Description:

FIELD OF INVENTION
[0001] The present disclosure relates to green logistics solutions, and particularly relates to system and method for diagnosing and managing carbon footprints in road logistics.

BACKGROUND
[0002] The transportation and logistics industry are key drivers of global economic activity, responsible for the movement of goods across vast distances. However, this sector is also one of the largest contributors to greenhouse gas emissions, particularly carbon dioxide (CO2), primarily due to the widespread use of fossil fuels in road-based transportation. According to the International Energy Agency (IEA), the transportation sector accounts for nearly 25% of global energy-related CO2 emissions, with road freight accounting for a significant portion of these emissions. As concerns over climate change grow, governments, organizations, and the public are increasingly focused on reducing the environmental impact of transportation operations.
[0003] Globally carbon emission from road logistics has a contribution of approx. 27%, whereas in India, it is found to be more than 50%. Despite the growing pressure to reduce carbon emissions, there is a lack of integrated solutions that allow logistics providers to accurately diagnose, track, and manage their carbon footprint in real time. Existing systems either focus on vehicle diagnostics without factoring in the broader environmental impact or provide static reports that are not actionable.
[0004] Consequently, efforts have been made previously to provide management of carbon emissions. For instance, China Patent No.113592187A discloses an intelligent carbon emission management system and method, which can predict the amount of carbon emission and assist carbon emission index trading according to the prediction result. The system generates predicted carbon emission based on the carbon emission data and emission reduction data, and compare the predicted carbon emission and carbon emission indicators to generate judgement results. However, the system and method are only limited to the carbon emission prediction for company or industrial enterprises.
[0005] United States Patent No. 20200372588 A1 discloses methods and systems for machine-learning for prediction of grid carbon emissions. The artificial intelligence and machine-learning methods are used to estimate real-time emission impacts based on grid data. Deep learning for real-time or online optimization and control may be used to minimize emission impacts while maximizing efficiency benefits under uncertainties of the ambient environment and user behaviors. A result may be a real-time data-driven software platform that implements methods and provides intuitive, compelling real-time visualizations. However, the methods and systems only disclose grid carbon emission which regards to emission of atmospheric carbon due to production and/or consumption of electrical energy in an electrical power grid. It does not include other carbon emission, carbon off-set.
[0006] Further, with the European Union imposing the Carbon Border Adjustment Mechanism (CBAM) in its transitional phase (2023-2025) and becoming fully active in 2026, it is imperative for our industry to take proactive and rapid measures to diagnose, reduce, and offset carbon footprints to safeguard our industry and exports.
[0007] Therefore, there remains a need for a comprehensive and innovative solution for diagnosing, managing, and reducing carbon footprints in road logistics. Keeping this in mind, design and development of a system and method for diagnosing and managing carbon footprints in road logistics is presented. The invention leverages real-time data and optimization algorithms, thereby contributing to reducing environmental impacts while improving operational efficiency.
[0008] The invention aims to educate, create awareness, promote plantation of trees, reduce greenhouse effect, and recreate prakruti with the invention i.e. “Pure ???????” application. Therefore, the aim of “Pure ???????” is to save Mother Earth from carbon emissions, Pure ??????? version 1.0 is focused on reducing the maximum carbon emitter factor in India (road logistics).
[0009] Accordingly, we have designed, introduced, validated, collaborated and executed world’s first systematic SaaS based carbon auditing platform for road logistics in India. Pure ??????? application is designed to diagnose the carbon footprint on cargo vehicles for each and every transaction within a fraction of seconds. The app also provides nature oriented practical solution to offset carbon emissions to meet our end goal of supporting the initiative of net zero.

OBJECTS OF THE INVENTION
[0010] It is an object of the present disclosure which provides a system and method for diagnosing and managing carbon footprints in road logistics.
[0011] It is an object of the present disclosure which provides a comprehensive and innovative solution for diagnosing, managing, and reducing carbon footprints in road logistics.
[0012] It is yet another object of the present disclosure which provides leveraging real-time data and optimization algorithms, thereby contributing to reducing environmental impacts while improving operational efficiency.

