's movement within the cold storage. The spatial changes of goods being handled and transferred within the cold storage from warehousing to outbound are linked together chronologically to form a path, allowing cargo owners to review the flow of goods within the warehouse segment by segment, achieving full traceability of the location and path of each operation. The beneficial effect of the event list is that it lists each action event that triggers the multi-dimensional billing result in a list format on the interactive interface, allowing cargo owners to review the records of each warehousing, picking, and handling operation, achieving a one-to-one correspondence between operation actions and billing items. The beneficial effect of the playback list is that it links each action event in the event list with its corresponding cost details, allowing cargo owners to trace the specific source action and environmental conditions of any cost, achieving full-chain verifiability of billing results from total amount to individual action. The beneficial effect of the cost details is that it breaks down the multi-dimensional billing result into the basic action cost, environmental disturbance additional cost, and expiration date sensitive pricing cost generated by each action event on the interactive interface, allowing cargo owners to clearly understand the specific service content and cost composition corresponding to every penny, achieving complete transparency of cold storage billing.

[0024] Furthermore, this invention provides a multi-dimensional billing method for cold chain operations based on Logistics 4.0, comprising the following steps: S1: Through the sensing network deployed in the working area of ​​the cold storage, action event data and environmental disturbance data are collected and output synchronously. The action event data is generated by a low-temperature resistant radio frequency identification reader in response to the logistics operation of goods or equipment. The environmental disturbance data is generated by a temperature and humidity sensor that collects temperature and humidity data in the cold storage in real time. S2: The billing algorithm processor in the multi-dimensional billing engine receives the action event data and the environmental disturbance data, and uses the internally configured door opening and closing heat load allocation algorithm model to calculate the temperature rise slope based on the temperature data before and after the cold storage door is opened in the environmental disturbance data. The temperature rise slope is used as the core variable and input into the energy consumption allocation function configured inside the billing algorithm processor to calculate the additional power consumption of the refrigeration unit caused by the opening of the cold storage door. The additional power consumption is then multiplied by the unit electricity price configured inside the billing algorithm processor to generate the environmental disturbance additional fee. S3: The billing algorithm processor calculates the basic action cost based on the action event data, and associates the environmental disturbance additional cost with the action event data to generate a multi-dimensional billing result that includes the basic action cost and the environmental disturbance additional cost.

[0025] Based on the above, the beneficial effect of step S1 is that within the cold storage operation area, action event data generated by the low-temperature RFID reader and environmental disturbance data generated by the temperature and humidity sensor are synchronously acquired through the sensing network. This enables the billing algorithm processor to obtain spatiotemporally aligned operation behavior and temperature and humidity change data streams, achieving complete and synchronous collection of the causal relationship basic information required for subsequent environmental disturbance cost allocation. The beneficial effect of step S2 is that by utilizing the door opening and closing heat load allocation algorithm model configured within the billing algorithm processor, the temperature change before and after the cold storage door is opened in the environmental disturbance data provided in step S1 is converted into a temperature rise slope. This slope is then input into the energy consumption allocation function to calculate the additional power consumption of the refrigeration unit, and multiplied by the unit electricity price to generate additional environmental disturbance costs. This achieves automated and accurate conversion from temperature fluctuation events to monetized environmental costs. The beneficial effect of step S3 is that the additional environmental disturbance costs generated in step S2 are associated with the action event data and merged with the basic action costs to output multi-dimensional billing results. This allows the action cost of a single operation and the resulting environmental additional costs to be fully reflected in the same bill, achieving billing delivery with multiple charges per order and cost traceability.

[0026] To make the above features of the present invention and the objectives to be achieved clearer, the present invention will be further described below in conjunction with the accompanying drawings and specific embodiments. Attached Figure Description

[0027] Figure 1 : This is a signal block diagram of the system of the present invention; Figure 2 : This is a flowchart of the method of the present invention.

