Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
1. This is a first non-final Office Action on the merits for application 19199319. Claims 1-22 are pending examination.
Information Disclosure Statement
2. The information disclosure statement (IDS) submitted on 11/07/2021 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Double Patenting
3. The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the claims at issue are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on a nonstatutory double patenting ground provided the reference application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO internet Web site contains terminal disclaimer forms which may be used. Please visit http://www.uspto.gov/forms/. The filing date of the application will determine what form should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to http://www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claim(s) 1-22 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claim(s) 1-24 of US Application No. 19248131 and claim(s) 1-22 of US Application No. 19199106. Although the claims at issue are not identical, they are not patentably distinct from each other because the claims are directed to the same subject matter, perform the same method steps and a person of ordinary skill in the art would not be free to practice one of the claimed inventions without infringing upon the other inventions.
Application number: 19199319
1. A method for filtering data transmitted to a user device of a user, comprising: subscribing, by a server having one or more processors, one or more memories, a transmitter and a receiver, users fromamong businesses and consumers, to a proximity-based mobile advertising service, to form a subscriber database that includes location information of subscribing businesses; storing, by the one or more memories, an advertisements database that includes one or more advertisements for each respective subscribing business from the subscriber database; receiving, by the receiver, location information and trajectory information of the user; representing, by the one or more processors based on the location information of a subscribing business, a physical region of interest proximate to the subscribing business by a geometric shape; filtering, by the one or more processors, the advertisements database, to select for display to the user, at least one advertisement corresponding to the subscribing business, responsive to a user trajectory being within at least a portion the geometric shape; and transmitting, by the transmitter to the user device, the at least one advertisement.
Application number: 192481311. A method, comprising: subscribing, by a server having one or more processors, one or more memories, a transmitter, and a receiver, users to a location-based mobile advertising service; receiving, by the receiver of the server from a location determining device of a mobile device of a subscriber, location information of the mobile device of the subscriber; monitoring, by the one or more processors of the server, the location information of the mobile device of the subscriber with respect to a physical region of interest proximate to a business; confirming, by the one or more processors of the server responsive to the location information indicating the mobile device of the subscriber is within the physical region of interest, an actual presence of the subscriber within the physical region of interest based on user identifying information captured from the subscriber by a capture device located within the physical region of interest and mobile device identifying information captured from the mobile device of the subscriber in the physical region of interest; and transmitting, by the transmitter of the server to the mobile device of the subscriber responsive to the actual presence of the subscriber being confirmed within the physical region of interest, digital content corresponding to the business.
Application number: 191991061. A method for filtering data transmitted to a user device of a user, comprising: subscribing, by a server having one or more processors, one or more memories, a transmitter and a receiver, users to one or more services relating to friendship, dating, and business, to form a database of subscribers that includes one or more pictures of, and a biography for, each of the subscribers; receiving, by the receiver of the server, user inputs selecting a geometric shape and a size of the geometric shape, for each of the one or more services to which the user has subscribed; receiving, by the receiver of the server, location information and trajectory information of the user; representing, by the one or more processors of the server, a physical region of interest proximate to the user by the geometric shape, wherein parameters of the geometric shape are based on one or more of the user inputs, the location information, and the trajectory information; filtering, by the one or more processors of the server, the database of subscribers, to select for display to the user, the one or more pictures and the biography of one or more other subscribers than the user, responsive to the one or more other subscribers being within a trajectory of at least a portion the geometric shape and having one or more services subscribed in common with the user; and transmitting, by the transmitter of the server to the user device, the one or more pictures and the biography of the one or more other subscribers.
