AU2021106436A4

AU2021106436A4 - An automatic advertising system for providing personalized and visiting location based promotional offers related to nearby business using machine learning model

Info

Publication number: AU2021106436A4
Application number: AU2021106436A
Authority: AU
Inventors: Sandeep Dubey; Vilas M. Ghodki; S. B. Kishor; B. K. Madhavi; V. Mohan; X. S. Asha Shiny; Ashish Tamrakar; Sitendra Tamrakar
Original assignee: Dubey Sandeep Dr; Ghodki Vilas M Dr; Kishor S B Dr; Madhavi B K Mrs; Mohan V Mr; Shiny X S Asha Dr; Tamrakar Ashish Dr; Tamrakar Sitendra Dr
Current assignee: Dubey Sandeep Dr; Ghodki Vilas M Dr; Kishor S B Dr; Madhavi BK Mrs; Shiny XS Asha Dr; Tamrakar Ashish Dr
Priority date: 2021-08-22
Filing date: 2021-08-22
Publication date: 2021-11-25
Anticipated expiration: 2029-08-22

Abstract

An automatic advertising system for providing personalized and visiting location based promotional offers related to nearby business using machine learning model ABSTRACT The present invention relates to an advertisement system for providing personalized and visiting location based promotional offers related to nearby location using machine learning model. The objective of present invention is to solve the anomalies presented in the prior art techniques and using advanced technique for providing advertisements to the consumers of the nearby business based on the current or visiting location and consumers/customers browsing history using machine learning model. Customers often going for market for buying something from the market need to wander here and there in the market for searching for relevant shops in the market and getting the searched article at a reasonable price. Further, consumers often search for the products or article in their phone before buying in the market. Hence, the proposed invention recommends the products based on the browsing history of the consumer along with providing the promotional offers from the nearby shops of the current location of the consumer using machine learning model. The proposed invention captures the location of the consumers from the GPS sensor of the mobile terminal. The proposed invention first registers the business and maintains a database of the registered business on the server along with location of the registered business. The registered business periodically updates or adds the promotional offers related to the product of their businesses. The proposed invention comprises a central server which is based on machine learning model. The said machine learning model is trained using initial database of the related category and test cases. The central server dynamically or periodically monitors the browsing history of the consumers which are analyzed by the machine learning model at the central server in consultation with the registered businesses. Further, the central servers dynamically monitor the location of the consumers based on the location available through the GPS sensor of the mobile terminal of the consumer. Every aspect of the registered businesses, location and browsing history of the consumer is analyzed by the machine learning model of the said system. The whole process of said advertisement system is automatic and dynamic in nature. Further, the central server based on the browsing history of the consumer, current location of the consumer captured through the mobile terminal, promotional offers of the registered business in the vicinity of current location of the consumer provides or recommends or provides the advertisement to the consumer using the analysis of the machine leaning model. The said machine learning model is adaptive and self-learning in nature and the recommendations or advertisement to the consumers are more relevant and precise with time. Thus, using the advanced technology of machine learning model, the consumers or customers will get the information related to the products along with best promotional offers available on the required product in the current location of the consumer. The proposed advertisement system is fully automatic, dynamic in nature and helps the consumers in providing the required products with best available cost quickly and efficiently. 1 registering the business along with the location and products catalogue sold by that business (201) )1 updating the promotional offers related to registered business in database at central server periodically (202) capturing the browsing history of the mobile device of the user terminal at predetermined intervals (203) capturing the current location of the user terminal using GPS system of the mobile device of the user terminal continuously (204) analyzing, by the machine learning model, at the central server, the captured data related to location and user browsing history of mobile terminal along with promotional offers to related products of nearby location of user terminal (205) determining the location based personalized promotional offers by the machine learning model based on analysis of said data (206) posting location based personalized promotional offers to the user terminal in the form of advertisement related to nearby businesses (207) Figure 2 - Flow-diagram of the method automatic advertising system for providing location based personalized promotional offers of nearby business using machine learning model 2

