Description:BACKGROUND
Field of Invention
[001] Embodiments of the present invention generally relate to logistics and supply chain optimization and particularly to an Artificial Intelligence (AI) based system to connect transporters with freight needs on return journeys.
Description of Related Art
[002] Logistics and transportation industry plays a vital role in ensuring the timely movement of goods across different regions. Small and medium-sized truck operators often face operational challenges, particularly after completing delivery assignments. A persistent issue arises when vehicles return without carrying any freight, leading to resource underutilization and financial inefficiencies.
[003] Several solutions have emerged to address empty return trips, such as freight exchanges and backhaul optimization platforms. These solutions attempt to connect available truck capacity with freight requirements by leveraging market demand. However, most existing solutions depend heavily on manual processes or partial automation, which limits their overall effectiveness and scalability in dynamic transport environments.
[004] Despite the presence of digital load boards and freight matching platforms, many existing solutions fall short due to limited integration with real-time tracking technologies and automated dispatch systems. This lack of seamless coordination results in delayed matching, increased operational costs, and missed opportunities for both drivers and businesses.
[005] There is thus a need for an improved and advanced Artificial Intelligence (AI) based system to connect transporters with freight needs on return journeys that can administer the aforementioned limitations in a more efficient manner.
SUMMARY
[006] Embodiments in accordance with the present invention provide an Artificial Intelligence (AI) based system to connect transporters with freight needs on return journeys. The system comprising: a request interface adapted to enable a sender to transmit a consignment request. The system further comprising a processing unit established in a cloud server. The processing unit is configured to receive the consignment request from the request interface; analyze the consignment request using an Artificial Intelligence (AI) algorithm; fetch data of ongoing trips of the transporters from a database based on the analyzed consignment request; shortlist relevant transporters intended to have ongoing trips towards the destination location based on the fetched data of the transporters; transmit the consignment request to the shortlisted transporters; enable the shortlisted relevant transporters to accept the consignment request through a transporter interface; and allocate the consignment to the one of the shortlisted relevant transporters based on a set consignment allocation rule, upon acceptance of the consignment request.
[007] Embodiments in accordance with the present invention further provide a method for connecting transporters with freight needs on return journeys. The method comprising steps of receiving a consignment request from a request interface; analyzing the consignment request using an Artificial Intelligence (AI) algorithm; fetching data of ongoing trips of the transporters from a database based on the analyzed consignment request; shortlisting relevant transporters intended to have ongoing trips towards a destination location based on the fetched data of the transporters; transmitting the consignment request to the shortlisted transporters; enabling the shortlisted relevant transporters to accept the consignment request through a transporter interface; and allocating the consignment to the one of the shortlisted relevant transporters based on a set consignment allocation rule, upon acceptance of the consignment request.
[008] Embodiments of the present invention may provide a number of advantages depending on their particular configuration. First, embodiments of the present application may provide an Artificial Intelligence (AI) based system to connect transporters with freight needs on return journeys.
[009] Next, embodiments of the present application may provide a system to connect transporters with freight needs that transporters utilize their return journeys by transporting goods, thereby reducing the occurrence of empty trips and minimizing fuel wastage.
[0010] Next, embodiments of the present application may provide a system to connect transporters with freight needs that uses machine learning algorithms to automatically match drivers with transportation needs, eliminating the delays and inefficiencies associated with manual freight matching.
[0011] Next, embodiments of the present application may provide a system to connect transporters with freight needs that provides tracking, allowing customers and businesses to monitor their shipments in real time, enhancing trust and transparency.
[0012] Next, embodiments of the present application may provide a system to connect transporters with freight needs that reduces brokerage fees and optimizes transportation costs.
[0013] Next, embodiments of the present application may provide a system to connect transporters with freight needs that includes a digital payment gateway that secures transactions between truck drivers and customers, ensuring reliability and reducing risks related to payment defaults.
[0014] These and other advantages will be apparent from the present application of the embodiments described herein.
[0015] The preceding is a simplified summary to provide an understanding of some embodiments of the present invention. This summary is neither an extensive nor exhaustive overview of the present invention and its various embodiments. The summary presents selected concepts of the embodiments of the present invention in a simplified form as an introduction to the more detailed description presented below. As will be appreciated, other embodiments of the present invention are possible utilizing, alone or in combination, one or more of the features set forth above or described in detail below.
BRIEF DESCRIPTION OF THE DRAWINGS
[0016] The above and still further features and advantages of embodiments of the present invention will become apparent upon consideration of the following detailed description of embodiments thereof, especially when taken in conjunction with the accompanying drawings, and wherein:
[0017] FIG. 1 illustrates a schematic block diagram of an Artificial Intelligence (AI) based system to connect transporters with freight needs on return journeys, according to an embodiment of the present invention;
[0018] FIG. 2 illustrates a block diagram of a processing unit, according to an embodiment of the present invention; and
[0019] FIG. 3 depicts a flowchart of a method for connecting transporters with freight needs on return journeys, according to an embodiment of the present invention.