[0028] The following are the definitions of the symbols in the attached diagram: 1-Cold storage, 2-Refrigeration unit, 3-Sensing network, 31-Low temperature RFID reader, 32-Temperature and humidity sensor, 33-Current transformer, 34-Automatic guided vehicle, 4-Multi-dimensional billing engine, 41-Billing algorithm processor, 42-Expiration-sensitive pricing module, 43-Three-dimensional overlay billing module, 5-Digital twin visualization module. Detailed Implementation

[0029] See Figures 1-2 As shown, This invention also discloses a multi-dimensional billing system for cold chain operations based on Logistics 4.0, comprising a cold storage 1, at least one refrigeration unit 2 deployed in the operating area of ​​the cold storage 1, a sensing network 3, and a multi-dimensional billing engine 4. The sensing network 3 includes a low-temperature resistant RFID reader 31 and a temperature and humidity sensor 32. The output terminals of the low-temperature resistant RFID reader 31 and the temperature and humidity sensor 32 are respectively communicatively connected to the input terminal of the multi-dimensional billing engine 4. The low-temperature resistant RFID reader 31 is used to generate action event data in response to logistics operation actions. The temperature and humidity sensor 32 is used to collect temperature and humidity data in the cold storage 1 to generate environmental disturbance data. The multi-dimensional billing engine 4 includes a billing algorithm processor 41. The billing algorithm processor 41 is internally configured with a door opening and closing heat load allocation algorithm model, an energy consumption allocation function, and a unit electricity price. The billing algorithm processor 41 receives temperature data collected by the temperature and humidity sensor 32 before and after the door of the cold storage 1 is opened, calculates the temperature rise slope, and substitutes it into the energy consumption allocation function to obtain the additional power consumption of the refrigeration unit 2 caused by the opening of the door of the cold storage 1. Then, it multiplies it by the unit electricity price to generate an environmental disturbance additional fee. The billing algorithm processor 41 calculates the basic action fee based on the action event data, and associates the environmental disturbance additional fee with the corresponding action event data to generate a multi-dimensional billing result that includes the basic action fee and the environmental disturbance additional fee.

[0030] In this embodiment, both the low-temperature RFID reader 31 and the temperature and humidity sensor 32 adopt an industrial-grade low-temperature resistant design adapted to environments ranging from -25℃ to -40℃, ensuring continuous and stable operation in cryogenic and refrigerated temperature zones. The action event data is associated with the corresponding pallet ID and the expiration date information of the goods batch, so that each logistics operation action can be bound to a specific consignor and goods batch. The temperature and humidity sensor 32 monitors the temperature and humidity fluctuation curve corresponding to the door opening time of the cold storage 1 in real time, providing continuous environmental disturbance data input for subsequent energy consumption allocation, thereby realizing the synchronous collection and association of action dimension and environmental dimension data.

[0031] In this embodiment, the sensing network 3 further includes at least one current transformer 33, which is installed on the power supply line of the chiller unit 2 and is used to monitor the current change of the chiller unit 2 in real time to generate energy consumption verification data. The data input terminal of the billing algorithm processor 41 is connected to the data output terminal of the current transformer 33. The door opening and closing heat load sharing algorithm model is used to correct the additional power consumption based on the energy consumption verification data.

[0032] In this embodiment, the current transformer 33 is a high-precision current transformer, which can capture the instantaneous current fluctuations generated by the refrigeration unit 2 due to the offsetting of the heat load from opening the door. The energy consumption verification data is compared and verified with the additional power consumption calculated based on the temperature rise slope. When there is a deviation between the two, the door opening and closing heat load sharing algorithm model corrects the additional power consumption with the energy consumption verification data as a reference, so that the final generated environmental disturbance additional cost is closer to the actual additional work consumption of the refrigeration unit 2, thereby improving the credibility of the billing result and the cargo owner's acceptance of the energy consumption sharing cost.

[0033] In this embodiment, the sensing network 3 further includes at least one automated guided vehicle 34. The low-temperature resistant radio frequency identification reader 31 is fixedly installed on the body of the automated guided vehicle 34 and is used to automatically read the electronic tag attached to the target goods when the automated guided vehicle 34 performs handling or picking actions, and generate action event data containing goods identity information, action type and timestamp.

