Carbon footprint accounting method, device and equipment based on passive Internet of Things and medium

Abstract

The embodiment of the invention provides a carbon footprint accounting method, device and equipment based on a passive internet of things, and a medium. The invention belongs to the technical field of computers. The method comprises the following steps: acquiring article basic information and article positioning information reported by a passive tag of an article through a base station; the method comprises the following steps: acquiring current carrier attribute information, carrier positioning information and bearing information reported by a passive tag of a current carrier used for transporting articles through a base station; the object track and the current carrier transportation track are analyzed; determining a first transportation energy consumption parameter according to the basic information of the article, the transportation track of the current carrier and the attribute information of the current carrier; determining a first bearing distribution parameter according to the article basic information and the bearing information; a first transport carbon footprint accounting result of the article is determined. According to the technical scheme, the passive label data of the article and the carrier are collected through the base station, track analysis is combined, carbon footprint refined accounting is completed, and the accuracy and accounting efficiency of carbon footprint accounting are improved.

Description

Technical Field

[0001] This application belongs to the field of computer technology, and in particular relates to a carbon footprint accounting method, apparatus, device and medium based on passive Internet of Things. Background Technology

[0002] In carbon footprint accounting, the quantification of carbon emissions in the transportation sector is a core component, which requires calculation based on parameters such as transportation routes, vehicle attributes, and cargo information.

[0003] Currently, due to the difficulty in collecting key parameters during transportation, the industry generally uses the factor method for estimation. This involves obtaining transportation mileage through maps and combining it with a pre-defined carbon emission intensity factor for the vehicle and the weight of the goods to estimate carbon emissions by multiplying ton-kilometers by the emission factor. However, this method cannot obtain the actual operating status of the vehicles, relies on carbon emission factors statistically compiled by the industry, and fails to reflect the true energy consumption of transportation. Furthermore, estimating transportation distance solely based on origin and destination points cannot achieve cargo tracking, leading to a mismatch between the actual and theoretical transportation paths, which is insufficient to meet the requirements for precise carbon footprint management. Therefore, how to accurately calculate the carbon footprint of transportation with high precision is a pressing technical challenge that needs to be addressed in this field. Summary of the Invention

[0004] This application provides a carbon footprint accounting method, apparatus, device, and medium based on passive Internet of Things. The purpose of this application is to solve the technical problems in existing transportation carbon footprint accounting, such as reliance on preset factor estimation, inaccurate collection of key parameters, and inability to identify vehicle replacement. By collecting passive tag information of items and current vehicles through base stations, the trajectory of items and vehicles is accurately analyzed and the consistency of vehicles is verified. The calculation is completed by combining transportation energy consumption parameters and load allocation parameters, thereby improving the accuracy of transportation carbon footprint accounting results, ensuring data comprehensiveness, and improving the management precision of transportation carbon footprint.

[0005] In a first aspect, embodiments of this application provide a carbon footprint accounting method based on passive Internet of Things (IoT), the method comprising: Obtain basic information and location information of the item, as well as attribute information, location information, and carrying information of the current vehicle used to transport the item; The item's trajectory is analyzed based on the item's location information, and the current vehicle's transportation trajectory is analyzed based on the vehicle's location information; If the trajectory of the item matches the trajectory of the current vehicle, a first transportation energy consumption parameter is determined based on the basic information of the item, the current vehicle transportation trajectory, and the attribute information of the current vehicle. Based on the basic information of the item and the carrying information, the first carrying allocation parameter is determined; Based on the first transportation energy consumption parameter and the first load allocation parameter, the first transportation carbon footprint calculation result of the item is determined.

[0006] In one feasible embodiment, obtaining basic item information and item location information includes: The basic information of the item and its location information are collected by the passive tag of the item through the base station. Obtain the attribute information, vehicle location information, and carrying information of the current vehicle used to transport the goods, including: The base station collects the current vehicle attribute information, vehicle positioning information, and carrying information reported by the passive tag of the current vehicle used to transport the goods.

[0007] In one feasible embodiment, the method further includes: If the trajectory of the item does not match the current vehicle transport trajectory, a vehicle change event is determined to have occurred.

[0008] In one feasible embodiment, the method further includes: Identify whether the current vehicle's return load status is empty; Accordingly, when the item trajectory matches the current vehicle transportation trajectory, a first transportation energy consumption parameter is determined based on the item's basic information, the current vehicle transportation trajectory, and the current vehicle's attribute information, including: The first transportation energy consumption parameter is determined based on the return load status, the basic information of the items, the current vehicle transportation trajectory, and the attribute information of the current vehicle.

[0009] In one feasible embodiment, a first transportation energy consumption parameter is determined based on the return load status, the basic information of the goods, the current vehicle transportation trajectory, and the attribute information of the current vehicle, including: The following formula is used for calculation: ; in, The primary energy consumption parameter for transportation. For the quality of the item, This represents the energy consumption of the vehicle under a preset load rate. This represents the current transport trajectory distance of the vehicle. This represents the energy consumption value under load conditions during the return trip. This represents the vehicle's return mileage. If there is no empty return trip, the vehicle's return mileage is 0. The carbon emission factor of the vehicle.

[0010] In one feasible embodiment, the first load allocation parameter is determined based on the basic item information and the load information, including: The first load allocation parameter is determined based on the mass of a single item in the basic item information and the total load information in the load information. or, The first load allocation parameter is determined based on the volume of a single item in the item's basic information and the total volume information in the load information.

[0011] In one feasible embodiment, a first load-bearing allocation parameter is determined based on the individual item mass in the item basic information and the total load information in the load-bearing information, including: The following formula is used for calculation: ; in, Assign parameters to the first bearer. For the quality of the item, Let n be the number of items and n be the number of types of items.

[0012] In one feasible embodiment, the first load-bearing allocation parameter is determined based on the individual item volume in the item basic information and the total volume information in the load-bearing information, including: The following formula is used for calculation: ; in, Assign parameters to the first bearer. For the volume of the item, Let n be the number of items and n be the number of types of items.

[0013] In one feasible embodiment, the first transportation carbon footprint calculation result of the goods is determined based on the first transportation energy consumption parameter and the first load allocation parameter, including: The following formula is used for calculation: ; ; in, The first transportation carbon footprint accounting result for the goods. The primary energy consumption parameter for transportation. For the quality of the item, This represents the energy consumption of the vehicle under a preset load rate. This represents the current transport trajectory distance of the vehicle. This represents the energy consumption value under load conditions during the vehicle's return journey. This represents the mileage for the vehicle's empty return trip. If there is no empty return trip, the mileage is 0. The carbon emission factor of the vehicle.

[0014] In one feasible embodiment, the method further includes: The system collects basic information about the items from the passive tags of the items via the base station at the origin; and collects vehicle attribute information from the passive tags of the vehicles used to transport the items. The system collects basic information about the items from the passive tags of the items via the base station at the point of arrival; and collects vehicle attribute information from the passive tags of the vehicle used to transport the items. Compare the vehicle attribute information at the starting point with the vehicle attribute information at the destination point to see if they are the same; If they are the same, then it is determined that there is no vehicle change event.

[0015] In one feasible embodiment, the method further includes: Obtain the production information of the item; Based on the production information, determine the carbon footprint accounting result of the production of the item; Based on the production carbon footprint accounting results and the transportation carbon footprint accounting results, the total carbon footprint accounting result of the item is determined.