19. A system for filtering data transmitted to a user device of a subscribing consumer, comprising: a receiver configured to receive location information and trajectory information of the subscribing consumer; one or more memories, individually or in combination, having instructions and an advertisements database that includes one or more advertisements and location information for each respective business from a subscriber database; one or more processors each coupled to at least one of the one or more memories and configurable/operable to execute the instructions to:subscribe users fromamong businesses and consumers to a proximity-based mobile advertising service to form a subscriber database; represent based on the location information of a subscribing business, a physical region of interest proximate to the subscribing business by a geometric shape; and filter the advertisements database, to select for display to a subscribing consumer, at least one advertisement corresponding to the subscribing business, responsive to a user trajectory being within at least a portion the geometric shape; and a transmitter configured to transmit the at least one advertisement to the user device of the subscribing consumer.
13. A system, comprising: a receiver configured to receive location information of a subscriber from a location determining device of a mobile device of the subscriber; one or more memories, individually or in combination, having instructions; one or more processors each coupled to at least one of the one or more memories and configurable/operable to execute the instructions to:subscribe users to a location-based mobile advertising service;monitor the location information of the mobile device of the subscriber with respect to a physical region of interest proximate to a business; andconfirm, responsive to the location information indicating the mobile device of the subscriber is within the physical region of interest, an actual presence of the subscriber within the physical region of interest based on user identifying information captured from the subscriber by a capture device located within the physical region of interest and mobile device identifying information captured from the mobile device of the subscriber in the physical region of interest; and a transmitter configured to transmit, responsive to the actual presence of the subscriber being confirmed within the physical region of interest, digital content corresponding to the business.
12. A system for filtering data transmitted to a user device of a user, comprising: a receiver configured to receive location information and trajectory information of a user and user inputs selecting a geometric shape and a size of the geometric shape, for each of one or more services relating to friendship, dating, and business subscribed to by the user; one or more memories, individually or in combination, having instructions; one or more processors each coupled to at least one of the one or more memories and configurable/operable to execute the instructions to:subscribe users to the one or more services to form a database of subscribers that includes one or more pictures of, and a biography for, each of the subscribers;represent a physical region of interest proximate to the user by the geometric shape, wherein parameters of the geometric shape are based onone ormore of the user inputs, the location information, and the trajectory information; andfilter the database of subscribers, to select for display to the user, the one or more pictures and the biography of one or more other subscribers than the user, responsive to the one or more other subscribers being within a trajectory of at least a portion the geometric shape and having one or more service subscribed in common with the user; and a transmitter configured to transmit the one or more pictures and the biography of the one or more other subscribers to the user device.
20. A method for filtering data transmitted to a user device of a user, comprising: subscribing, by a server having one or more processors, one or more memories, a transmitter and a receiver, users fromamong businesses and consumers, to a proximity-based event and content access service to form a subscriber database of subscriber information; storing, by the one or more memories, exclusive digital content provided by the businesses in an exclusive digital content database; receiving, by the receiver, location information and trajectory information of the user; representing, by the one or more processors based on the location information and the trajectory information of the user, a physical region of interest proximate to the user by a geometric shape; filtering, by the one or more processors, the exclusive digital content database to identify one or more items of exclusive digital content provided by one or more of the businesses that are within a trajectory of at least a portion of the geometric shape; and transmitting, by the transmitter to the user device, the one or more items of exclusive digital content.
13. A method for filtering data transmitted to a user device of a user, comprising: subscribing, by a server having one or more processors, one or more memories, a transmitter and a receiver, users to (i) one or more roles from a set of roles including a buyer, a seller, and a trader, and (ii) one or more commodities corresponding to the one or more roles, to form a database of subscribers;storing, by the one or more memories of the server, a database of advertisements for buying, selling, and trading commodities, each of the advertisements associated with a respective subscriber from the database of subscribers;receiving, from a location determining device by the receiver of the server, location information and trajectory information of the user;representing, by the one or more processors of the server, a physical region of interest proximate to the user by a geometric shape, wherein dynamic parameters of the geometric shape including a location, a size, and a position of the geometric shape relative to a location of the user are based on the location information and the trajectory information;filtering, by the one or more processors of the server, the database of advertisements, to select for display to the user, one or more advertisements from the database of advertisements responsive to the one or more advertisements corresponding to one or more other subscribers than the user that are within a trajectory of at least a portion the geometric shape and have at least one role and at least one commodity complimentary to the one or more roles and the one or more commodities subscribed to by the user; andtransmitting, by the transmitter of the server to the user device, the one or more advertisements.