[0034] In this embodiment, the automated guided vehicle 34 moves along a preset path within the cold storage 1. Its low-temperature resistant RFID reader 31 reads the electronic tag on the target goods in real time during each handling or picking action, so that the generation of action event data occurs synchronously with the actual logistics operation. The automatic recording of the goods movement trajectory and action type can be completed without human intervention. At the same time, the forklift picking action and the packing table scanning action are also captured in real time by the corresponding sensing devices and associated with the corresponding pallet ID and goods batch expiration date, ensuring that all kinds of value-added service actions are included in the automatic billing trigger range, and preventing revenue leakage caused by missed orders due to manual recording.

[0035] In this embodiment, the multi-dimensional billing engine 4 further includes an expiration date sensitive pricing module 42. The data input terminal of the expiration date sensitive pricing module 42 is communicatively connected to the data output terminal of the low-temperature resistant RFID reader / writer 31. The expiration date sensitive pricing module 42 internally stores expiration date tiered discount rules, which are used to obtain the percentage of the remaining shelf life of the goods and dynamically adjust the billing according to the expiration date tiered discount rules.

[0036] In this embodiment, the expiration date sensitive pricing module 42 extracts the expiration date information of the goods batch from the action event data and compares it with the current date. It automatically calculates the percentage of the remaining shelf life of the goods. When the percentage of the remaining shelf life of the goods is lower than a preset threshold, the expiration date sensitive pricing module 42 executes the corresponding billing adjustment strategy according to the owner's choice. This automatically links the warehousing operation costs with the risk of the remaining shelf life of the goods. Through economic means, it guides the owner to prioritize the first-to-last-out policy and reduce the long-term storage losses of near-expiration products.

[0037] In this embodiment, the shelf-life tiered discount rule is as follows: when the percentage of the remaining shelf life of the goods is lower than a preset threshold and the cargo owner selects FEFO priority outbound, the shelf-life sensitive pricing module 42 reduces the unit price of the basic action fee to a preset discount ratio of the original price; when the percentage of the remaining shelf life of the goods is lower than the preset threshold and the cargo owner requests mandatory retention, the shelf-life sensitive pricing module 42 generates a near-expiry storage management fee according to the daily rate.

[0038] In this embodiment, the preset threshold is set according to the shelf-life management requirements of food or pharmaceutical products. For example, the state where the remaining shelf life is less than one-third of the total shelf life is defined as the near-expiry state. The preset discount ratio corresponding to the FEFO priority outbound strategy enables the cargo owner to complete the outbound at a preferential operating rate, which incentivizes the cargo owner to actively cooperate to accelerate the turnover of near-expiry inventory and reduce the risk of goods damage due to expiration in cold storage. The daily rate corresponding to mandatory retention makes the near-expiry storage management fee increase with the time occupied by cold storage space and temperature control resources. This uses economic means to constrain the long-term retention behavior that occupies cold storage resources and increases the risk of expiration, and to compensate for the potential losses caused by the near-expiry products occupying the warehouse.

[0039] In this embodiment, the multidimensional billing engine 4 further includes a three-dimensional overlay billing module 43. The data input terminal of the three-dimensional overlay billing module 43 is connected to the data output terminal of the billing algorithm processor 41 and the expiration date sensitive pricing module 42, respectively. The three-dimensional overlay billing module 43 is used to receive the basic action fee, the environmental disturbance additional fee, and the fee output by the expiration date sensitive pricing module 42, and sum the above fees to generate the multidimensional billing result.

[0040] In this embodiment, the three-dimensional overlay billing module 43 integrates the three costs from the action dimension, environment dimension, and expiration date dimension, respectively, so that the multi-dimensional billing result fully reflects the operation cost of the goods in the cold storage 1, the temperature control environment loss cost caused by the operation, and the risk management cost caused by the near-expiration state of the goods in a single billing. This realizes the explicit collection of various implicit costs by the cold storage operator, and the cargo owner can obtain the complete cost composition covering the three billing dimensions at one time. This solves the problem of isolated accounting of various costs in traditional cold storage billing and the inability to form a complete cost view.