SUMMARY
[0013] The present disclosure is directed towards a system and method for diagnosing and managing carbon footprints in road logistics. The system comprising of a personal computing unit selected from a mobile or a computer; an application program installed in the personal computing unit; a cloud server configured to wirelessly trans-receive information with the application program for storage and processing, wherein the cloud server is configured to utilize ULIP data driven technique to process atleast one information from the application program to generate atleast one output; and a wireless internet network to enable real-time data transmission.
[0014] In an aspect of the present disclosure, the atleast one information comprising details of atleast one vehicle including Source and Destination Pin Codes, Loaded Weight of Vehicle, Transit distance, Loading and Unloading distance, and wherein the atleast one output comprising carbon emission corresponding to the atleast one vehicle.
[0015] In an aspect of the present disclosure, the atleast one output generated by calculating a plurality of metrics including Distance calculation, Emission Factor, Loaded Weight.
[0016] In an aspect of the present disclosure, the cloud server comprises a database to store and retrieve user and vehicular data.
[0017] The present disclosure is also directed towards a method for diagnosing and managing carbon footprints in road logistics. The method comprising of authenticating a user for access using user details by an application program installed on a personal computing unit; receiving atleast one information from the user using the application program; transmitting each of the atleast one information to a cloud server using a wireless network, wherein the personal computing unit is configured to wirelessly communicate with the cloud server; validating and processing each of the atleast one information by the cloud server; and generating atleast one output of the atleast one information based on the processing.
[0018] In an aspect of the present disclosure, the receiving the atleast one information comprising details of atleast one vehicle including Source and Destination Pin Codes, Loaded Weight of Vehicle, Transit distance, Loading and Unloading distance.
[0019] In another aspect of the present disclosure, the generating the atleast one output comprising carbon emission corresponding to the atleast one vehicle.
[0020] In another aspect of the present disclosure, the generating the atleast one output utilizing ULIP data driven technique.
[0021] In another aspect of the present disclosure, the generating the atleast one output by calculating a plurality of metrics including Distance calculation, Emission Factor, Loaded Weight.
[0022] In another aspect of the present disclosure, the method further including recommending atleast one action to the user based on the generated output, wherein the recommending atleast one action including planting a specified number of trees corresponding to the carbon emission.

BRIEF DESCRIPTION OF THE DRAWINGS
[0023] The accompanying drawings are included to provide a further understanding of the present disclosure and are incorporated in and constitute a part of this specification. The drawings illustrate exemplary embodiments of the present disclosure and, together with the description, serve to explain the principles of the present disclosure.
[0024] FIG. 1 illustrates a flowchart of an embodiment of method for diagnosing and managing carbon footprints in road logistics in accordance with the present disclosure.
[0025] FIG. 2 illustrates a carbon footprint calculator in accordance with embodiments of the present disclosure.
[0026] FIG. 3 illustrates exemplary user information input as shown in application display screen in accordance with embodiments of the present disclosure.
[0027] FIG. 4 illustrates exemplary vehicle information input as shown in application display screen in accordance with embodiments of the present disclosure.
[0028] FIG. 5 illustrates exemplary calculated output of vehicular carbon emission as shown in application display screen in accordance with embodiments of the present disclosure.
[0029] FIG. 6 illustrates exemplary recommended action for vehicle user as shown in application display screen in accordance with embodiments of the present disclosure.