22. A system for filtering data trans mitted to a user device of a user, comprising: a receiver configured to receive location information and trajectory information of the user; one or more memories, individually or in combination, having instructions and an exclusive digital content database including exclusive digital content provided by businesses; one or more processors each coupled to at least one of the one or more memories and configurable/operable to execute the instructions to:subscribe users from among the businesses and consumers, to a proximity based event and content access service to form a subscriber database of subscriber information;store exclusive digital content provided by the businesses in an exclusive digital content database;represent, based on the location information and the trajectory information of the user, a physical region of interest proximate to the user by a geometric shape; and filter the exclusive digital content database to identify one or more items of exclusive digital content provided by one or more of the businesses that are within a trajectory of at least a portion of the geometric shape; and a transmitter configured to transmit the one or more items of exclusive digital content.
18. A system for filtering data transmitted to a user device of a user, comprising: a receiver configured to receive location information and trajectory information of a user from a location determining device; one or more memories, individually or in combination, having instructions; and configured to store a database of advertisements for buying, selling, and trading commodities, each of the advertisements associated with a respective subscriber from a database of subscribers;one or more processors each coupled to at least one of the one or more memonries and configurable/operable to execute the instructions to: subscribe users to (i) one or more roles from a set of roles including a buyer, a seller, and a trader, and (ii) one or more commodities corresponding to the one or more roles, to form the database of subscribers; represent a physical region of interest proximate to the user by a geometric shape, wherein dynamic parameters of the geometric shape including a location, a size, and a position of the geometric shape relative to a location of the user are based on the location information and the trajectory information; and filter the database of advertisements, to select for display to the user, one or more advertisements from the database of advertisements responsive to the one or more advertisements corresponding to one or more other subscribers than the user that are within a trajectory of at least a portion the geometric shape and have at least onerole and at least one commodity complimentary to the one or more roles and the one or more commodities subscribed to by the user; and a transmitter configured to transmit the one or more advertisements to the user device.
It would have been obvious to one having ordinary skill in the art to make the changes above in order to cover slightly broader limitations. Furthermore, the claimed elements perform the same function as before.
Claim Rejections - 35 USC § 101
4. 35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claim(s) 1, and 20 is/are drawn to method (i.e., a process), claim(s) 19, and 22 is/are drawn to a system (i.e., a machine/manufacture). As such, claims 1, 19, 20, and 22 is/are drawn to one of the statutory categories of invention.
Claims 1-22 are directed to providing advertisements based on location information of the business and a physical region of interest proximate to the business by geometric shape. Specifically, claim(s) 1, 19, 20, and 22 recite(s) subscribing, users from among businesses and consumers, to a proximity-based advertising service, to form a subscriber that includes location information of subscribing businesses; storing, an advertisements that includes one or more advertisements for each respective subscribing business from the subscriber; receiving, location information and trajectory information of the user; representing, based on the location information of a subscribing business, a physical region of interest proximate to the subscribing business by a geometric shape; filtering, the advertisements, to select for display to the user, at least one advertisement corresponding to the subscribing business, responsive to a user trajectory being within at least a portion the geometric shape; and transmitting, the at least one advertisement, which is grouped within the Methods Of Organizing Human Activity and is similar to the concept of (commercial or legal interactions including agreements in the form of contracts, legal obligations, advertising, marketing or sales activities or behaviors business relations) grouping of abstract ideas in prong one of step 2A of the Alice/Mayo test (See 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 52, 54 (January 7, 2019)). Accordingly, the claims recite an abstract idea (See pages 7, 10, Alice Corporation Pty. Ltd. v. CLS Bank International, et al., US Supreme Court, No. 13-298, June 19, 2014; 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 53-54 (January 7, 2019)).