[0016] Secondly, embodiments of this application provide a carbon footprint accounting device based on passive Internet of Things, the device comprising: The information collection module is used to acquire basic information and location information of the item, as well as the attribute information, location information, and carrying information of the current vehicle used to transport the item. The trajectory determination module is used to parse the trajectory of the item based on the item's location information, and to parse the current vehicle's transportation trajectory based on the vehicle's location information; The transportation energy consumption parameter determination module is used to determine a first transportation energy consumption parameter based on the basic information of the item, the transportation trajectory of the current vehicle, and the attribute information of the current vehicle when the trajectory of the item matches the transportation trajectory of the current vehicle. The load allocation parameter determination module is used to determine the first load allocation parameter based on the basic information of the item and the load information; The transportation carbon footprint calculation module is used to determine the first transportation carbon footprint calculation result of the item based on the first transportation energy consumption parameter and the first carrying capacity allocation parameter.

[0017] Thirdly, embodiments of this application provide a carbon footprint accounting device based on passive Internet of Things (IoT). The device includes a processor and a memory storing computer program instructions. The processor reads and executes the computer program instructions to implement the carbon footprint accounting method based on passive IoT as described above.

[0018] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer program instructions, which, when executed by a processor, implement the carbon footprint accounting method based on passive Internet of Things as described above.

[0019] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the carbon footprint accounting method based on the passive Internet of Things as described above.

[0020] This application's embodiment of a carbon footprint accounting method, apparatus, device, and medium based on passive IoT collects passive tag data of goods and vehicles through base stations, avoiding manual input errors. Combined with trajectory analysis, it completes refined carbon footprint accounting, solving the problems of scattered data and large deviations in traditional accounting. Furthermore, by identifying vehicle changes through trajectory coverage, it achieves the accumulation of carbon emissions from multiple transportation segments, avoiding omissions or errors in accounting. The return load status is incorporated into the calculation of transportation energy consumption parameters, especially considering the energy consumption allocation of empty return trips, making the carbon footprint nucleic acid results more accurate. Based on two load allocation parameter calculation methods and standardized formulas based on mass or volume percentage, it adapts to different categories of goods, ensuring more accurate allocation results. Moreover, during the vehicle change identification process, the comparison of vehicle information at the departure and arrival points efficiently verifies whether the vehicle has been changed, enabling efficient and accurate identification. Furthermore, the production stage is also integrated to obtain carbon footprint accounting results for the entire life cycle. Attached Figure Description

[0021] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart illustrating a carbon footprint accounting method based on passive Internet of Things provided in an embodiment of this application; Figure 2 This is a schematic diagram of the transportation carbon footprint accounting and management system based on passive Internet of Things provided in this embodiment; Figure 3 This is a schematic diagram of the various transportation project information presented on the display platform provided in this embodiment; Figure 4This is a schematic diagram illustrating the analysis of energy consumption parameters for cargo transportation provided in this embodiment; Figure 5 This is a schematic diagram of the interface of the passive carbon tag management module provided in this embodiment; Figure 6 This is a schematic diagram of a carbon footprint accounting device based on passive Internet of Things provided in an embodiment of this application; Figure 7 This is a schematic diagram of the structure of a carbon footprint accounting device based on passive Internet of Things provided in an embodiment of this application. Detailed Implementation

[0023] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0024] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

[0025] To address the problems of existing technologies, this application provides a carbon footprint accounting method, apparatus, device, and medium based on passive Internet of Things (IoT). The technical solution provided in this application solves several technical problems in traditional carbon footprint accounting, such as low efficiency and large errors due to reliance on manual data collection, incomplete accounting in scenarios like vehicle changes and empty return trips, and the accounting scope being limited to a single stage. This solution automatically collects data on items and vehicles through passive IoT base stations, replacing manual operation. It combines trajectory analysis and entry / exit point information comparison for dual identification of vehicle changes, superimposed with return trip load status calculation, and provides two allocation methods—mass or volume percentage—and standardized formulas to adapt to different item characteristics. This achieves automated data collection without manual intervention, accurate identification of vehicle changes, and reasonable allocation using allocation rules, improving the efficiency and accuracy of carbon footprint accounting.

[0026] The carbon footprint accounting method based on passive Internet of Things provided in the embodiments of this application will be introduced first.

[0027] Figure 1 This is a flowchart illustrating a carbon footprint accounting method based on passive Internet of Things (IoT) provided in an embodiment of this application. Figure 1 As shown, the method may include the following steps: S101, obtain basic information about the item and its location information, and obtain the attribute information, vehicle location information and carrying information of the current vehicle used to transport the item; Basic information about an item can be manually entered by staff or can be basic data used to identify the item's identity and attributes, such as the item's unique code, like a SKU code, and can also include information such as name, category, individual weight, individual volume, and production batch.

[0028] The location information of an item can be manually entered by staff or generated by a passive tag through interaction with a base station to determine the real-time location of the item. For example, it can be the latitude and longitude coordinates and the area where the item is located, obtained by positioning based on the signal strength of multiple base stations.

[0029] The current vehicle can be any means of transport currently used to transport the target item, such as a truck, like a 4.2-meter van or a 17.5-meter semi-trailer. In addition, it can also be a container, a train carriage, or a ship's cargo hold.

[0030] The current vehicle attribute information can be manually entered by staff or data used to describe the inherent attributes and operational characteristics of the current vehicle, such as the vehicle's unique identifier, such as license plate number or chassis number, vehicle type, such as diesel truck or electric truck, rated load, rated volume, fuel type, such as diesel, natural gas or electricity, energy consumption standard, such as fuel consumption per 100 kilometers, and other attribute information of the vehicle itself.

[0031] Vehicle location information can be reported by the vehicle's own positioning module or by passive tags attached to the vehicle. This data is used to determine the vehicle's real-time location and is similar in format to object location information, such as the vehicle's latitude and longitude trajectory and stopping positions. Alternatively, location information can be obtained through the vehicle's own positioning module, transmitted to a passive tag on the vehicle, and then reported to the base station by the passive tag.

[0032] Load information can be data describing the actual load status of the vehicle, such as the vehicle's total load, which is the total mass of all items on the vehicle, the total volume, which is the total volume of all items on the vehicle, the actual load factor, the ratio of the total load to the rated load, etc. This information can be collected and reported by passive tags on the vehicle combined with weight sensors and volume measurement modules such as laser scanning modules.

[0033] In one feasible embodiment, the acquisition of basic item information and item location information includes: The basic information of the item and its location information are collected by the passive tag of the item through the base station. Obtain the attribute information, vehicle location information, and carrying information of the current vehicle used to transport the goods, including: A base station can be a signal receiving and data transmission device in a passive Internet of Things (Passive IoT). It can identify, receive, and upload data from passive tag signals. For example, passive IoT base stations can be deployed at warehouse entrances and exits or along transportation routes.

[0034] Passive tags are electronic tags that do not require an internal power source and rely on radio frequency signals emitted by a base station to obtain energy and report data. For example, UHF RFID (Radio Frequency Identification) passive tags are characterized by low cost, long lifespan, and mass deployment. They can be used for tracking the trajectory and location of items.

[0035] Among them, the current vehicle attribute information, vehicle positioning information, and carrying information are collected by the base station from the passive tag of the current vehicle used to transport the goods.

[0036] A base station can continuously transmit radio frequency signals. When a passive tag attached to an item enters the signal coverage area of ​​the base station, the passive tag absorbs radio frequency energy and is activated. It then feeds back the stored basic information of the item and real-time location-related data to the base station in the form of radio frequency signals. After receiving the signal, the base station forwards it to the corresponding management platform, such as a carbon footprint accounting platform. The platform can decode and analyze the signal to obtain the basic information of the item and the item's location information.

[0037] After the passive tag attached to the current vehicle enters the signal coverage area of ​​the base station, it is activated and reports the current vehicle attribute information, vehicle positioning information and carrying information. The base station receives the signal and forwards it to the carbon footprint management platform.