DETAILED DESCRIPTION
[0030] Aspects of the present disclosure relate to system and method for diagnosing and managing carbon footprints in road logistics.
[0031] The following is a detailed description of embodiments of the disclosure. The embodiments are in such detail as to clearly communicate the disclosure. However, the amount of detail offered is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the present disclosure as defined by the appended claims.
[0032] The present disclosure is directed towards a system and method for diagnosing and managing carbon footprints in road logistics. The system comprising of a personal computing unit selected from a mobile or a computer; an application program installed in the personal computing unit; a cloud server configured to wirelessly trans-receive information with the application program for storage and processing; and a wireless internet network to enable real-time data transmission. The cloud server is configured to utilize ULIP data driven technique to process atleast one information from the application program to generate atleast one output.
[0033] In an embodiment of the present disclosure, the atleast one information comprising details of atleast one vehicle including Source and Destination Pin Codes, Loaded Weight of Vehicle, Transit distance, Loading and Unloading distance. The atleast one output comprising carbon emission corresponding to the atleast one vehicle. The atleast one output generated by calculating a plurality of metrics including Distance calculation, Emission Factor, Loaded Weight. The cloud server comprises a database to store and retrieve user and vehicular data.
[0034] In an embodiment of the present disclosure, the method for diagnosing and managing carbon footprints in road logistics is disclosed. The method comprising of authenticating a user for access using user details by an application program installed on a personal computing unit; receiving atleast one information from the user using the application program; transmitting each of the atleast one information to a cloud server using a wireless network; validating and processing each of the atleast one information by the cloud server; and generating atleast one output of the atleast one information based on the processing. The personal computing unit is configured to wirelessly communicate with the cloud server. Figure 1 discloses a flowchart of an embodiment of method for diagnosing and managing carbon footprints in road logistics.
[0035] In an embodiment of the present disclosure, the receiving the atleast one information or input comprising details of atleast one vehicle including Source and Destination Pin Codes, Loaded Weight of Vehicle, Transit distance, Loading and Unloading distance.
[0036] INPUT INFORMATION-
1. Source and Destination Pin Codes:
•Users input the starting and ending locations of their journey using pin codes.
•The system calculates the direct distance between these two points.
2. Loaded Weight of Vehicle:
•Users provide the total weight of the vehicle when loaded.
•Heavier loads generally result in higher fuel consumption and thus higher CO2 emissions.
3. Transit distance: The net distance between the source pin code and the destination pin code
4. Loading and Unloading distance: The distance traveled to reach source pin code and distance traveled after destination.
[0037] In an embodiment of the present disclosure, the atleast one output is carbon emission corresponding to the atleast one vehicle.
[0038] OUTPUT-
Total CO2 Emissions (in kg):
•The application provides the user with the total CO2 emissions for the journey, including mobilization and demobilization distances.
•This value is crucial for users to understand the environmental impact of their journey.
[0039] In an embodiment of the present disclosure, the atleast one output is generated by utilizing ULIP data driven technique. The atleast one output is generated by calculating a plurality of metrics including Distance calculation, Emission Factor, Loaded Weight.

[0040] CALCULATION PROCESS-
1. Distance Calculation:
•Journey Distance: The direct distance between the source and destination is calculated using geographical data based on the provided pin codes.
•Total Distance: This is the sum of the Transit distance, Loading Distance and Unloading Distance.
2. Emission Factor:
•An emission factor is determined based on the type of vehicle and its fuel efficiency. This factor represents the amount of CO2 emitted per unit distance per unit weight.
3. CO2 Emission Calculation:
•The total CO2 emissions are calculated using the formula:
•Total CO2 Emissions = (Transit distance + Loading Distance + Unloading Distance) × Loaded Weight × Emission Factor
•This formula accounts for the entire distance traveled by the vehicle and its load, providing an accurate measure of the total CO2 emissions.
[0041] In an embodiment of the present disclosure, the method further includes recommending atleast one action to the user based on the generated output. The atleast one action includes planting a specified number of trees corresponding to the carbon emission. The invention offers carbon auditing through a SaaS-based solution.

[0042] DATA SOURCE FOR EMISSION FACTOR-
Emission factor for fuel
Table 1
Fuel type The amount of carbon dioxide produced by burning 1 litre of fuel (kg)
Diesel 2.33
Petrol 2.33
LPG 2.95
CNG 2.73

• Burning 1 litre of diesel produces 2.33 KG of carbon dioxide.
• Burning 1 litre of petrol produces 2.33 KG of carbon dioxide.
• Burning 1 litre of LPG produces 2.95 KG of carbon dioxide.
• Burning 1 litre of CNG produces 2.73 KG of carbon dioxide.
EXEMPLARY EMBODIMENTS:
[0043] 1. ULIP integration
Accessing API for vehicle information from ULIP system includes:
1. Data Integration between VAHAN and ULIP web service: Identification of operational points where data integration between VAHAN and ULIP web service will be needed.
2. Technical Approach for performing Data Integration.

User will share the vehicle information such as vehicle number, chassis number and engine number based on data send by user ULIP system will call respective VAHAN APIs for accessing information.

Following are the point for accessing vehicle information: -

1. This API will share vehicle data based on information provided by user.
2. ULIP will expose three API for getting data from VAHAN API.
3. For VAHAN/01 ULIP will take vehicle number from user and get data from VAHAN API based on vehicle number.
4. For VAHAN/02 ULIP will take chassis number from user and get data from VAHAN API based on chassis number.
5. For VAHAN/03 ULIP will take engine number from user and get data from VAHAN API based on engine number.

1.1 Data Integration between VAHAN System and ULIP application
User will share information to ULIP system based on data shared ULIP will provide data to user.