The Claim limitations are listed under Methods Of Organizing Human Activity, and grouped as following:
subscribing, users from among businesses and consumers, to a proximity-based advertising service, to form a subscriber that includes location information of subscribing businesses; which is similar to the concept of (advertising, marketing or sales activities or behaviors business relations),
storing, an advertisements that includes one or more advertisements for each respective subscribing business from the subscriber; which is similar to the concept of (advertising, marketing or sales activities or behaviors business relations),
receiving, location information and trajectory information of the user; representing, based on the location information of a subscribing business, a physical region of interest proximate to the subscribing business by a geometric shape; which is similar to the concept of (advertising, marketing or sales activities or behaviors business relations),
filtering, the advertisements, to select for display to the user, at least one advertisement corresponding to the subscribing business, responsive to a user trajectory being within at least a portion the geometric shape; and which is similar to the concept of (advertising, marketing or sales activities or behaviors business relations),
transmitting, the at least one advertisement; which is similar to the concept of (advertising, marketing or sales activities or behaviors business relations).
This judicial exception is not integrated into a practical application because, when analyzed under prong two of step 2A of the Alice/Mayo test (See 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 54-55 (January 7, 2019)), the additional element(s) of the claim(s) such as user device, server, processors, memories, transmitter, receiver, database, system merely use(s) a computer as a tool to perform an abstract idea and/or generally link(s) the use of a judicial exception to a particular technological environment. Specifically, the user device, server, processors, memories, transmitter, receiver, database, system perform(s) the steps or functions of subscribing, users from among businesses and consumers, to a proximity-based advertising service, to form a subscriber that includes location information of subscribing businesses; storing, an advertisements that includes one or more advertisements for each respective subscribing business from the subscriber; receiving, location information and trajectory information of the user; representing, based on the location information of a subscribing business, a physical region of interest proximate to the subscribing business by a geometric shape; filtering, the advertisements, to select for display to the user, at least one advertisement corresponding to the subscribing business, responsive to a user trajectory being within at least a portion the geometric shape; and transmitting, the at least one advertisement. The use of a processor/computer as a tool to implement the abstract idea and/or generally linking the use of the abstract idea to a particular technological environment does not integrate the abstract idea into a practical application because it requires no more than a computer performing functions that correspond to acts required to carry out the abstract idea. The additional elements do not involve improvements to the functioning of a computer, or to any other technology or technical field (MPEP 2106.05(a)), the claims do not apply or use the abstract idea to effect a particular treatment or prophylaxis for a disease or medical condition (Vanda Memo), the claims do not apply the abstract idea with, or by use of, a particular machine (MPEP 2106.05(b)), the claims do not effect a transformation or reduction of a particular article to a different state or thing (MPEP 2106.05(c)), and the claims do not apply or use the abstract idea in some other meaningful way beyond generally linking the use of the abstract idea to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception (MPEP 2106.05(e) and Vanda Memo). Therefore, the claims do not, for example, purport to improve the functioning of a computer. Nor do they effect an improvement in any other technology or technical field. Accordingly, the additional elements do not impose any meaningful limits on practicing the abstract idea, and the claims are directed to an abstract idea.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when analyzed under step 2B of the Alice/Mayo test (See 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 52, 56 (January 7, 2019)), the additional element(s) of using a user device, server, processors, memories, transmitter, receiver, database, system to perform the steps amounts to no more than using a computer or processor to automate and/or implement the abstract idea of providing advertisements based on location information of the business and a physical region of interest proximate to the business by geometric shape. As discussed above, taking the claim elements separately, the user device, server, processors, memories, transmitter, receiver, database, system perform(s) the steps or functions of subscribing, users from among businesses and consumers, to a proximity-based advertising service, to form a subscriber that includes location information of subscribing businesses; storing, an advertisements that includes one or more advertisements for each respective subscribing business from the subscriber; receiving, location information and trajectory information of the user; representing, based on the location information of a subscribing business, a physical region of interest proximate to the subscribing business by a geometric shape; filtering, the advertisements, to select for display to the user, at least one advertisement corresponding to the subscribing business, responsive to a user trajectory being within at least a portion the geometric shape; and transmitting, the at least one advertisement. These functions correspond to the actions required to perform the abstract idea. Viewed as a whole, the combination of elements recited in the claims merely recite the concept of providing advertisements based on location information of the business and a physical region of interest proximate to the business by geometric shape. Therefore, the use of these additional elements does no more than employ the computer as a tool to automate and/or implement the abstract idea. The use of a computer or processor to merely automate and/or implement the abstract idea cannot provide significantly more than the abstract idea itself (MPEP 2106.05(I)(A)(f) & (h)). Therefore, the claim is not patent eligible.