[0038] This technical solution enables information collection based solely on data interaction between passive tags and base stations, simplifying the information acquisition process. Furthermore, after setting up passive tags, real-time location information of items and vehicles can be obtained without the need for other positioning modules, simplifying the data collection process. No special design is required on the vehicle side to achieve the information collection process.

[0039] S102, analyze the item trajectory based on the item location information, and analyze the current vehicle transportation trajectory based on the vehicle location information; An item's trajectory can be the path formed by the changes in the location of an item during transportation. For example, an item may start from a factory warehouse, pass through a logistics park and a highway service area, and finally arrive at a city distribution center.

[0040] The current vehicle transport trajectory can be the path formed by the change in position of the current vehicle during the transportation of goods.

[0041] This solution can sort the collected item location information and vehicle location information in chronological order, remove abnormal data, and then generate continuous and visualized item trajectories and current vehicle transportation trajectories through map matching algorithms. For example, the travel paths of items and vehicles can be displayed on an electronic map in the form of multi-point lines.

[0042] S103, if the item trajectory matches the current vehicle transportation trajectory, determine the first transportation energy consumption parameter based on the item's basic information, the current vehicle transportation trajectory, and the current vehicle's attribute information; The first transportation energy consumption parameter can be a parameter calculated based on the basic information of the goods, the transportation trajectory of the vehicle, and the attribute information of the vehicle, which reflects the relationship between energy consumption and carbon emissions during the transportation process. For example, the basic value of carbon emissions corresponding to the total energy consumption of the vehicle during the transportation of the goods can be expressed in kilograms of carbon dioxide equivalent.

[0043] This solution first extracts the item's category and transportation requirements from its basic information, such as whether temperature-controlled transportation is required. It then calculates the transportation mileage from the current vehicle's trajectory, for example, by summing the distances between adjacent locations on the trajectory. Finally, it extracts the vehicle type, fuel type, and energy consumption standard from the current vehicle attribute information, such as a diesel truck's fuel consumption of 30L per 100km and its carbon emission factor, such as diesel's carbon emission factor of 2.63kgCO. e / L; then, based on the above information, calculate the first transportation energy consumption parameter. For example, if the vehicle is a diesel truck, the transportation distance is 500 kilometers, and the fuel consumption is 30L per 100 kilometers, then the total fuel consumption is 150L. Combining this with the carbon emission factor, the first transportation energy consumption parameter is calculated as 150L × 2.63kgCO. e / L = 394.5 kg CO e.

[0044] S104, Determine the first load allocation parameter based on the basic information of the item and the load information; The first load allocation parameter can be a parameter calculated based on the basic information and load information of the item, used to reflect the proportion of a single item in the total load of the vehicle, that is, the carbon emission allocation coefficient of the item, such as the proportion of the mass of a single item to the total load of the vehicle, or the proportion of the volume of a single item to the total volume of the vehicle, and its value range is 0-1.

[0045] This solution can extract the mass or volume of a single item from the basic information of the item, extract the total load or volume of the vehicle from the load information, and then calculate the first load allocation parameter by dividing the attribute value of a single item by the total attribute value of the vehicle. For example, if the mass of a single item is 5kg and the total load of the vehicle is 500kg, then the first load allocation parameter is 5kg / 500kg=0.01.

[0046] S105, based on the first transportation energy consumption parameter and the first load allocation parameter, determine the first transportation carbon footprint calculation result of the item.

[0047] The first result of the transportation carbon footprint calculation can be the carbon emissions generated by a single item during the current transportation phase, that is, the carbon emissions of the transportation to which the item should be allocated, expressed in kilograms of carbon dioxide equivalent (kgCO). e).

[0048] This scheme can be calculated by multiplying the first transportation energy consumption parameter and the first load allocation parameter. For example, if the first transportation energy consumption parameter is 394.5 kg CO e. If the first load-bearing allocation parameter is 0.01, then the first transportation carbon footprint calculation result is 394.5 kg CO. e × 0.01 = 3.945 kg CO e, meaning the carbon emissions generated by the item during its current transport by the vehicle are 3.945 kg CO. e.

[0049] The technical solution provided in this embodiment realizes the automated collection of data on goods and vehicles, eliminating the need for manual data entry and effectively avoiding the errors and inefficiencies of manual recording. Simultaneously, by calculating transportation energy consumption parameters and load allocation parameters, the total carbon emissions of the vehicle are allocated according to the actual load proportion of the goods, ensuring the accuracy of the carbon footprint calculation results for individual goods transportation.

[0050] In one feasible embodiment, the method further includes: If the trajectory of the item does not match the current vehicle transport trajectory, a vehicle change event is determined to have occurred.

[0051] Trajectory coverage can be defined as the current vehicle's transportation trajectory completely encompassing the item's trajectory in both time and space. In other words, every location point of the item during the entire transportation phase falls within the corresponding time and space range of the current vehicle's transportation trajectory. For example, if the item's location points between 10:00 and 12:00 are the first and second points, and the current vehicle's location points during the same time period also completely cover this range, then it is considered trajectory coverage.

[0052] A vehicle change event can be a situation where goods are transferred from the original vehicle to another vehicle during transportation. For example, goods are planned to be transported from the factory to the logistics park by a small truck, but the small truck breaks down midway and is then transported by a medium-sized truck. This is a vehicle change event.

[0053] The process involves aligning the item's trajectory with the current vehicle's transport trajectory along the timeline. The spatial distance between the item's location point and the vehicle's location point at each time point is calculated. If the spatial distance at all time points is less than a preset threshold, such as less than 10 meters, the deviation of the item's position within the vehicle can be taken into account, and the current vehicle's transport trajectory is determined to cover the item's trajectory. If the spatial distance at some time points is greater than the preset threshold, or if the two location results are completely different after a certain time point, it can be determined that the item is not covered.

[0054] Specifically, when it is determined that the current vehicle's transportation trajectory does not cover the item's trajectory, the system combines the item's trajectory's time breakpoints or location changes to further retrieve the logistics park's base station data within that time period. If the item's location information is found to be related to the location information of another vehicle, then it is determined that a vehicle replacement event has occurred.

[0055] This technical solution, through trajectory coverage recognition, can automatically detect vehicle change events during the transportation of goods, avoiding omissions in carbon footprint accounting due to overlooking vehicle changes, and ensuring the completeness and accuracy of transportation carbon footprint accounting.

[0056] In one feasible embodiment, after determining that a vehicle change event has occurred, the method further includes: Obtain the location data of the replaced vehicle to analyze the transportation route after the replacement; Obtain the attribute and load information of the vehicle after replacement; The second transportation energy consumption parameter is determined based on the basic information of the item, the transportation route after replacement, and the attribute information of the vehicle after replacement. Based on the basic information of the item and the load-bearing information of the replaced vehicle, the second load-bearing allocation parameters are determined; The second transportation carbon footprint calculation result of the item is determined based on the second transportation energy consumption parameter and the second load allocation parameter; Based on the first transportation carbon footprint calculation result and the second transportation carbon footprint calculation result, the transportation carbon footprint calculation result of the goods is determined.

[0057] The replacement vehicle can be the vehicle used to transport the goods after the replacement event, for example, the original vehicle was a small truck and the replacement vehicle is a semi-trailer.

[0058] The location data of the replaced vehicle can be the location information reported by the passive tag attached to the replaced vehicle, in the same format as the current vehicle's location information, including latitude and longitude coordinates at various times. The transportation route after the replacement can be the path formed during the transportation of goods by the replaced vehicle, that is, the transportation path that the goods take after the replacement of the vehicle, such as the path from the logistics park to the destination.