[0020] The headings used herein are for organizational purposes only and are not meant to be used to limit the scope of the description or the claims. As used throughout this application, the word "may" is used in a permissive sense (i.e., meaning having the potential to), rather than the mandatory sense (i.e., meaning must). Similarly, the words “include”, “including”, and “includes” mean including but not limited to. To facilitate understanding, like reference numerals have been used, where possible, to designate like elements common to the figures. Optional portions of the figures may be illustrated using dashed or dotted lines, unless the context of usage indicates otherwise.
DETAILED DESCRIPTION
[0021] The following description includes the preferred best mode of one embodiment of the present invention. It will be clear from this description of the invention that the invention is not limited to these illustrated embodiments but that the invention also includes a variety of modifications and embodiments thereto. Therefore, the present description should be seen as illustrative and not limiting. While the invention is susceptible to various modifications and alternative constructions, it should be understood, that there is no intention to limit the invention to the specific form disclosed, but, on the contrary, the invention is to cover all modifications, alternative constructions, and equivalents falling within the scope of the invention as defined in the claims.
[0022] In any embodiment described herein, the open-ended terms "comprising", "comprises”, and the like (which are synonymous with "including", "having” and "characterized by") may be replaced by the respective partially closed phrases "consisting essentially of", “consists essentially of", and the like or the respective closed phrases "consisting of", "consists of”, the like.
[0023] As used herein, the singular forms “a”, “an”, and “the” designate both the singular and the plural, unless expressly stated to designate the singular only.
[0024] FIG. 1 illustrates a schematic block diagram of an Artificial Intelligence (AI) based system 100 (hereinafter referred to as the system 100) to connect transporters with freight needs on return journeys, according to an embodiment of the present invention. The system 100 may be adapted to provide a framework for enabling a connectivity with a sender to a transporter. In an embodiment of the present invention, the sender may be an entity that may be deemed for sending a logistics from an origination location to a destination location. The logistics may be, but not limited to, a package, a parcel, a courier, documents, perishable goods, pharmaceuticals, flowers, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the logistics, including known, related art, and/or later developed technologies. In an embodiment of the present invention, the transporter may be, but not limited to, an agency, a company, an individual, a driver, and so forth responsible for carrying out the delivery of the logistics.
[0025] According to the embodiments of the present invention, the system 100 may incorporate non-limiting hardware components to enhance the processing speed and efficiency such as the system 100 may comprise a request interface 102, a transporter interface 104, a processing unit 106, a cloud server 108, an Artificial Intelligence (AI) algorithm 110, and a database 112. In an embodiment of the present invention, the hardware components of the system 100 may be integrated with computer-executable instructions for overcoming the challenges and the limitations of the existing systems and/or networks.
[0026] In an embodiment of the present invention, the request interface 102 may be configured to enable a sender to transmit a consignment request. The request interface 102 may be enabled on a first user device (not shown). The consignment request may notify the transporters about an availability of the consignment request that may be fulfilled. The consignment request may comprise details such as, but not limited to, an origination of consignment, a destination of the consignment, a weight of the consignment, a deadline of the consignment, a tare of a hauler, and so forth.
[0027] In an embodiment of the present invention, the transporter interface 104 may be configured to display the consignment request transmitted by the request interface 102. The transporter interface 104 may enable the transporters to select one of the consignment request and may further fulfill the selected consignment request. The transporter interface 104 may be enabled on a second user device (not shown). Moreover, the consignment request may be displayed to the transporters who may be conducting a return journey towards their base and/or home location and may not be hauling any load. The situation may better be understood by an exemplary scenario of a truck driver with the base and/or the home location at point A, delivering a load at point B. Upon delivery of the load at the point B, the truck driver may be left with no option other than returning back to the base and/or the home location at point A without hauling any load. To eliminate empty return journey, the truck driver may accept any one the consignment request, as all the consignment requests displayed to the driver may have pick up location of the point B and a drop-off location of the point A. In some embodiment of the present invention, the drop-off location may be a location prior to point A, such that the truck driver may drop the consignment request at the location prior to point A and may continue their journey towards the base and/or the home location at point A.
[0028] In an embodiment of the present invention, the processing unit 106 may be established in the cloud server 108. The processing unit 106 may be communicatively connected to the first user device, running the request interface 102, and to the second user device, running the transporter interface 104. The processing unit 106 may further be configured to execute computer-executable instructions to generate an output relating to the system 100. According to embodiments of the present invention, the processing unit 106 may be, but not limited to, a Programmable Logic Control (PLC) unit, a microprocessor, a development board, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the processing unit 106 including known, related art, and/or later developed technologies. In an embodiment of the present invention, the processing unit 106 may further be explained in conjunction with FIG. 2.