Description

registering the business along with the location and products catalogue sold by that business (201)

)1

updating the promotional offers related to registered business in database at central server periodically (202)

capturing the browsing history of the mobile device of the user terminal at predetermined intervals (203)

capturing the current location of the user terminal using GPS system of the mobile device of the user terminal continuously (204)

analyzing, by the machine learning model, at the central server, the captured data related to location and user browsing history of mobile terminal along with promotional offers to related products of nearby location of user terminal (205)

determining the location based personalized promotional offers by the machine learning model based on analysis of said data (206)

posting location based personalized promotional offers to the user terminal in the form of advertisement related to nearby businesses (207)

Figure 2 - Flow-diagram of the method automatic advertising system for providing location based personalized promotional offers of nearby business using machine learning model

An automatic advertising system for providing personalized

and visiting location based promotional offers related to

nearby business using machine learning model

FIELD OF INVENTION

[0001] The present invention relates to the technical field of getting promotional offers or advertisement on the mobile terminal based on location. The field of the invention is to provide an automatic advertising system for providing personalized offers related to nearby business.

[0002] More particularly, this present invention relates to the field of automatic advertising system for providing personalized and location based promotional offers related to nearby location businesses or shops using machine learning model.

BACKGROUND & PRIOR ART

[0003] The subject matter discussed in the background section should not be assumed to be prior art merely as a result of its mention in the background section. Similarly, a problem mentioned in the background section or associated with the subject matter of the background section should not be assumed to have been previously recognized in the prior art. The subject matter in the background section merely represents different approaches, which in-and-of-themselves may also be inventions.

[0004] In old days, people often buy essentials or required materials from the shop. People need to go to market and first search for shop related to the things they need to buy. Then people often search for other shops in the local market and ask for the price of articles they need to buy in one or more shops and decide to buy the things or article from the shops which is providing the needed article at reasonable price. This whole process of searching shops relevant to the articles they need to buy and then enquire for the price at one or more shop and deciding the shops from the article is available with best reasonable price and offers is very time consuming and people need to wander here and there in search of shop in the local market. Now a days, there are two options for shopping articles or things needed to the people. The first one is online shopping while the later one is offline shopping from the local market. Beside the option of online shopping, people still prefer to buy or shop articles from the local market because of many reasons. The procedure of buying the articles or things from the local market need to be improved.

[0005] Now, with the advancement in technology, the process or tradition of shopping from local market is also changed. There is a rapid shift in the technology and people wants to use the technology in every field of life. In today's era, people are handy with mobile phone or mobile terminal. Since mobile phone is a common device which is readily available to all the people, they want to use the mobile phone in every aspect of life. The mobile terminal readily available with the people can help the people in finding the shops available with the needed article based on the location of the mobile terminal. Further, people often search for the articles online before they buy it from the market. Thus, there is a need of such a system that can provide the promotional offers in the form of advertisement to the people based on the current location of the mobile terminal and user browsing history automatically. One such kind of technology for providing automation to any field is machine learning model.

[0006] Machine learning is an intelligence demonstrated by machines, unlike the natural intelligence displayed by humans and animals. As the use of machine learning models are increasing in every field for improving the effectiveness and correctness of the work to be done. The machine learning models are based on various models that makes the said system automated and more competent and capable in the said field. Machines can work and act like a human if they have enough information. So, in machine learning models, knowledge engineering plays a vital role. The relation between objects and properties are established to implement knowledge engineering.