[0059] The attribute information of the replaced vehicle can be the inherent attributes and operating characteristics of the replaced vehicle, such as the license plate number, type, rated load, fuel type and carbon emission factor of the replaced vehicle, which is consistent with the attribute information type of the current vehicle.

[0060] The load information of the replaced vehicle can be the actual load status data when the replaced vehicle transports the item, such as total load and total volume, which is consistent with the load information type of the current vehicle.

[0061] The second transportation energy consumption parameter can be a transportation energy consumption parameter calculated based on the transportation data of the replaced vehicle. It has the same definition and unit as the first transportation energy consumption parameter and reflects the correlation between energy consumption and carbon emissions during transportation using the replaced vehicle. For example, it can be the basic value of carbon emissions corresponding to the total energy consumption generated by the replaced vehicle in transporting goods.

[0062] The second load allocation parameter can be a load allocation parameter calculated based on the load data of the replaced vehicle. It has the same definition and value range as the first load allocation parameter and reflects the proportion of a single item in the total load of the replaced vehicle, that is, the carbon emission allocation coefficient of the item in the transportation stage of the replaced vehicle.

[0063] The second transportation carbon footprint accounting result can be the carbon emissions generated by a single item during the transportation phase after the change of vehicle. The transportation carbon footprint accounting result of an item can be the total carbon emissions generated by the item throughout the entire transportation process, that is, the cumulative value of the transportation carbon footprint accounting results at each stage.

[0064] This solution can associate the subsequent location points of the item's trajectory with the corresponding replacement vehicle, and then retrieve the location data of the replacement vehicle from the base station data. By sorting the location data, removing anomalies, and matching maps, a replacement transportation segment is generated. Furthermore, using the unique identifier of the replacement vehicle, its attribute information is retrieved from passive tag reporting data or the backend database. Its carrying information is obtained through the interaction data between the passive tags on the replacement vehicle and the base station. Then, a second transportation carbon footprint calculation result is calculated for the replacement vehicle transporting the item. Finally, based on the sum of the first and second transportation carbon footprint calculation results, if multiple vehicle replacements exist, the transportation carbon footprint calculation results corresponding to multiple replacement vehicles are accumulated to obtain the item's transportation carbon footprint calculation result.

[0065] This technical solution enables the calculation and accumulation of carbon emissions across multiple transportation segments, completely resolving the issue of incomplete carbon footprint accounting in vehicle-changing scenarios. Furthermore, its calculation logic is consistent with the original vehicle's accounting logic, ensuring the consistency and comparability of carbon emission data across different transportation stages. For example, in scenarios where a vehicle malfunctions during transportation, the goods may be transported to a different vehicle. This solution can then calculate and accumulate the carbon emissions for each segment to obtain a complete transportation carbon footprint.

[0066] In one feasible embodiment, the method further includes: Identify whether the current vehicle's return load status is empty; Accordingly, when the item trajectory matches the current vehicle transportation trajectory, a first transportation energy consumption parameter is determined based on the item's basic information, the current vehicle transportation trajectory, and the current vehicle's attribute information, including: The first transportation energy consumption parameter is determined based on the return load status, the basic information of the items, the current vehicle transportation trajectory, and the attribute information of the current vehicle.

[0067] The return load status refers to the load status of the vehicle when it returns from the destination to the departure point after completing the goods transportation task. It includes two situations: empty and loaded. Empty means that the vehicle does not carry any goods when returning, while loaded means that the vehicle carries other goods when returning.

[0068] "Empty" can refer to a situation where the total load or volume of a vehicle is zero during its return journey. For example, a vehicle might deliver goods to city A and then return to city B empty.

[0069] This solution can first determine the current transport direction of the vehicle, determine the outbound direction by the start and end points of the vehicle's transport trajectory, define the vehicle trajectory after the outbound end point as the return trajectory, and then retrieve the vehicle carrying information corresponding to the return trajectory to identify whether the return load status is empty.

[0070] This solution can identify the return load status of the vehicle and include the carbon emissions of the vehicle throughout the entire journey in the accounting scope, avoiding the underestimation of carbon footprint caused by only calculating the carbon emissions of the outbound journey, and further improving the accuracy of carbon footprint accounting.

[0071] In one feasible embodiment, a first transportation energy consumption parameter is determined based on the return load status, the basic information of the goods, the current vehicle transportation trajectory, and the attribute information of the current vehicle, including: Calculate using the following formula 1: Formula 1, ; in, The primary energy consumption parameter for transportation. For the quality of the item, This represents the energy consumption of the vehicle under a preset load rate. This represents the current transport trajectory distance of the vehicle. This represents the energy consumption value under load conditions during the return trip. This represents the vehicle's return mileage. If there is no empty return trip, the vehicle's return mileage is 0. The carbon emission factor of the vehicle.

[0072] When the vehicle is returning, the energy consumption per unit mileage is calculated based on the return load status. If the return trip is empty, the carbon emissions generated during the return trip can be included in the transportation of this item. If the return trip is loaded, they do not need to be calculated.

[0073] The technical solution provided in this embodiment can calculate the first transportation energy consumption parameter under different scenarios, fully consider whether the return trip is empty, improve the accuracy of carbon footprint accounting, and at the same time, this solution has strong adaptability and can be adapted to various goods transportation scenarios.

[0074] In one feasible embodiment, the first load allocation parameter is determined based on the basic item information and the load information, including: The first load allocation parameter is determined based on the mass of a single item in the basic item information and the total load information in the load information. or, The first load allocation parameter is determined based on the volume of a single item in the item's basic information and the total volume information in the load information.

[0075] Among them, the mass of a single item can be a parameter extracted from the basic information of the item, describing the weight of a single item, in kilograms (kg), for example, the mass of a single item is 5kg. The total load information can be the total weight of all items actually carried by the vehicle, extracted from the load information, in kilograms (kg), for example, the total load of the vehicle is 500kg.

[0076] The volume of a single item can be a parameter extracted from the item's basic information, describing the space occupied by a single item, and is expressed in cubic meters (m³) or cubic decimeters (dm³). For example, the volume of a single item is 0.1 m³. The total volume information can be the total volume of all items actually carried by the current vehicle, extracted from the carrying information, and is expressed in the same unit as the volume of a single item. For example, the total volume of the vehicle is 10 m³.

[0077] This technical solution provides two calculation methods for the first load-bearing allocation parameter. The appropriate calculation basis can be selected according to the attributes of the item. For example, for heavy goods, such as metal products, the calculation based on mass ratio is more in line with the actual load-bearing situation. For light goods, such as foam products, the calculation based on volume ratio is more reasonable. This improves the flexibility and accuracy of carbon footprint accounting and makes the carbon emission allocation of items reasonable in various scenarios.

[0078] In one feasible embodiment, a first load-bearing allocation parameter is determined based on the individual item mass in the item basic information and the total load information in the load-bearing information, including: Calculate using the following formula 2: Formula 2, ; in, Assign parameters to the first bearer. For the quality of the item, Let n be the number of items and n be the number of types of items.

[0079] The first load allocation parameter can be a carbon emission allocation coefficient for a single item based on its mass percentage, with a value range of 0-1. The number of item types can be the number of different types of items carried on the current vehicle. For example, the vehicle may carry three types of items: part A, part B, and part C. By calculating the total mass of all types of items, the total mass carried by the vehicle can be obtained.

[0080] This technical solution, through a clear summation formula, accurately calculates the mass proportion of a single item in scenarios with multiple item types, avoiding errors in the total load calculation caused by the vehicle carrying multiple items. It ensures that the calculation of the first load allocation parameter accurately reflects the actual proportion of a single item in the total load mass, providing a basis for subsequent accurate allocation of carbon emissions and thus obtaining accurate transportation carbon footprint accounting results.