As for dependent claims 2-18, and 21 further describe the abstract idea of providing advertisements based on location information of the business and a physical region of interest proximate to the business by geometric shape. Claim(s) 2-18, and 21 does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when analyzed under step 2B of the Alice/Mayo test (See 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 52, 56 (January 7, 2019)), the additional element(s) of using a user device, server, processors, memories, transmitter, receiver, database, system to perform the steps amounts to no more than using a computer or processor to automate and/or implement the abstract idea of providing advertisements based on location information of the business and a physical region of interest proximate to the business by geometric shape. As discussed above, taking the claim elements separately, the user device, server, processors, memories, transmitter, receiver, database, system perform(s) the steps or functions of dynamically adjusting a size of the geometric shape based on one or more sizing criteria; dynamically determining an extended size of the geometric shape based on sizing criteria; dynamically determining a time duration for the extended size of the geometric shape based on the sizing criteria; determining the sizing criteria based on heatmap data for a region proximate to the subscribing business; determining the sizing criteria based on a subscription level that assigns extended sizes to the geometric shape; determining an extension of a size of the geometric shape using a hierarchical system that assigns different size extensions of the geometric shape to different size extension tiers; selecting an applicable size extension tier from among the different size extension tiers responsive to heatmap data derived from a heatmap image; selecting an applicable size extension tier from among the different size extension tiers responsive to subscription data; determining a time duration of an extension of a size of the geometric shape using a hierarchical that assigns different time duration extensions to different time duration tiers; selecting an applicable time duration tier from among the different time duration tiers responsive to heatmap data derived from a heatmap image; selecting an applicable time duration tier from among the different time duration tiers responsive to subscription data; generating different representations of the physical region of interest proximate to the user that respectively correspond to different subscribing businesses; generating geometric shapes corresponding to at least two of the different representations to have different sizes; generating geometric shapes corresponding to at least two of the different representations to have different durations during which sizes of geometric shapes are extended; dynamically creating the different representations responsive to the user moving proximate to the different subscribing businesses; providing marketing and traffic information to the businesses using a hierarchical that assigns different access levels to the marketing and traffic information to different tiers; wherein the marketing and traffic information comprises foot traffic information corresponding to a respective one or more areas proximate to the businesses; accessing the subscriber information in the subscriber database to determine user preferences with respect to types of digital content to be received by the user, wherein filtering the exclusive digital content comprises filtering the exclusive digital content provided by one or more of the businesses that are within the trajectory of at least the portion of the geometric shape based on the user preferences with respect to types of digital content to be received by the user. These functions correspond to the actions required to perform the abstract idea. Viewed as a whole, the combination of elements recited in the claims merely recite the concept of providing advertisements based on location information of the business and a physical region of interest proximate to the business by geometric shape. Therefore, the use of these additional elements does no more than employ the computer as a tool to automate and/or implement the abstract idea. The use of a computer or processor to merely automate and/or implement the abstract idea cannot provide significantly more than the abstract idea itself (MPEP 2106.05(I)(A)(f) & (h)). Therefore, the claim is not patent eligible.
Claim Rejections - 35 USC § 103
5. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Beaurepaire et al., (U.S. Patent Application Publication No. 20090249445) in view of Wold et al., (U.S. Patent Application Publication No. 20090203387) in view of Lyman et al., (U.S. Patent Application Publication No. 20140066101).