[0007] Hence, the use of machine learning makes any technology related system automated and more efficient. Automatic advertising system for providing personalized and location based promotional offers can also be developed using machine learning model. The automatic advertising system can automate the process using various data taken automatically and dynamically and provide promotional offers related to the things they need to buy based on current location of the mobile terminal. Hence, there is a need of such a system that can automate the process and provide more relevant and convenient shops along with offers in the local market. There is various prior art that aim to resolve the said issue which are discussed below:

[0008] US20030046152 Al- A method for the preparation and administration of advertisements for electronic and print publishing, and other advertising media is provided. The present system and method are directed to an interactive network-accessible computer-assisted cooperative preparation of advertisements governed by business rules provided by both a Company advertiser and a media Publisher. Using the system and method of the invention Companies and Publishers are able to cooperate (1) in the joint creation, editing, and arrangement of text, images, audio, animation, and video for inclusion in a publication's advertising media spaces and (2) in the joint administration of the advertisement preparation process. The invention has application in any visual, audio, electronic and print media that can support perusing of ads by potential purchasers. Media which provide such presentations include newspapers, magazines, trade journals, as well as computer-based applications, such as on-line catalogues, yellow pages, want ads, and other network-accessible advertising platforms and other advertising media including movie theatre ads, billboards, and radio ads.

[0009] US20140074591 Al - An end-to-end automated management system facilitates generation of advertisement proposals, and purchase orders, over one or many media outlets and stations. Once an advertisement proposal is purchased and inserted into a traffic management and billing system, near real-time performance feedback about the advertisements can be obtained from media consumers through a media presentation application presenting the advertisement, via a social media service, or the like. The consumer feedback and other performance factors, which can be received concurrently with airing of an advertisement, can be considered in determining whether a particular advertisement or an advertising proposal as a whole, is effective in meeting purchaser requirements. Advertisement copy can be changed according to the proposal parameters, without purchaser intervention, to provide near-real-time responsiveness to consumer feedback.

[0010] US20050086105 Al - A method of optimizing an advertising campaign on a computer network includes the steps of delivering an advertisement to a client computer over a computer network, measuring an efficacy of the advertisement to generate a result, and changing a characteristic of the advertisement based on the result. The characteristic of the advertisement may be an aesthetic feature or a processing trigger, for example. The aesthetic feature may include the presentation vehicle used to display the advertisement, the artwork of the advertisement, and so on. The processing trigger may include rules on when to display the advertisement. The efficacy of the advertisement may be measured by determining its conversion rate or click-through rate, for example.

[0011] US5948061 A - Methods and apparatuses for targeting the delivery of advertisements over a network such as the Internet are disclosed. Statistics are compiled on individual users and networks and the use of the advertisements is tracked to permit targeting of the advertisements of individual users. In response to requests from affiliated sites, an advertising server transmits to people accessing the page of a site an appropriate one of the advertisement based upon profiling of users and networks.

[0012] US5724424 A - A system for the purchasing of goods or information over a computer network is presented. Merchant computers on the network maintain databases of digital advertisements that are accessed by buyer computers. In response to user inquiries, buyer computers retrieve and display digital advertisements from merchant computers. A digital advertisement can further include a program that is interpreted by a buyer's computer. The buyer computers include a means for a user to purchase the product described by a digital advertisement. If a user has not specified a means of payment at the time of purchase, it can be requested after a purchase transaction is initiated. A network payment system performs payment order authorization in a network with untrusted switching, transmission, and host components. Payment orders are backed by accounts in an external financial system network, and the payment system obtains account authorizations from this external network in real-time. Payment orders are signed with authenticators that can be based on any combination of a secret function of the payment order parameters, a single-use transaction identifier, or a specified network address.

[0013] US6401075 B1 - A method for obtaining Internet-type advertisements, modifying those advertisements to fit designated advertising spaces allotted by a plurality of different and unrelated online newspaper websites, and automatically placing those advertisements. Preferred embodiments permit online advertisements to be tracked, audited and/or modified, at any time during an advertising campaign.

[0014] US20040249713 Al - A method for implementing electronic advertising which provides content to users based on observing behavior of certain trendsetters within a member population. The trendsetters are determined by studying historical adoption behaviour of individuals within the member population, or by reference to known indicia.

[0015] US5105184 A - Commercial advertisements of small, medium or full page size to be integrated with different screen types which will result in a change from screen before the advertisements to screen after the advertisements. Also, the sequence of different size screens will be integrated. These advertisements may, may not, or only partially integrated in the first screen second screen, third screen, menu screen, or last screen. In addition, a commercial advertisement of an appropriate size may be integrated with different screens at different locations on the screen. Furthermore, a directory advertisement accessible by menu or other input devices to display various commercial advertisements.