[0081] In one feasible embodiment, the first load-bearing allocation parameter is determined based on the individual item volume in the item basic information and the total volume information in the load-bearing information, including: Calculate using the following formula 3: Formula 3, ; in, Assign parameters to the first bearer. For the volume of the item, Let n be the number of items and n be the number of types of items.

[0082] Among them, the first load allocation parameter R1 can be a carbon emission allocation coefficient for a single item based on volume ratio, with a value range of 0-1.

[0083] This technical solution, through a clear summation formula, accurately calculates the volume ratio of a single item in scenarios with multiple item types. It is particularly suitable for calculating the load-bearing allocation parameters of light and bulky goods, avoiding the problem of inaccurate calculations based solely on mass and the lack of a more accurate allocation algorithm, thus improving the accuracy and rationality of carbon emission allocation calculations.

[0084] In one feasible embodiment, the first transportation carbon footprint calculation result of the goods is determined based on the first transportation energy consumption parameter and the first load allocation parameter, including: The following formula, 4, is used for calculation: Formula 4, ; in, ; in, The first transportation carbon footprint accounting result for the goods. The primary energy consumption parameter for transportation. For the quality of the item, This represents the energy consumption of the vehicle under a preset load rate. This represents the current transport trajectory distance of the vehicle. This represents the energy consumption value under load conditions during the vehicle's return journey. This represents the mileage for the vehicle's empty return trip. If there is no empty return trip, the mileage is 0. The carbon emission factor of the vehicle.

[0085] The first transportation carbon footprint accounting result of an item can be the carbon emissions generated by a single item during the entire transportation phase of the current vehicle. It can be obtained by determining the mass or volume percentage of a single item after calculating the carbon emissions corresponding to the total energy consumption of the vehicle during the entire journey.

[0086] This technical solution directly links the total carbon emissions of the vehicle throughout its journey to the proportion carried by a single item, forming a standardized calculation logic for the carbon footprint of individual item transportation, and realizing the calculation from the total carbon emissions of the vehicle to the carbon emissions of a single item. Using this formula, the actual carbon footprint can be calculated quickly.

[0087] In one feasible embodiment, the method further includes: The system collects basic information about the items from the passive tags of the items via the base station at the origin; and collects vehicle attribute information from the passive tags of the vehicles used to transport the items. The system collects basic information about the items from the passive tags of the items via the base station at the point of arrival; and collects vehicle attribute information from the passive tags of the vehicle used to transport the items. Compare the vehicle attribute information at the starting point with the vehicle attribute information at the destination point to see if they are the same; If they are the same, then it is determined that there is no vehicle change event.

[0088] The starting point can be the initial location of goods transportation, such as the warehouse exit of a production factory, the loading point of a logistics park, or the shipping area of ​​an e-commerce warehouse.

[0089] The base station at the starting point can be a passive IoT base station deployed at the starting point to collect basic data on the departure of goods and vehicles, such as a fixed RFID base station at the exit of a factory warehouse.

[0090] The destination can be the target location for the transportation of goods, such as a destination distribution center, customer warehouse, or retail store.

[0091] The base station at the arrival point can be a passive IoT base station deployed at the arrival point to collect basic data on the arrival of goods and vehicles, such as a fixed RFID base station at the entrance of a distribution center.

[0092] The basic information of the items must be the same, meaning that the basic information of the items collected at the origin point and the basic information of the items collected at the destination point must be completely consistent, ensuring that the comparison is of the transportation data of the same item.

[0093] If the vehicle attribute information is the same, it means that the unique identifier in the vehicle attribute information collected at the departure point is exactly the same as the unique identifier in the vehicle attribute information collected at the arrival point, indicating that the vehicle used to transport the item has not been changed.

[0094] This solution first associates the item data at the starting point and the destination point through the item's unique code to confirm that the item's basic information is the same. Then, it extracts the unique identifier from the vehicle attribute information at the starting point and the destination point. If the two are completely consistent, it is determined that there is no vehicle change event. If they are inconsistent, it is determined that there is a vehicle change event.

[0095] This technical solution provides an alternative method for detecting vehicle replacement events, namely, comparing vehicle attribute information between the starting point and the destination point. This method does not require complex trajectory analysis; it can quickly determine whether a vehicle has been replaced simply by comparing key data between the starting point and the destination. It is suitable for scenarios such as short-distance transportation and fixed-route transportation, improving the efficiency of vehicle replacement detection and reducing the amount of data processing.

[0096] In one feasible embodiment, the method further includes: Obtain the production information of the item; Based on the production information, determine the carbon footprint accounting result of the production of the item; Based on the production carbon footprint accounting results and the transportation carbon footprint accounting results, the total carbon footprint accounting result of the item is determined.

[0097] Among them, the production information of the goods can be data related to carbon emissions generated during the production process, including energy consumption information during the production stage, such as the electricity consumption and fuel consumption of production equipment, raw material usage information, such as the types and quantities of raw materials and their corresponding carbon emissions, and production process information, such as whether low-carbon processes are used.

[0098] The production carbon footprint accounting result can be the total carbon emissions generated during the production stage of an item, expressed in kilograms of carbon dioxide equivalent.

[0099] The total carbon footprint accounting result can be the total carbon emissions generated by an item from the production stage to the transportation stage, that is, the sum of the production carbon footprint accounting result and the transportation carbon footprint accounting result.

[0100] This solution can retrieve production information for an item from the manufacturer's MES (Manufacturing Execution System), ERP (Enterprise Resource Planning) system, or a third-party carbon footprint database using the item's unique code. For example, it can automatically obtain energy consumption and raw material data during the production phase by interface with the manufacturer's database, thus obtaining the production carbon footprint calculation result. The production carbon footprint calculation result is then added to the transportation carbon footprint calculation result to obtain the total carbon footprint calculation result.

[0101] This technical solution achieves partial integration of the carbon footprint of an item throughout its entire lifecycle, avoiding the limitation of focusing only on carbon emissions from transportation while ignoring carbon emissions from production. It provides comprehensive carbon footprint data, facilitating carbon footprint management and the application of relevant information.

[0102] To enable those skilled in the art to better understand this solution, this application also provides a preferred embodiment.

[0103] This system leverages the characteristics of passive IoT, such as being unpowered, having strong sensing capabilities, and being widely applicable. A passive IoT data receiving and processing platform was developed, relying on the interaction of tag information within the signal coverage area of ​​base stations to efficiently collect key parameters for carbon footprint accounting of goods and vehicles during transportation using passive tags. This enables rapid batch inventory of all goods and vehicles within the range of the base station, overcoming the limitations of traditional RFID and manual data entry methods, which require individual scanning and are inefficient. This creates a transportation carbon footprint accounting and management system that supports real-time collection and tracking of carbon emission data in transportation scenarios. Secondly, based on the globally unique attribute of passive tag IDs, binding passive tags to goods, compared to ordinary tags, allows for one-item-one-code end-to-end supply chain tracking of individual goods. Goods information cannot be tampered with, improving the granularity of supply chain information management and optimizing supply chain transparency and information tamper-proofing.

[0104] Figure 2 This is a schematic diagram of the transportation carbon footprint accounting and management system based on passive Internet of Things provided in this embodiment. Figure 2 As shown, the workflow of the carbon footprint accounting system based on passive IoT is divided into two stages: Phase 1: Product Shipment and 'Carbon Label' Generation. The product supplier associates basic information about the product, such as product type, weight, and specifications, with the passive carbon footprint label. This information serves as the basic data for carbon footprint accounting and is passed to the carbon footprint accounting tool.