[0041] In this embodiment, the billing algorithm processor 41 is also configured with a disturbance threshold. The billing algorithm processor 41 is also used to: when it is detected that the frequency of occurrence of the action event data in a predetermined area within the cold storage 1 exceeds the disturbance threshold within a unit time, start the door opening and closing heat load sharing algorithm model to calculate the environmental disturbance additional cost, and allocate the calculated environmental disturbance additional cost to the bill of the cargo owner based on the identity of the cargo owner who triggered the action event data.

[0042] In this embodiment, the setting of the disturbance threshold enables the billing algorithm processor 41 to automatically distinguish between sporadic operations and high-frequency entry and exit operations. The calculation of environmental disturbance surcharge is only triggered when the frequency of action events in the predetermined area exceeds the threshold, i.e., when the heat load accumulation effect is significant. This avoids the waste of billing resources caused by frequent activation of the apportionment algorithm due to occasional, low-intensity door opening actions. At the same time, the environmental disturbance surcharge is directly bound to the identity of the cargo owner who triggers the fee, so that the environmental surcharge caused by the cargo owner's operation can be accurately attributed to their exclusive bill.

[0043] In this embodiment, when several cargo owner identities trigger several action event data within the predetermined area during the same time period, the billing algorithm processor 41 weights and distributes the environmental disturbance surcharge to the bills of each cargo owner identity according to the proportion of the number of action events triggered by each cargo owner identity.

[0044] In this embodiment, the weighted allocation mechanism uses the frequency of each cargo owner's actual contribution to the accumulated heat load in the predetermined area as a weighting factor. Cargo owners with high operation frequency and large contribution to temperature disturbance bear a correspondingly higher proportion of environmental disturbance additional costs, while cargo owners with low operation frequency bear a lower proportion. This achieves a precise match between the environmental disturbance cost and the actual impact of each cargo owner's behavior on the cold storage environment in the scenario of multiple cargo owners sharing a cold storage, avoiding the unreasonable phenomenon of high-frequency operation costs being shared by low-frequency cargo owners.

[0045] In this embodiment, the system further includes a digital twin visualization module 5. The data input end of the digital twin visualization module 5 is communicatively connected to the data output end of the sensing network 3 and the multidimensional billing engine 4. The digital twin visualization module 5 is used to generate an interactive interface for customer terminals. On the interactive interface, the historical movement trajectory of goods in the cold storage 1 is overlaid at least in the form of a heat map, and the replay list of each action event that triggers the multidimensional billing result and its corresponding cost details are displayed in the form of an event list.

[0046] In this embodiment, the digital twin visualization module 5 integrates the action event data and environmental disturbance data collected by the perception network 3 with the multidimensional billing results generated by the multidimensional billing engine 4. On the interactive interface of the customer terminal, the cargo owner can not only view the total bill amount, but also intuitively identify the high-frequency activity areas and hot spots of the goods in the warehouse through the heat map. By reviewing the historical movement trajectory segment by segment, the spatial position changes of each handling and transfer of the goods from the time of entry to exit can be viewed. By reviewing the event list and replay list, each action event that triggers the fee and its corresponding basic action fee, environmental disturbance additional fee and expiration date sensitive pricing fee details can be reviewed one by one. This allows the cargo owner to clearly understand the specific service content and cost composition corresponding to every penny, realizing the transparent delivery of the entire process of cold storage operation services and effectively solving the long-standing problem of fee disputes in cold chain logistics.