[0016] US6141010 A - A method and apparatus for providing an automatically upgradeable software application that includes targeted advertising based upon demographics and user interaction with the computer. The software application is a graphical user interface that includes a display region used for banner advertising that is downloaded from time to time over a network such as the Internet. The software application is accessible from a server via the Internet and demographic information on the user is acquired by the server and used for determining what banner advertising will be sent to the user. The software application further targets the advertisements in response to normal user interaction, or use, of the computer. Associated with each banner advertisement is a set of data that is used by the software application in determining when a particular banner is to be displayed.

[0017] Hence, there are various prior art that aims to develop a method for providing advertisement system. The objective of all these advertisement systems is to develop more efficient system with the use of the technology. The aim here to present this invention is to develop more advanced system with the current technology to make more efficient and automatic system. Further, none of the cited prior art provides advertisements based on the location of the mobile terminals for shops available in the local market. All the above cited prior art provide advertisement system only and does not provide promotional offers for local market or local shops based on the current location of the user and user browsing history.

[0018] Besides this, there are various prior arts in the state of the art that claims to resolve the problem of providing advertisement system for providing personalized offers but the approach adopted for solving the same need to be further refined. Hence, there is a need to provide an automatic advertising system for location based personalized offers to the users in the local market. The aim of the present invention is to use machine learning model that makes less intervention and involvement of the human resources. The use of machine learning model provides more advanced system for providing location based personalized promotional offers to the users based on the location of the user available in the local market and automated advertising system based on browsing history of the user.

[0019] Groupings of alternative elements or embodiments of the invention disclosed herein are not to be construed as limitations. Each group member can be referred to and claimed individually or in any combination with other members of the group or other elements found herein. One or more members of a group can be included in, or deleted from, a group for reasons of convenience and/or patentability. When any such inclusion or deletion occurs,