As to Claim 1, Beaurepaire teaches a method for filtering data transmitted to a user device of a user, comprising: representing, by the one or more processors based on the location information of a subscribing business, a physical region of interest proximate to the subscribing business by a geometric shape; (Fig. 3C geometric shape can be the 303 shape, the business can be the 301 pizza place), and (0042: the parking initiation module 403 can collect and process trajectory or probe data from the vehicle 101 and/or vehicle sensors 103 to analyze for parking related behaviors (e.g., looping or circling over the same set of streets, slowing down, etc.), and (0038: the system 100 computes relevant geofenced areas 203 and 303 around the destinations 201 and 301, respectively, as depicted in FIGS. 2B and 3B. In both examples, the system 100 delimits the geofences 203 and 303 on or along the higher FC roads of the areas 200 and 300, respectively. In both examples, the higher FC roads are wider and busier roads relative to the other roads or routes in the respective areas. Consequently, the higher FC roads are likely to have more traffic and often pose more challenges when attempting to quickly find parking (e.g., due to a lack of easy maneuverability). In both examples, the system 100 designates the geofences 203 and 303 such that they surround the destinations 201 and 301, respectively, on three sides. In one embodiment, the system 100 then identifies the segments 205 and 305 that lead to exiting the geofences 203 and 303, respectively. In one instance, the system 100 computes one or more routes 207 and 307 (e.g., 1-N routes) that enable the user to avoid the segments 205 and 305 and, therefore, remain within the geofences 203 and 303, respectively, while searching for parking. By way of example, “avoiding” in this instance may mean that the one or more routes driven by the user or the driver (e.g., routes 207 and 307) are self-contained within in the geofences 203 and 303, respectively (i.e., the user or driver need not cross or drive on the higher FC roads of the geofences 203 and 303). For example, referring to FIG. 2C, a driver could make one or two different circles around the destination 201 on the routes 207 while looking for parking without having to travel on a segment 205 or drive on or across the geofence 203. Similarly, referring to FIG. 3C, a driver could make a circle adjacent to the destination 301 on the routes 307 without having to travel on a segment 305 or drive on or across the geofence 303. In one embodiment, if the user or the driver has already searched or explored all “internal” links (e.g., segments 203 and routes 207), then the system 100 can provide the user or the driver with the next best route that allows the user or driver to leave the geofence 203 and come back shortly thereafter (e.g., route 209), (Examiner notes: Fig. 3C geometric shape can be the 303 shape, the business can be the 301 pizza place and based on the protectory of the vehicle or the user and the subscribed business inside the geofence with the geometric shape, it provides an advertisement for the pizza place 301 to the user.).
Beaurepaire does not teach subscribing, by a server having one or more processors, one or more memories, a transmitter and a receiver, users from among businesses and consumers, to a proximity-based mobile advertising service to form a subscriber database that includes location information of subscribing businesses;
storing, by the one or more memories, an advertisements database that includes one or more advertisements for each respective subscribing business from the subscriber database;
filtering, by the one or more processors, the advertisements database, to select for display to the user, at least one advertisement corresponding to the subscribing business, responsive to a user trajectory being within at least a portion the geometric shape; and.