[0047] In this embodiment, the present invention also discloses a multi-dimensional billing method for cold chain operations based on Logistics 4.0, comprising the following steps: S1: Through the sensing network 3 deployed in the working area of ​​the cold storage 1, action event data and environmental disturbance data are collected and output synchronously. The action event data is generated by the low-temperature resistant radio frequency identification reader 31 in response to the logistics operation of goods or equipment. The environmental disturbance data is generated by the temperature and humidity sensor 32 collecting temperature and humidity data in the cold storage 1 in real time. S2: The billing algorithm processor 41 in the multi-dimensional billing engine 4 receives the action event data and the environmental disturbance data, and uses the internally configured door opening and closing heat load sharing algorithm model to calculate the temperature rise slope based on the temperature data before and after the door of the cold storage 1 is opened in the environmental disturbance data. The temperature rise slope is used as the core variable and input into the energy consumption sharing function configured inside the billing algorithm processor 41 to calculate the additional power consumption generated by the refrigeration unit 2 due to the opening of the door of the cold storage 1. The additional power consumption is then multiplied by the unit electricity price configured inside the billing algorithm processor 41 to generate the environmental disturbance additional fee. S3: The billing algorithm processor 41 calculates the basic action cost based on the action event data, and associates the environmental disturbance additional cost with the action event data to generate a multi-dimensional billing result that includes the basic action cost and the environmental disturbance additional cost.

[0048] The above description is merely the optimal embodiment of the present invention and is not intended to limit the present invention. Any modifications or substitutions made by those skilled in the art without departing from the essence and scope of protection of the present invention should also be within the scope of protection of the present invention.

Claims

1. A multi-dimensional billing system for cold chain operations based on Logistics 4.0, characterized in that, The system includes a cold storage (1), at least one refrigeration unit (2) deployed in the operating area of ​​the cold storage (1), a sensing network (3), and a multi-dimensional billing engine (4). The sensing network (3) includes a low-temperature resistant RFID reader (31) and a temperature and humidity sensor (32). The outputs of the low-temperature resistant RFID reader (31) and the temperature and humidity sensor (32) are respectively connected to the input of the multi-dimensional billing engine (4). The low-temperature resistant RFID reader (31) is used to generate action event data in response to logistics operation actions. The temperature and humidity sensor (32) is used to collect temperature and humidity data in the cold storage (1) to generate environmental disturbance data. The multi-dimensional billing engine (4) includes a billing algorithm processor (41). The billing algorithm... The processor (41) is internally configured with a door opening and closing heat load allocation algorithm model, an energy consumption allocation function, and a unit electricity price. The billing algorithm processor (41) receives temperature data of the cold storage (1) before and after the door is opened from the temperature and humidity sensor (32), calculates the temperature rise slope and substitutes it into the energy consumption allocation function to obtain the additional power consumption of the refrigeration unit (2) caused by the opening of the door of the cold storage (1), and then multiplies it by the unit electricity price to generate an additional environmental disturbance fee. The billing algorithm processor (41) calculates the basic action fee based on the action event data and associates the additional environmental disturbance fee with the corresponding action event data to generate a multi-dimensional billing result that includes the basic action fee and the additional environmental disturbance fee.

2. The cold chain multi-dimensional billing system based on Logistics 4.0 according to claim 1, characterized in that, The sensing network (3) also includes at least one current transformer (33), which is installed on the power supply line of the refrigeration unit (2) and is used to monitor the current change of the refrigeration unit (2) in real time to generate energy consumption verification data. The data input terminal of the billing algorithm processor (41) is connected to the data output terminal of the current transformer (33). The door opening and closing heat load sharing algorithm model is used to correct the additional power consumption based on the energy consumption verification data.

3. The cold chain multi-dimensional billing system based on Logistics 4.0 according to claim 1, characterized in that, The sensing network (3) also includes at least one automated guided vehicle (34). The low-temperature resistant radio frequency identification reader (31) is fixedly installed on the body of the automated guided vehicle (34) and is used to automatically read the electronic tag attached to the target goods when the automated guided vehicle (34) performs handling or picking actions, and generate action event data containing goods identity information, action type and timestamp.

4. The cold chain multi-dimensional billing system based on Logistics 4.0 according to claim 1, characterized in that, The multidimensional billing engine (4) also includes an expiration date sensitive pricing module (42). The data input terminal of the expiration date sensitive pricing module (42) is connected to the data output terminal of the low temperature RFID reader (31). The expiration date sensitive pricing module (42) stores the expiration date tiered discount rules internally, which are used to obtain the percentage of the remaining shelf life of the goods and dynamically adjust the billing according to the expiration date tiered discount rules.