Claims

the specification is herein deemed to contain the group as modified thus fulfilling the written description of all Markus groups used in the appended claims. [0020] As used in the description herein and throughout the claims that follow, the meaning of "a," "an," and "the" includes plural reference unless the context clearly dictate otherwise. Also, as used in the description herein, the meaning of "in" includes "in" and "on" unless the context clearly dictates otherwise. [0021] The recitation of ranges of values herein is merely intended to serve as a shorthand method of referring individually to each separate value falling within the range. Unless otherwise indicated herein, each individual value is incorporated into the specification as if it were individually recited herein. All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. [0022] The use of any and all examples, or exemplary language (e.g. "such as") provided with respect to certain embodiments herein is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention otherwise claimed. No language in the specification should be construed as indicating any non-claimed element essential to the practice of the invention. [0023] The above information disclosed in this Background section is only for enhancement of understanding of the background of the invention and therefore it may contain information that does not form the prior art that is already known in this country to a person of ordinary skill in the art. SUMMARY OF THE INVENTION [0024] Before the present systems and methods, are described, it is to be understood that this application is not limited to the particular systems, and methodologies described, as there can be multiple possible embodiments which are not expressly illustrated in the present disclosure. It is also to be understood that the terminology used in the description is for the purpose of describing the particular versions or embodiments only and is not intended to limit the scope of the present application. This summary is provided to introduce concepts related to automatic advertising system for location based personalized promotional offers in the local businesses using machine learning model and the concepts are further described below in the detailed description. This summary is not intended to identify essential features of the claimed subject matter nor is it intended for use in determining or limiting the scope of the claimed subject matter. [0025] The present invention mainly solves the technical problems existing in the prior art. In response to these problems, the present invention discloses an automatic advertising system for providing location based personalized promotional offers in nearby market using machine learning model. The given solution provides the complete and automatic advertising system that uses user browsing history and location of the mobile terminal of the user and promotional offers from the local market based on the location of the shop and analyzes the data using machine learning model for providing more relevant and attractive offers to the system and helps them in finding the right shops and reasonable price in the local market. The aim of the proposed invention is to develop an advertising system that is completely automatic and can provide promotional offers in vicinity of the user terminal using latest technology like machine learning model. Thus, using the advanced technology of machine learning model, the consumers or customers will get the information related to the products along with best promotional offers available on the required product in the current location of the consumer. The proposed advertisement system is fully automatic, dynamic in nature and helps the consumers in providing the required products with best available cost quickly and efficiently. [0026] The proposed invention comprises a central server storing the data related to the customers/consumers along with the location of the mobile terminal of the user. The said data is stored in the database storing data related to the customers/consumers like name, contact number, email-id, date of birth and other data related to the customers. The said data also include the database related to the business in the local market along with the promotional offers active in said business and location. The server involved in the present invention is machine learning enabled server which is self-learning machine and adapted to provide personalized offers or promotional offers to the user terminal based on the location and browsing history of the user terminal. The proposed invention comprises the central server which is trained using initial database relevant to the advertising system according to the present invention and test cases. The trained central server is used to analyze the data collected or captured. The central server is competent and self learned enough to provide the more relevant and useful promotional offers by time and very useful for the users of the mobile terminal. The proposed invention uses the GPS system to fetch the location of the mobile terminal dynamically. [0027] The proposed invention captures the location of the consumers from the GPS sensor of the mobile terminal. The proposed invention first registers the business and maintains a database of the registered business on the server along with location of the registered business. The registered business periodically updates or adds the promotional offers related to the product of their businesses. The proposed invention comprises a central server which is based on machine learning model. The said machine learning model is trained using initial database of the related category and test cases. The central server dynamically or periodically monitors the browsing history of the consumers which are analyzed by the machine learning model at the central server in consultation with the registered businesses. Further, the central servers dynamically monitor the location of the consumers based on the location available through the GPS sensor of the mobile terminal of the consumer. Every aspect of the registered businesses, location and browsing history of the consumer is analyzed by the machine learning model of the said system. The whole process of said advertisement system is automatic and dynamic in nature. Further, the central server based on the browsing history of the consumer, current location of the consumer captured through the mobile terminal, promotional offers of the registered business in the vicinity of current location of the consumer provides or recommends or provides the advertisement to the consumer using the analysis of the machine leaning model. The said machine learning model is adaptive and self-learning in nature and the recommendations or advertisement to the consumers are more relevant and precise with time. [0028] An aspect of the present disclosure relates to a computer implemented method of automatic advertising system for providing location based personalized promotional offers of nearby business using machine learning model, the method comprises: registering the business along with the location and products sold; updating the promotional offers related to registered business in database at central server periodically; capturing the browsing history of the mobile device of the user terminal at predetermined intervals; capturing the current location of the user terminal using GPS system of the mobile device of the user terminal continuously; analyzing, by the machine learning model, at the central server, the captured data related to location and user browsing history of mobile terminal along with promotional offers to related products of nearby location of user terminal; determining the location based personalized promotional offers by the machine learning model based on analysis of said data; posting location based personalized promotional offers to the user terminal in the form of advertisement related to nearby businesses. [0029] Another aspect of the present disclosure relates to a computer implemented system of automatic advertising system for providing location based personalized promotional offers of nearby business using machine learning model, the method comprises: registering the business along with the location and products sold; updating the promotional offers related to registered business in database at central server periodically; capturing the browsing history of the mobile device of the user terminal at predetermined intervals; capturing the current location of the user terminal using GPS system of the mobile device of the user terminal continuously; analyzing, by the machine learning model, at the central server, the captured