[0105] Phase 2: Transportation activity data collection is divided into two methods: scenarios with base stations and scenarios without base stations. In scenarios with base stations: The passive carbon tag of the goods and the passive vehicle tag of the vehicle (such as a truck) interact with each other through a cellular passive base station to collect data such as fuel / electricity consumption per 100 kilometers and empty load status of the vehicle.

[0106] In base station-free scenarios: By combining vehicle-mounted positioning terminals, such as GPS, with the vehicle's passive vehicle tag, data such as fuel / electricity consumption per 100 kilometers and empty load status of the vehicle can be collected.

[0107] Passive data collected during the transportation of goods and vehicles is transmitted to a passive IoT data receiving and processing platform. After processing, it becomes passive data and is then passed to a carbon footprint accounting tool. The carbon footprint accounting tool combines the carbon label data from the goods' factory and the passive data from the transportation phase to perform carbon footprint accounting, and finally outputs the carbon footprint data of the goods for applications such as generating carbon labels for the goods.

[0108] The steps involved in building a transportation carbon footprint accounting and management system based on passive Internet of Things are as follows: Step 1: Development of a Passive IoT Data Receiving and Processing Platform. This platform supports receiving various types of passive tag information and GPS information, and performs data preprocessing to generate parameters related to transportation carbon footprint accounting, supporting high-precision transportation carbon footprint accounting. The carbon footprint results are then written to passive tag records through the passive IoT data receiving and processing platform. The passive IoT data receiving and processing platform includes a passive data management module, a GPS data management module, a product transportation data analysis module, and a passive carbon tag management module.

[0109] The passive data management module, based on the interaction data between base stations and passive tags, comprehensively manages the information of goods and vehicles in the transportation process. By maintaining passive tags, it supports functions such as adding tags, tag binding details, and passive tag inventory. During the shipment stage, suppliers use the platform to enter the specifications of the goods, such as product category, weight, volume, packaging, and manufacturing carbon emissions, in the form of passive tags and bind them to the corresponding products. Similarly, the transporter uses the platform to bind the vehicle information of the transport vehicle, such as fuel type, fuel / electricity consumption per 100 kilometers, and empty load rate, to the transport vehicle in the form of passive tags. By comparing the passive information of goods and vehicles during transportation and the receiving stage, key parameters for transportation carbon emission accounting are recorded. The passive data management module supports adding, deleting, and searching passive tags. Passive tag ID search quickly displays corresponding tag information, such as tags "unbound" or "bound," tag categories "product" or "vehicle," and tag status "normal" or "invalid." Passive tag inventory checks are performed on vehicles and goods passing through each base station's range based on the transportation phase time series. The inventory results display information such as inventory time, inventory status, and the number of passive tags, and support filtering and searching for specific tags based on the inventory results, as well as updating the status of a specific tag by time.

[0110] The GPS data management module primarily addresses the current situation where passive base stations are not yet widespread. It uses GPS data to supplement transportation data from base stations along the route, recording the cargo transportation trajectory. In areas with well-developed passive base station infrastructure, information can be exchanged between base stations and passive tags within their receiving range to achieve real-time recording of vehicle trajectories and cargo status. In areas without passive base station infrastructure, vehicle-mounted positioning terminals can be installed on the vehicles to generate transportation trajectories in real-time via GPS or BeiDou data. Cargo status information is mainly obtained from warehouse base stations at the shipping and receiving warehouses. Through real-time GPS data recording, the actual transportation trajectory of the vehicle is generated based on a map, and the transportation mileage is automatically calculated.

[0111] The product transportation data analysis module, based on completed transportation projects, statistically analyzes key parameters such as the physical properties, transportation status, historical trajectory, and vehicle load of various goods, and allocates the total emissions of corresponding transportation activities among different goods based on carbon emission accounting formulas. Figure 3 This is a schematic diagram of the various transportation project information presented on the display platform provided in this embodiment, such as... Figure 3 As shown, the information displayed may include the transportation project ID, transportation project name, license plate number, quantity of transported products, transportation start time, transportation end time, and transportation distance. Figure 4 This is a schematic diagram illustrating the analysis of energy consumption parameters for cargo transportation provided in this embodiment. For example... Figure 4 As shown, it can display the calculation parameter types of the data statistical analysis interface, including whether it is an empty return trip, the quantity of transported products, the mass (kg) of transported products, the volume (m3) of transported products, the load (t), the start and end time of transport, the transport distance (km), and the transport fuel consumption (L). Based on the above parameters, the transport proportion value is calculated, representing the mass and volume proportion of related products, which is used to allocate the total carbon emissions of transport among goods. The mass proportion has the sum of the mass of the products as the denominator, and the volume proportion has the sum of the volume of the products as the denominator. The energy consumption of cargo transportation is calculated by summarizing the energy consumption data, mass proportion, or volume proportion data of a specific vehicle under different load rates.

[0112] The passive carbon label management module is primarily responsible for writing carbon footprint information into the passive labels. Based on product transportation result analysis parameters, the carbon footprint accounting tool generates the transportation carbon footprint of individual goods. This data, along with the product manufacturing carbon footprint obtained from the carbon footprint accounting tool before shipment, is written into the product's passive carbon label through the carbon label data management module. Figure 5 This is a schematic diagram of the interface of the passive carbon tag management module provided in this embodiment. Figure 5 As shown, carbon tags bind carbon tag IDs (carbon footprint), product IDs, and passive tag IDs through ID association. Carbon tag statuses are categorized as "inactive, normal, invalid, and obsolete." The definitions of each carbon tag status are as follows: Not activated: The specific carbon tag ID, the corresponding passive tag ID, and the passive carbon tag status is not activated.

[0113] Normal: The specific carbon tag ID corresponds to the passive tag ID, and the passive carbon tag status is normal.

[0114] Expired: The specific carbon tag ID, the corresponding passive tag ID, and the passive carbon tag status is expired.

[0115] Obsolete: Specific carbon tag ID, corresponding passive tag ID, passive carbon tags are obsolete.

[0116] Step 2: Product Carbon Footprint Model Development. Using the input-output data format of each process unit within the accounting system as a template, obtain the corresponding activity data such as material flow, energy flow, and emissions flow. Then, complete the construction and calculation of the corresponding product carbon footprint model using the carbon footprint accounting tool.

[0117] The carbon footprint of goods manufacturing is calculated based on the unit process input-output data provided by the supplier, and the data is transmitted to a passive IoT data receiving and processing platform. This platform adds the carbon footprint values ​​to passive carbon footprint tags, and binds the corresponding carbon footprint tags to specific goods in a product-tag ID association format. Formula 5 for calculating the manufacturing carbon footprint (i.e., carbon emissions up to the point of leaving the factory) of transported goods is as follows: Formula 5, ; in, This represents the total carbon emissions from m production processes in product P, expressed in kgCO2e. The total energy or fuel i required for production process m, expressed in kilowatt-hours (kWh), cubic meters (m³), or kilograms (kg), etc. Carbon emission factor of energy or fuel i required for production process m, in units of kgCO2e / kwh, kgCO2e / m³, and kgCO2e / kg; This refers to the total consumption of material j required for production process m, expressed in kilograms (kg). Material j should include the consumption of consumable materials allocated to each unit of process. The carbon emission factor per unit material of material j required for production process m is expressed in kgCO2e / kg. The total emissions of greenhouse gases e (such as CO2, CH4, N2O, etc.) directly emitted from production process m, expressed in kg. This represents the greenhouse gas equivalent value of the directly emitted greenhouse gas e generated by production process m, expressed in kgCO2e / kg.