1.2 VAHAN Integration masking fields
We are masking some fields in vahan integration. These are the fields:
rc_present_address, rc_permanent_address, rc_owner_name, rc_mobile_no,
rc_f_name.
We are applying default masking for these fields for all the users.

1.3 VAHAN/01
This API will take vehicle number and connect with VAHAN API to get data.

Table 2
S. No. Field Name Field Description Format Require
d/Not –
Required Length
1 Vehicle
number Vehicle Number as available
inVAHAN system ^[a-zA-Z0-
9]{5,11}$ Required Min 5
Max 11

1.3.1 Technical Approach
1. All the data will be shared through rest web services.
2. ULIP system will provide vehicle number for which detail is required.
3. VAHAN API will share details of vehicle which exist in VAHAN system in xml format.
4. Data receive from VAHAN is in XML format. ULIP system convert this data to string format and assign it to key “response”.
5. ULIP system will provide the data in JSON Object format in response body.

Example:
User will share Vehicle Number UP91L0001 to ULIP system, then ULIP system will make a request to VAHAN API.

1.4 VAHAN/02
This API will take vehicle number and connect with VAHAN API to get data.
Table 3
S. No. Field Name Field Description Format Require
d/Not –
Required Length
1 Chasis
number Chassis Number as available
in VAHAN system ^[a-zA-Z0-
9]{1,20}$ Required Min 1
Max 20

1.4.1 Technical Approach
1. All the data will be shared through rest web services.
2. ULIP system will provide chassis number for which detail is required.
3. VAHAN API will share details of vehicle which exist in VAHAN system in xml format.
4. Data receive from VAHAN is in XML format. ULIP system convert this data to string format and assign it to key “response”.
5. ULIP system will provide the data in JSON Object format in response body.

Example:
Chassis Number ME4JF509AH7069705 is shared by ULIP system, then VAHAN integration will make a request to VAHAN API.
[0044] While the foregoing describes various embodiments of the invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof. The scope of the invention is determined by the claims that follow. The invention is not limited to the described embodiments, versions or examples, which are included to enable a person having ordinary skill in the art to make and use the invention when combined with information and knowledge available to the person having ordinary skill in the art.
, Claims:We Claim:
1. A method for diagnosing and managing carbon footprints in road logistics, the method comprising of:
authenticating a user for access using user details by an application program installed on a personal computing unit;
receiving atleast one information from the user using the application program;
transmitting each of the atleast one information to a cloud server using a wireless network, wherein the personal computing unit is configured to wirelessly communicate with the cloud server;
validating and processing each of the atleast one information by the cloud server; and
generating atleast one output of the atleast one information based on the processing.
2. The method as claimed in claim 1, wherein the receiving the atleast one information comprising details of atleast one vehicle including Source and Destination Pin Codes, Loaded Weight of Vehicle, Transit distance, Loading and Unloading distance.
3. The method as claimed in claim 2, wherein the generating the atleast one output comprising carbon emission corresponding to the atleast one vehicle.
4. The method as claimed in claim 1, wherein the generating the atleast one output utilizing ULIP data driven technique.
5. The method as claimed in claim 1, wherein the generating the atleast one output by calculating a plurality of metrics including Distance calculation, Emission Factor, Loaded Weight.
6. The method as claimed in claim 1, wherein the method further including recommending atleast one action to the user based on the generated output, wherein the recommending atleast one action including planting a specified number of trees corresponding to the carbon emission.
7. A system for diagnosing and managing carbon footprints in road logistics, the system comprising of:
a personal computing unit selected from a mobile or a computer;
an application program installed in the personal computing unit;
a cloud server configured to wirelessly trans-receive information with the application program for storage and processing, wherein the cloud server is configured to utilize ULIP data driven technique to process atleast one information from the application program to generate atleast one output; and
a wireless internet network to enable real-time data transmission.
8. The system as claimed in claim 7, wherein the atleast one information comprising details of atleast one vehicle including Source and Destination Pin Codes, Loaded Weight of Vehicle, Transit distance, Loading and Unloading distance, and wherein the atleast one output comprising carbon emission corresponding to the atleast one vehicle.
9. The system as claimed in claim 7, wherein the atleast one output generated by calculating a plurality of metrics including Distance calculation, Emission Factor, Loaded Weight.
10. The system as claimed in claim 7, wherein the cloud server comprises a database to store and retrieve user and vehicular data.