[0029] In an embodiment of the present invention, the cloud server 108 may be remotely located. In an exemplary embodiment of the present invention, the cloud server 108 may be a public cloud server. In another exemplary embodiment of the present invention, the cloud server 108 may be a private cloud server. In yet another embodiment of the present invention, the cloud server 108 may be a dedicated cloud server. According to embodiments of the present invention, the cloud server 108 may be, but not limited to, a Microsoft Azure cloud server, an Amazon AWS cloud server, a Google Compute Engine (GCE) cloud server, an Amazon Elastic Compute Cloud (EC2) cloud server, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the cloud server 108 including known, related art, and/or later developed technologies.
[0030] FIG. 2 illustrates a block diagram of the processing unit 106, according to an embodiment of the present invention. The processing unit 106 may comprise the computer-executable instructions in form of programming modules such as a data receiving module 200, a data analysis module 202, a data shortlisting module 204, and a consignment module 206.
[0031] In an embodiment of the present invention, the data receiving module 200 may be configured to receive the consignment request from the request interface 102. The data receiving module 200 may be configured to transmit the consignment request to the data analysis module 202.
[0032] The data analysis module 202 may be activated upon receipt of the consignment request from the data receiving module 200. In an embodiment of the present invention, the data analysis module 202 may be configured to analyze the consignment request using an Artificial Intelligence (AI) algorithm 110. The analysis may disclose the details of the consignment request. The Artificial Intelligence (AI) algorithm 110 may be adapted to optimize routes of the transporters based on demand patterns of the consignment request. Further, the data analysis module 202 may be configured to fetch data of ongoing trips of the transporters from the database 112 based on the analyzed consignment request. The data analysis module 202 may be configured to transmit the disclosed details of the consignment request and the fetched data of the ongoing trips of the transporters to the data shortlisting module 204.
[0033] The data shortlisting module 204 may be activated upon receipt of the disclosed details of the consignment request and the fetched data of the ongoing trips of the transporters from the data analysis module 202. In an embodiment of the present invention, the data shortlisting module 204 may be configured to shortlist relevant transporters intended to have ongoing trips towards the destination location based on the fetched data of the transporters.
[0034] In an embodiment of the present invention, the data shortlisting module 204 may be configured to enqueue sequential consignment requests to the shortlisted transporters. The consignment requests may be sequentially enqueued, when the destination of one or more consignment requests may be routed to the trips towards the destination location of the shortlisted transporters. In an embodiment of the present invention, ‘n’ number of consignment requests may be sequentially enqueued, where ‘n’ may be any natural number. However, the origination and the destination of the enqueued consignment requests may be routed the trips towards the destination location of the shortlisted transporters.
[0035] Further, the shortlisted relevant transporters may be transmitted to the consignment module 206.
[0036] The consignment module 206 may be activated upon receipt of the shortlisted relevant transporters from the data shortlisting module 204. In an embodiment of the present invention, the consignment module 206 may be configured to relay the consignment request to the shortlisted transporters. The consignment module 206 may be configured to enable the shortlisted relevant transporters to accept the consignment request through the transporter interface 104. Upon acceptance of the consignment request, the consignment module 206 may be configured to allocate a consignment corresponding to the consignment request to the one of the shortlisted relevant transporters based on a set consignment allocation rule. The set consignment allocation rule may be, but not limited to, a deadline, a fragility of the consignment, a perishability of the consignment, and so forth. Embodiments of the present invention are intended to include or otherwise cover any set consignment allocation rule, including known, related art, and/or later developed technologies.
[0037] In another embodiment of the present invention, the consignment module 206 may further be configured to enable the shortlisted relevant transporters to accept the enqueued consignment request through the transporter interface 104. Upon acceptance of the enqueued consignment request, the consignment module 206 may be configured to enable the shortlisted relevant transporters to continue with delivery of the one or more consignments corresponding to the enqueued consignment requests, at the corresponding destination locations, in the sequential consignment requests.
[0038] Further, upon delivery of the consignment by the relevant transporter(s) at the corresponding destination of the consignment, the consignment module 206 may be configured to conduct a secure payout to the relevant transporter(s).
[0039] In an embodiment of the present invention, the consignment module 206 may be configured to geographically track the relevant transporter(s) carrying the consignment in real-time. Further, the tracked geographical location may be transmitted to the request interface 102.
[0040] FIG. 3 depicts a flowchart of a method 300 for connecting transporters with freight needs on return journeys, according to an embodiment of the present invention.