[0118] Based on the preprocessed transportation data parameters of the passive IoT data receiving and processing platform, the carbon footprint accounting tool incorporates the transportation carbon footprint accounting result ID of each product into the corresponding passive carbon tag. The transportation carbon footprint accounting formula for each individual product during the transportation stage is as follows: Formula 6, ; in, This represents the carbon emissions of goods P during transportation, expressed in kgCO2e. The mass of the item P is expressed in kilograms (kg). Let P be the quantity of the item, in pieces. The fuel or electricity consumption per 100 kilometers for vehicle v under load factor q1 is expressed in L / 100km or kWh / 100km. The distance traveled by vehicle v during the delivery phase is expressed in km. The fuel or electricity consumption per 100 kilometers of vehicle v under no-load return conditions with a load rate of zero, expressed in L / 100km or kWh / 100km. This represents the distance traveled by vehicle v during the empty return trip, in km. If there is no empty return trip, the distance traveled is zero. The carbon emission factor of the electricity or fuel i required for vehicle v is expressed in kgCO2e / kwh or kgCO2e / L.

[0119] The actual load factor q1 of vehicle V is calculated by dividing the total weight of the transported goods by the theoretical maximum load capacity (Hmax) of the vehicle. The specific calculation formula is as follows: Formula 7, ; Step 3: Hardware Development of the Passive IoT Transportation Carbon Footprint Accounting and Management System. The hardware required for this system includes passive IoT base stations, passive tags, and vehicle-mounted positioning terminals. Based on the surface physical characteristics of the transported goods, suitable passive tags will be designed from the perspectives of energy consumption requirements and environmental adaptability. The current deployment of passive base stations needs to consider their installation locations. Given the current anti-interference capabilities of base stations, the ideal installation location is near the warehouse entrance; specific locations can be chosen that cover both the goods storage area and the loading vehicle area. Vehicle-mounted positioning terminals require modification based on the specific characteristics of the vehicles.

[0120] Passive carbon tags can support the automated and efficient recording of a product's carbon footprint information throughout the entire process, from raw material acquisition and manufacturing to logistics and transportation, and in each stage. In the future, this carbon tag can also be linked to the carbon footprint information of the product during the warehousing and usage stages, and together with the carbon emission information during the disposal stage, form a complete "cradle to grave" carbon footprint of the product.

[0121] This technical solution utilizes passive IoT technology in methods for storing and recording carbon footprint information, collecting transportation carbon footprint activity data, and constructing transportation carbon footprint models. Compared with existing transportation carbon footprint accounting methods and carbon label disclosure, it improves the granularity of carbon footprint data collection and the accuracy and traceability of accounting results.

[0122] This solution leverages the characteristics and potential cost advantages of passive IoT technologies, such as being non-powered, having strong sensing capabilities, and being tamper-proof, to achieve efficient data collection, optimized data granularity, and verifiable end-to-end tracking in transportation scenarios. Compared to traditional RFID tag data recording technology, passive IoT carbon tags can quickly exchange information with items and vehicles passing near base stations during transportation, eliminating the need to stop and scan each item individually. This satisfies the requirements for real-time tracking management and rapid data collection during transportation. Furthermore, based on the globally unique attribute of passive tag IDs, with a sufficient number of base stations along the route, the passive IoT transportation carbon footprint accounting management system can achieve "one item, one code" product tracking throughout the entire process, compared to the "GPS+RFID" model, and the data cannot be tampered with midway. GPS tracking and positioning are not limited to the vehicle level and cannot locate the goods level. RFID or QR code tags pose risks such as data loss during transportation, failure to detect lost or replaced goods, and easy data tampering. Therefore, the transportation carbon footprint accounting management system based on passive technology has achieved a qualitative leap from quantitative change. It overcomes the limitations of traditional technical solutions in achieving high-precision transportation carbon footprint accounting and full-process tracking management of goods during logistics.

[0123] Based on the aforementioned technologies, this system has developed a passive IoT data receiving and processing platform to receive and process passive data, providing key parameters for carbon footprint accounting tools and enabling the writing of carbon footprint accounting results into passive tags. Based on the passive IoT-based transportation carbon footprint accounting management standard, this proposal puts forward corresponding carbon footprint accounting formulas, clarifies the types of parameters that need to be collected, and outlines detailed operational steps for constructing a passive IoT-based carbon footprint accounting management platform. This guides industry personnel in building an efficient and accurate digital platform for transportation carbon footprints and provides reliable data support for carbon footprint disclosure and carbon trading.

[0124] Figure 6 This is a schematic diagram of a carbon footprint accounting device based on passive Internet of Things provided in an embodiment of this application. Figure 6 As shown, the device may include: an information collection module 610, a trajectory determination module 620, a transportation energy consumption parameter determination module 630, a load allocation parameter determination module 640, and a transportation carbon footprint calculation module 650. The information collection module 610 is used to acquire basic information about the item and the item's location information, as well as to acquire the attribute information, vehicle location information, and carrying information of the current vehicle used to transport the item. The trajectory determination module 620 is used to parse the trajectory of an item based on the item's location information, and to parse the current vehicle's transportation trajectory based on the vehicle's location information; The transportation energy consumption parameter determination module 630 is used to determine a first transportation energy consumption parameter based on the basic information of the item, the transportation trajectory of the current vehicle, and the attribute information of the current vehicle when the trajectory of the item matches the transportation trajectory of the current vehicle. The load allocation parameter determination module 640 is used to determine the first load allocation parameter based on the basic information of the item and the load information; The transportation carbon footprint calculation module 650 is used to determine the first transportation carbon footprint calculation result of the item based on the first transportation energy consumption parameter and the first carrying capacity allocation parameter.

[0125] The carbon footprint accounting device based on passive Internet of Things provided in this embodiment has the same functional modules and beneficial effects as the carbon footprint accounting method based on passive Internet of Things described above. To avoid repetition, it will not be described in detail here.

[0126] Figure 7 This is a schematic diagram of the structure of a carbon footprint accounting device based on passive Internet of Things provided in an embodiment of this application. Figure 7 As shown, a carbon footprint accounting device based on passive Internet of Things may include a processor 701 and a memory 702 storing computer program instructions.

[0127] Specifically, the processor 701 may include a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0128] Memory 702 may include mass storage for data or instructions. For example, and not limitingly, memory 702 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. In one instance, memory 702 may include removable or non-removable (or fixed) media, or memory 702 may be non-volatile solid-state memory. Memory 702 may be internal or external to the integrated gateway disaster recovery device.

[0129] In one instance, memory 702 may be read-only memory (ROM). In one instance, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), an electrically rewritable ROM (EAROM), or flash memory, or a combination of two or more of these.

[0130] Memory 702 may include read-only memory (ROM), random access memory (RAM), disk storage media device, optical storage media device, flash memory device, electrical, optical, or other physical / tangible memory storage device. Therefore, generally, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to one aspect of this disclosure.

[0131] The processor 701 reads and executes computer program instructions stored in the memory 702 to implement the carbon footprint accounting method based on passive Internet of Things in the above embodiments.

[0132] In one example, a carbon footprint accounting device based on passive IoT may also include a communication interface 703 and a bus 704. For example, Figure 7 As shown, the processor 701, memory 702, and communication interface 703 are connected through bus 704 and complete communication with each other.

[0133] The communication interface 703 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0134] Bus 704 includes hardware, software, or both, that couples components of a carbon footprint accounting device based on passive Internet of Things (IoT) together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 704 may include one or more buses. While specific buses are described and illustrated in embodiments of this application, this application contemplates any suitable bus or interconnect.