data related to location and user browsing history of mobile terminal along with promotional offers to related products of nearby location of user terminal; determining the location based personalized promotional offers by the machine learning model based on analysis of said data; posting location based personalized promotional offers to the user terminal in the form of advertisement related to nearby businesses. [0030] This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter. OBJECTIVE OF THE INVENTION [0031] A primary object of the present invention is to provide a method of automatic advertising system for providing location based personalized promotional offers of nearby business using machine learning model. [0032] Yet another object of the present invention is to provide a system of automatic advertising system for providing location based personalized promotional offers of nearby business using machine learning model. The said system provides complete and automatic advertisement system based on location and browsing history of the user terminal. BRIEF DESCRIPTION OF DRAWINGS [0033] To clarify various aspects of some example embodiments of the present invention, a more particular description of the invention will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings. It is appreciated that these drawings depict only illustrated embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail through the use of the accompanying drawings. [0034] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the embodiments belong. Although methods and materials similar or equivalent to those described herein can be used in the practice or testing, suitable methods and materials are described below. In case of conflict, the patent specification, including definitions, will control. In addition, the materials, methods, and examples are illustrative only and not intended to be limiting. [0035] In order that the advantages of the present invention will be easily understood, a detail description of the invention is discussed below in conjunction with the appended drawings, which, however, should not be considered to limit the scope of the invention to the accompanying drawings, in which: [0036] Figure 1 shows block-diagram of the automatic advertising system for providing location based personalized promotional offers incorporating all the embodiment of the system of the present invention. [0037] Figure 2 shows a flow-diagram of computer implemented method of automatic advertising system for providing location based personalized promotional offers of nearby business using machine learning model in accordance with the present invention. DETAIL DESCRIPTION [0038] The present invention relates to a computer implemented method of automatic advertising system for providing location based personalized promotional offers of nearby business using machine learning model for increasing the ease of users of mobile terminal for finding the needed products at reasonable price in local market. [0039] Although the present disclosure has been described with the purpose of automatic advertising system for providing location based personalized promotional offers of nearby business using machine learning model, it should be appreciated that the same has been done merely to illustrate the invention in an exemplary manner and to highlight any other purpose or function for which explained structures or configurations could be used and is covered within the scope of the present disclosure. [0040] Some embodiments of this disclosure, illustrating all its features, will now be discussed in detail. The words and other forms thereof are intended to be open ended in that an item or items following any one of these words is not meant to be an exhaustive listing of such item or items, or meant to be limited to only the listed item or items. It must also be noted that as used herein and in the appended claims, the singular forms "a," "an," and "the" include plural references unless the context clearly dictates otherwise. Although any systems and methods similar or equivalent to those described herein can be used in the practice or testing of embodiments of the present disclosure, the exemplary systems and methods are now described. The disclosed embodiments are merely exemplary of the disclosure, which may be embodied in various forms. [0041] Various modifications to the embodiment will be readily apparent to those skilled in the art and the generic principles herein may be applied to other embodiments. However, one of ordinary skill in the art will readily recognize that the present disclosure is not intended to be limited to the embodiments illustrated, but is to be accorded the widest scope consistent with the principles and features described herein. [0042] Figure 1 show a block-diagram of automatic advertising system for providing location based personalized promotional offers of nearby business using machine learning model as per the embodiments of the present invention. According to the present invention, the said system comprises a central server (103) having the computation facility wherein the central server is equipped with machine learning model. The server machine (103) is backed with the database (102) comprising of data related to the customer's profile, user purchase history and registered business promotional offers along with location. The communication network (101) is responsible for transmitting and receiving various data across various embodiments of the present invention. The communication network involved in the present invention may be but not limited to Wide area Network (WAN), local area Network (LAN), WiFi, Bluetooth or the combination thereof. Further, there are n number of customer or consumer associated with the business of an organization. The proposed invention uses the GPS sensor of the mobile terminal to determine the location of the user device. The said system also captures the user browsing history of the mobile terminal at predetermined intervals. The machine learning model is trained using the database and test cases related to the proposed invention. The promotional offers related to the proposed invention may be accessed through the user interface on the mobile terminal browser or on the mobile application. [0043] Figure 2 shows the flow-diagram of computer implemented method of automatic advertising system for providing location based personalized promotional offers of nearby business using machine learning model in accordance with the proposed invention. The computer implemented method first registering the business along with the location and products sold at step 201; updating the promotional offers related to registered business in database at central server periodically at step 202; capturing the browsing history of the mobile device of the user terminal at predetermined intervals at step 203; capturing the current location of the user terminal using GPS system of the mobile device of the user terminal continuously at step 204; analyzing, by the machine learning model, at the central server, the captured data related to location and user browsing history of mobile terminal along with promotional offers to related products of nearby location of user terminal at step 205; determining the location based personalized promotional offers by the machine learning model based on analysis of said data at step 206; posting location based personalized promotional offers to the user terminal in the form of advertisement related to nearby businesses at step 207. [0044] The figures and the foregoing description give examples of embodiments. Those skilled in the art will appreciate that one or more of the described elements may well be combined into a single functional element. Alternatively, certain elements may be split into multiple functional elements. Elements from one embodiment may be added to another embodiment. For example, order of processes described herein may be changed and are not limited to the manner described herein. Moreover, the actions of any flow diagram need not be implemented in the order shown; nor do all of the acts need to be necessarily performed. Also, those acts that are not dependent on other acts may be performed in parallel with the other acts. The scope of embodiments is by no means limited by these specific examples. [0045] Although implementations for invention have been described in a language specific to structural features and/or methods, it is to be understood that the appended claims are not necessarily limited to the specific features or methods described. Rather, the specific features and methods are disclosed as examples of implementations for the invention. CLAIMS We claim:

1. A computer implemented method of automatic advertising system for providing location based personalized promotional offers of nearby business using machine learning model, the computer implemented method comprising steps of: registering the business along with the location and products catalogue sold by that business (201); updating the promotional offers related to registered business in database at central server periodically (202); capturing the browsing history of the mobile device of the user terminal at predetermined intervals (203); capturing the current location of the user terminal using GPS system of the mobile device of the user terminal continuously (204); analyzing, by the machine learning model, at the central server, the captured data related to location and user browsing history of mobile terminal along with promotional offers to related products of nearby location of user terminal (205); determining the location based personalized promotional offers by the machine learning model based on analysis of said data (206); posting location based personalized promotional offers to the user terminal in the form of advertisement related to nearby businesses (207).

2. The computer implemented method as claimed in claim 1, wherein the location of the user and user browsing history is captured from the GPS sensor and cookies of the internet browser and shopping apps.

3. The computer implemented method as claimed in claim 1, wherein the communication network may be based on the WiFi, Bluetooth, Local Area Network, Wide Area Network or the combination thereof.

4. The computer implemented method as claimed in claim 1, wherein database comprises customer profile, user purchase history and offers and products related to the registered business along with location.

5. A system of automatic advertising system for providing location based personalized promotional offers of nearby business using machine learning model, the system comprising: a communication network (101) to transmit/receive data from other embodiments of the system; database (102) to store data related to customer profile, user purchase history and offers and products related to the registered business along with location; GPS sensor (104) of the mobile terminal of the user for obtaining location of the user; central server (103) for performing function using machine learning model for performing the steps of: registering the business along with the location and products catalogue sold by that business (201); updating the promotional offers related to registered business in database at central server periodically (202); capturing the browsing history of the mobile device of the user terminal at predetermined intervals (203); capturing the current location of the user terminal using GPS system of the mobile device of the user terminal continuously (204); analyzing, by the machine learning model, at the central server, the captured data related to location and user browsing history of mobile terminal along with promotional offers to related products of nearby location of user terminal (205); determining the location based personalized promotional offers by the machine learning model based on analysis of said data (206); posting location based personalized promotional offers to the user terminal in the form of advertisement related to nearby businesses (207).

GPS 22 Aug 2021

sensor

Database (102)

Customer 1 2021106436

Customer 2

server (103) Communication network (101)

Customer n

Machine learning model

Figure 1: Block diagram of automatic advertising system for providing location based personalized promotional offers

updating the promotional offers related to registered business in database at central server periodically (202) 2021106436

Figure 2 – Flow-diagram of the method automatic advertising system for providing location based personalized promotional offers of nearby business using machine learning model