However Wold teaches subscribing, by a server having one or more processors (0022: processor), one or more memories (0022: memory), a transmitter and a receiver (0022), users from among businesses and consumers (0055: retailer), to a proximity-based mobile advertising service (0025: merchants as a location-based advertising platform), to form a subscriber database (0027: database 290) that includes location information of subscribing businesses; (0037: Targeted content generator 140 further comprises a subscribed advertiser database 402. In one embodiment, advertisers subscribe to the service provided by targeted content generator 140. In one embodiment, each store or outlet of a subscribed advertiser is also listed in subscribed advertiser database 402. More specifically, the geographic position of each store, or outlet, of a subscribed advertiser is stored in subscribed advertiser database 402. It is noted that the geographic position of a store or outlet may be formatted as a latitude and longitude of a location, an address of a location, the boundaries of a region, or may be represented in another format which permits conveying the location of the store or outlet.),storing, by the one or more memories, an advertisements database that includes one or more advertisements for each respective subscribing business from the subscriber database; (0037: a subscribed advertiser is stored in subscribed advertiser database 402… 0049: promotional codes is stored in subscribed advertiser database 402),filtering, by the one or more processors, the advertisements database, to select for display to the user, at least one advertisement corresponding to the subscribing business, responsive to a user trajectory being within at least a portion the geometric shape; and (0018: targeted content 141 can be selected and sent based upon the new geographic position of mobile electronic device… automatically send an instance of targeted content 141 to mobile electronic device 110 based upon the geographic position of a store or outlet of a subscribed advertiser and its proximity to mobile electronic device 110).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Beaurepaire to include filtering, by the one or more processors, the advertisements database, to select for display to the user, at least one advertisement corresponding to the subscribing business, responsive to a user trajectory being within at least a portion the geometric shape of Wold. Motivation to do so comes from the knowledge well known in the art that filtering, by the one or more processors, the advertisements database, to select for display to the user, at least one advertisement corresponding to the subscribing business, responsive to a user trajectory being within at least a portion the geometric shape would increase the likelihood that the user will review and engage with such advertisement and that would promote an increase in the sales and would therefore make the method/system more profitable.
Beaurepaire does not teach receiving, by the receiver, location information and trajectory information of the user;
transmitting, by the transmitter to the user device, the at least one advertisement.
However Lyman teaches receiving, by the receiver, location information and trajectory information of the user; (0019: location data points can also be used to detect and receive movement trajectories, which can be used to refine detection of presence within geofences representing a physical location (e.g., retail store, user's residence, etc. . . . )),transmitting, by the transmitter to the user device, the at least one advertisement; (0025: serve location-based advertising relevant to the specific electronic retailer store location only when one of the users 110 is in geographic proximity to the store (based on the mobile device 115 detecting a location within one of the monitored child geofences).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Beaurepaire to include transmitting, by the transmitter to the user device, the at least one advertisement of Lyman. Motivation to do so comes from the knowledge well known in the art that transmitting, by the transmitter to the user device, the at least one advertisement would increase the likelihood that the user will review and engage with such advertisement and that would promote an increase in the sales and would therefore make the method/system more profitable.
As to Claim 2, Beaurepaire, Wold, and Lyman teach the method of claim 1.
Beaurepaire further teaches further comprising dynamically adjusting a size of the geometric shape based on one or more sizing criteria; (0033: the initially computed boundaries of the geofence can evolve into more dynamic boundaries if the system 100 determines that one or more relevant parking related factors have changed and/or are changing during the time that a user or a driver is searching for parking. In one instance, the system 100 may adjust the geofence area based on the one or more routes covered by the user during the parking seeking process. For example, the system 100 may infer that the already covered routes are unlikely to present available parking within a short amount of time given the fact that a user or a vehicle (e.g., a vehicle 101) was already unable to find parking on such routes. Accordingly, the system 100 can contemporaneously modify the boundaries of the geofenced area to exclude these routes. In one embodiment, the system 100 may also recompute the geofence boundary based on the evolution of the parking situations. For example, parking spaces may become available or may be taken during the ending or starting of an event. In one instance, the system 100 can access the starting and/or ending times of an event (e.g., via the geographic database 111) and can adjust the boundaries of the geofenced area accordingly. In one instance, the system 100 can modify the geofence boundary based on traffic conditions (e.g., a known road closure). By way of example, the system 100 can enlarge the area or size of the geofence boundary during periods of high traffic and, therefore, potentially low available parking times (e.g., rush hour) and minimize the area or size of the geofence boundary (e.g., saving time and computational resources) during periods of low traffic and, therefore, potentially normal to relatively high available parking times (e.g., late at night, early in the morning, and/or during the weekends). In one instance, the system 100 may recompute the geofence boundary based on one or more local rules or regulations when the user or driver is searching for parking between two time periods or regimes (e.g., no parking permitted changing to parking permitted or vice-versa).