[0135] The carbon footprint accounting device based on passive Internet of Things can execute the carbon footprint accounting method based on passive Internet of Things in the embodiments of this application, thereby realizing the carbon footprint accounting method based on passive Internet of Things described in the above embodiments.

[0136] Furthermore, in conjunction with the carbon footprint accounting device method based on passive Internet of Things in the above embodiments, this application embodiment can provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the carbon footprint accounting device methods based on passive Internet of Things in the above embodiments.

[0137] This application also provides a computer program product, including a computer program that, when executed by a processor, implements any of the carbon footprint accounting device methods based on passive Internet of Things described above.

[0138] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0139] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, read-only memory (ROM), flash memory, erasable read-only memory (EROM), floppy disks, compact disc read-only memory (CD-ROM), optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0140] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0141] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowchart illustrations, and combinations of blocks in the block diagrams and / or flowchart illustrations, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0142] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A passive Internet of Things based carbon footprint accounting method, characterized in that, The method comprises: acquiring item basic information and item positioning information, and acquiring attribute information, carrier positioning information and carrying information of a current carrier used for transporting the item; resolving an item trajectory according to the item positioning information, and resolving a current carrier transportation trajectory according to the carrier positioning information; in a case where the item trajectory matches the current carrier transportation trajectory, determining a first transportation energy consumption parameter according to the item basic information, the current carrier transportation trajectory and the attribute information of the current carrier; determining a first carrying allocation parameter according to the item basic information and the carrying information; determining a first transportation carbon footprint accounting result of the item according to the first transportation energy consumption parameter and the first carrying allocation parameter. 2.The passive Internet of Things based carbon footprint accounting method according to claim 1, characterized in that, The method comprises: acquiring item basic information and item positioning information, and acquiring attribute information, carrier positioning information and carrying information of a current carrier used for transporting the item; acquiring attribute information, carrier positioning information and carrying information of a current carrier used for transporting the item, comprising: acquiring attribute information, carrier positioning information and carrying information of a current carrier used for transporting the item, comprising: 3.The passive Internet of Things based carbon footprint accounting method according to claim 1, characterized in that, The method further comprises: in a case where the item trajectory does not match the current carrier transportation trajectory, determining that there is a carrier replacement event. 4.The passive Internet of Things based carbon footprint accounting method according to claim 3, characterized in that, After determining that there is a carrier replacement event, the method further comprises: acquiring positioning data of the carrier after replacement to resolve a replacement transportation section; acquiring attribute information and carrying information of the carrier after replacement; determining a second transportation energy consumption parameter according to the item basic information, the replacement transportation section and the attribute information of the carrier after replacement; determining a second carrying allocation parameter according to the item basic information and the carrying information of the carrier after replacement; determining a second transportation carbon footprint accounting result of the item according to the second transportation energy consumption parameter and the second carrying allocation parameter; determining a transportation carbon footprint accounting result of the item according to the first transportation carbon footprint accounting result and the second transportation carbon footprint accounting result. 5.The passive Internet of Things based carbon footprint accounting method according to claim 1, wherein, The method further comprises: identifying whether a return load state of the current carrier is empty; determining a first transportation energy consumption parameter according to the item basic information, the current carrier transportation trajectory and the attribute information of the current carrier, comprising: determining a first transportation energy consumption parameter according to the return load state, the item basic information, the current carrier transportation trajectory and the attribute information of the current carrier. 6.The passive Internet of Things based carbon footprint accounting method according to claim 5, characterized in that, determining a first transportation energy consumption parameter according to the return load state, the item basic information, the current carrier transportation trajectory and the attribute information of the current carrier, comprising: calculating according to the following formula: ； wherein, is a first transport energy consumption parameter, is a mass of the item, is an energy consumption value of the carrier under a preset load rate, is a current carrier transport track mileage, is an energy consumption value under a load state of the return trip, is a carrier return trip mileage, if there is no empty return trip case, the carrier return trip mileage is 0, is a carbon emission factor of the carrier. 7.The passive Internet of Things based carbon footprint accounting method according to claim 1, wherein, determining a first carrying allocation parameter according to the item basic information and the carrying information, comprising: determining a first carrying allocation parameter according to single item mass in the item basic information and total load information in the carrying information; or determining a first carrying allocation parameter according to single item volume in the item basic information and total volume information in the carrying information. 8.The passive Internet of Things based carbon footprint accounting method according to claim 7, characterized in that, According to the single item quality in the item basic information and the total load information in the carrying information, a first carrying distribution parameter is determined, including: The following formula is used for calculation: ； wherein, allocating parameters for the first bearer, a quality of the item, a quantity of the item, n is a number of types of the item; Or, The following formula is used for calculation: ； wherein, allocating parameters for the first bearer, for a volume of the item, for a number of the item, n is a number of kinds of the item. 9.The passive Internet of Things based carbon footprint accounting method according to claim 8, characterized in that, According to the first transportation energy consumption parameter and the first carrying distribution parameter, a first transportation carbon footprint accounting result of the item is determined, including: The following formula is used for calculation: ； ； wherein, is a first transportation carbon footprint accounting result for the item, is a first transportation energy consumption parameter, is a mass of the item, is an energy consumption value of the carrier under a preset load rate, is a current carrier transportation track mileage, is an energy consumption value of the carrier under a load state of return, is a carrier empty return mileage, if there is no empty return case, the driving mileage is 0, is a carbon emission factor of the carrier. 10.The passive Internet of Things based carbon footprint accounting method according to claim 1, wherein, The method further includes: Through the base station at the departure point, item basic information reported by the passive tag of the item is collected; and carrier attribute information reported by the passive tag of the carrier used for transporting the item is collected; Through the base station at the arrival point, item basic information reported by the passive tag of the item is collected; and carrier attribute information reported by the passive tag of the carrier used for transporting the item is collected; Whether the departure point carrier attribute information is the same as the arrival point carrier attribute information is compared; If the same, it is determined that there is no carrier replacement event. 11.The passive Internet of Things based carbon footprint accounting method according to claim 1, wherein, The method further includes: Production information of the item is obtained; According to the production information, a production carbon footprint accounting result of the item is determined; According to the production carbon footprint accounting result and the transportation carbon footprint accounting result, a total carbon footprint accounting result of the item is determined. 12.A passive Internet of Things (IoT) -based carbon footprint accounting device, comprising: The device includes: An information collection module is configured to obtain item basic information and item positioning information, and obtain attribute information, carrier positioning information and carrying information of a current carrier used for transporting the item; A trajectory determination module is configured to analyze an item trajectory according to the item positioning information, and analyze a current carrier transportation trajectory according to the carrier positioning information; A transportation energy consumption parameter determination module is configured to, in the case that the item trajectory matches the current carrier transportation trajectory, determine a first transportation energy consumption parameter according to the item basic information, the current carrier transportation trajectory and the attribute information of the current carrier; A carrying distribution parameter determination module is configured to determine a first carrying distribution parameter according to the item basic information and the carrying information; A transportation carbon footprint accounting module is configured to determine a first transportation carbon footprint accounting result of the item according to the first transportation energy consumption parameter and the first carrying distribution parameter. 13.A passive Internet of Things (IoT) -based carbon footprint accounting device, comprising: The device includes a processor and a memory storing computer program instructions; the processor reads and executes the computer program instructions to implement the passive Internet of Things based carbon footprint accounting method according to any one of claims 1-11.

14. A computer-readable storage medium, characterized in that, The computer storage medium stores computer program instructions, and the computer program instructions are executed by the processor to implement the passive Internet of Things based carbon footprint accounting method according to any one of claims 1-11.

15. A computer program product, characterised in that, The computer program is executed by the processor to implement the passive Internet of Things based carbon footprint accounting method according to any one of claims 1-11.

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