[0041] At step 302, the system 100 may receive the consignment request from the request interface 102.
[0042] At step 304, the system 100 may analyze the consignment request using the Artificial Intelligence (AI) algorithm 110.
[0043] At step 306, the system 100 may fetch the data of the ongoing trips of the transporters from the database 112 based on the analyzed consignment request.
[0044] At step 308, the system 100 may shortlist the relevant transporters intended to have ongoing trips towards the destination location based on the fetched data of the transporters.
[0045] At step 310, the system 100 may transmit the consignment request to the shortlisted transporters.
[0046] At step 312, the system 100 may enable the shortlisted relevant transporters to accept the consignment request through the transporter interface 104.
[0047] At step 314, the system 100 may allocate the consignment to the one of the shortlisted relevant transporters based on the set consignment allocation rule, upon acceptance of the consignment request.
[0048] At step 316, the system 100 may conduct the secure payout to the shortlisted relevant transporters.
[0049] While the invention has been described in connection with what is presently considered to be the most practical and various embodiments, it is to be understood that the invention is not to be limited to the disclosed embodiments, but on the contrary, is intended to cover various modifications and equivalent arrangements included within the scope of the appended claims.
[0050] This written description uses examples to disclose the invention, including the best mode, and also to enable any person skilled in the art to practice the invention, including making and using any devices or systems and performing any incorporated methods. The patentable scope of the invention is defined in the claims, and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements within substantial differences from the literal languages of the claims. , Claims:CLAIMS
I/We Claim:
1. An Artificial Intelligence (AI) based system (100) to connect transporters with freight needs on return journeys, the system (100) comprising:
a request interface (102) adapted to enable a sender to transmit a consignment request;
a processing unit (106) established in a cloud server (108), characterized in that the processing unit (106) is configured to:
receive the consignment request from the request interface (102);
analyze the consignment request using an Artificial Intelligence (AI) algorithm (110);
fetch data of ongoing trips of the transporters from a database (112) based on the analyzed consignment request;
shortlist relevant transporters intended to have ongoing trips towards the destination location based on the fetched data of the transporters;
transmit the consignment request to the shortlisted transporters;
enable the shortlisted relevant transporters to accept the consignment request through a transporter interface (104); and
allocate the consignment to the one of the shortlisted relevant transporters based on a set consignment allocation rule, upon acceptance of the consignment request.
2. The system (100) as claimed in claim 1, wherein the consignment request comprise details selected from an origination of consignment, a destination of the consignment, a weight of the consignment, a deadline of the consignment, a tare of a hauler, or a combination thereof.
3. The system (100) as claimed in claim 1, wherein the processing unit (106) is configured to conduct a secure payout to the transporter upon delivery of the opted consignment request.
4. The system (100) as claimed in claim 1, wherein the processing unit (106) is configured to display sequential consignment requests to the shortlisted relevant transporters, when the destination of one or more consignment request in the sequential consignment requests is enroute to the origination location of the shortlisted transporters.
5. The system (100) as claimed in claim 1, wherein the processing unit (106) is configured to enable the shortlisted relevant transporters to continue with delivery of the one or more consignment requests, at the corresponding destination locations, in the sequential consignment requests.
6. The system (100) as claimed in claim 1, wherein the Artificial Intelligence (AI) algorithm (110) is adapted to optimize routes of the transporters based on demand patterns of the consignment request.
7. A method (300) for connecting transporters with freight needs on return journeys, the method (300) is characterized by steps of:
receiving a consignment request from a request interface (102);
analyzing the consignment request using an Artificial Intelligence (AI) algorithm (110);
fetching data of ongoing trips of the transporters from a database (112) based on the analyzed consignment request;
shortlisting relevant transporters intended to have ongoing trips towards a destination location based on the fetched data of the transporters;
transmitting the consignment request to the shortlisted transporters;
enabling the shortlisted relevant transporters to accept the consignment request through a transporter interface (104); and
allocating the consignment to the one of the shortlisted relevant transporters based on a set consignment allocation rule, upon acceptance of the consignment request.
8. The method (300) as claimed in claim 7, comprising a step of conducting a secure payout to the transporter upon delivery of the opted consignment request.
9. The method (300) as claimed in claim 7, wherein the Artificial Intelligence (AI) algorithm (110) is adapted to optimize routes of the transporters based on demand patterns of the consignment request.
10. The method (300) as claimed in claim 7, wherein the consignment request comprises details selected from an origination of consignment, a destination of the consignment, a weight of the consignment, a deadline of the consignment, a tare of a hauler, or a combination thereof.
Date: May 02, 2025
Place: Noida

Nainsi Rastogi
Patent Agent (IN/PA-2372)
Agent for the Applicant