5. A multi-dimensional billing system for cold chain operations based on Logistics 4.0 according to claim 4, characterized in that, The expiration date tiered discount rule is as follows: when the remaining shelf life percentage of the goods is lower than the preset threshold and the cargo owner selects FEFO priority delivery, the expiration date sensitive pricing module (42) reduces the unit price of the basic action fee to the preset discount ratio of the original price. When the remaining shelf life percentage of the goods is lower than the preset threshold and the cargo owner requests mandatory retention, the expiration date sensitive pricing module (42) generates a near-expiration storage management fee according to the daily rate.

6. A multi-dimensional billing system for cold chain operations based on Logistics 4.0 according to claim 4, characterized in that, The multidimensional billing engine (4) also includes a three-dimensional overlay billing module (43). The data input terminal of the three-dimensional overlay billing module (43) is connected to the data output terminal of the billing algorithm processor (41) and the expiration date sensitive pricing module (42), respectively. The three-dimensional overlay billing module (43) is used to receive the basic action fee, the environmental disturbance additional fee and the fee output by the expiration date sensitive pricing module (42), and sum the above fees to generate the multidimensional billing result.

7. A multi-dimensional billing system for cold chain operations based on Logistics 4.0 according to claim 1, characterized in that, The billing algorithm processor (41) is also configured with a disturbance threshold. The billing algorithm processor (41) is also used to: when it is identified that the frequency of occurrence of the action event data in a predetermined area within the cold storage (1) exceeds the disturbance threshold within a unit time, start the door opening and closing heat load sharing algorithm model to calculate the environmental disturbance additional cost, and according to the identity of the cargo owner who triggered the action event data, allocate the calculated environmental disturbance additional cost to the bill of the cargo owner.

8. A multi-dimensional billing system for cold chain operations based on Logistics 4.0 according to claim 7, characterized in that, When several of the cargo owners trigger several action event data in the predetermined area within the same time period, the billing algorithm processor (41) allocates the environmental disturbance surcharge to the bill of each cargo owner according to the proportion of the number of action events triggered by each cargo owner.

9. A multi-dimensional billing system for cold chain operations based on Logistics 4.0 according to claim 1, characterized in that, The system also includes a digital twin visualization module (5). The data input end of the digital twin visualization module (5) is communicatively connected to the data output end of the perception network (3) and the multidimensional billing engine (4). The digital twin visualization module (5) is used to generate an interactive interface for customer terminals. On the interactive interface, the historical movement trajectory of goods in the cold storage (1) is overlaid at least in the form of a heat map, and the replay list of each action event that triggers the multidimensional billing result and its corresponding cost details are displayed in the form of an event list.

10. A multi-dimensional billing method for cold chain operations based on Logistics 4.0, applied to the system described in claim 1, characterized in that, Includes the following steps: S1: Through the sensing network (3) deployed in the working area of ​​the cold storage (1), action event data and environmental disturbance data are collected and output synchronously. The action event data is generated by the low-temperature resistant radio frequency identification reader (31) in response to the logistics operation of goods or equipment. The environmental disturbance data is generated by the temperature and humidity sensor (32) collecting temperature and humidity data in the cold storage (1) in real time. S2: The billing algorithm processor (41) in the multi-dimensional billing engine (4) receives the action event data and the environmental disturbance data, and uses the internally configured door opening and closing heat load sharing algorithm model to calculate the temperature rise slope based on the temperature data before and after the door of the cold storage (1) is opened in the environmental disturbance data. The temperature rise slope is used as the core variable and input into the energy consumption sharing function configured in the billing algorithm processor (41) to calculate the additional power consumption of the refrigeration unit (2) caused by the opening of the door of the cold storage (1). The additional power consumption is then multiplied by the unit electricity price configured in the billing algorithm processor (41) to generate additional environmental disturbance fees. S3: The billing algorithm processor (41) calculates the basic action cost based on the action event data, and associates the environmental disturbance additional cost with the action event data to generate a multi-dimensional billing result that includes the basic action cost and the environmental disturbance additional cost.

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