As to Claim 3, Beaurepaire, Wold, and Lyman teach the method of claim 1.
Beaurepaire further teaches further comprising dynamically determining an extended size of the geometric shape based on sizing criteria; (Fig. 2b and 3B extending and redrawing the geofence based on criteria’s and protectories), and (0033: the initially computed boundaries of the geofence can evolve into more dynamic boundaries if the system 100 determines that one or more relevant parking related factors have changed and/or are changing during the time that a user or a driver is searching for parking. In one instance, the system 100 may adjust the geofence area based on the one or more routes covered by the user during the parking seeking process. For example, the system 100 may infer that the already covered routes are unlikely to present available parking within a short amount of time given the fact that a user or a vehicle (e.g., a vehicle 101) was already unable to find parking on such routes. Accordingly, the system 100 can contemporaneously modify the boundaries of the geofenced area to exclude these routes. In one embodiment, the system 100 may also recompute the geofence boundary based on the evolution of the parking situations. For example, parking spaces may become available or may be taken during the ending or starting of an event. In one instance, the system 100 can access the starting and/or ending times of an event (e.g., via the geographic database 111) and can adjust the boundaries of the geofenced area accordingly. In one instance, the system 100 can modify the geofence boundary based on traffic conditions (e.g., a known road closure). By way of example, the system 100 can enlarge the area or size of the geofence boundary during periods of high traffic and, therefore, potentially low available parking times (e.g., rush hour) and minimize the area or size of the geofence boundary (e.g., saving time and computational resources) during periods of low traffic and, therefore, potentially normal to relatively high available parking times (e.g., late at night, early in the morning, and/or during the weekends). In one instance, the system 100 may recompute the geofence boundary based on one or more local rules or regulations when the user or driver is searching for parking between two time periods or regimes (e.g., no parking permitted changing to parking permitted or vice-versa).
As to Claim 4, Beaurepaire, Wold, and Lyman teach the method of claim 3.
Beaurepaire further teaches further comprising dynamically determining a time duration for the extended size of the geometric shape based on the sizing criteria; (Fig. 2b and 3B extending and redrawing the geofence based on criteria’s and protectories), and (0033: the initially computed boundaries of the geofence can evolve into more dynamic boundaries if the system 100 determines that one or more relevant parking related factors have changed and/or are changing during the time that a user or a driver is searching for parking. In one instance, the system 100 may adjust the geofence area based on the one or more routes covered by the user during the parking seeking process. For example, the system 100 may infer that the already covered routes are unlikely to present available parking within a short amount of time given the fact that a user or a vehicle (e.g., a vehicle 101) was already unable to find parking on such routes. Accordingly, the system 100 can contemporaneously modify the boundaries of the geofenced area to exclude these routes. In one embodiment, the system 100 may also recompute the geofence boundary based on the evolution of the parking situations. For example, parking spaces may become available or may be taken during the ending or starting of an event. In one instance, the system 100 can access the starting and/or ending times of an event (e.g., via the geographic database 111) and can adjust the boundaries of the geofenced area accordingly. In one instance, the system 100 can modify the geofence boundary based on traffic conditions (e.g., a known road closure). By way of example, the system 100 can enlarge the area or size of the geofence boundary during periods of high traffic and, therefore, potentially low available parking times (e.g., rush hour) and minimize the area or size of the geofence boundary (e.g., saving time and computational resources) during periods of low traffic and, therefore, potentially normal to relatively high available parking times (e.g., late at night, early in the morning, and/or during the weekends). In one instance, the system 100 may recompute the geofence boundary based on one or more local rules or regulations when the user or driver is searching for parking between two time periods or regimes (e.g., no parking permitted changing to parking permitted or vice-versa).
As to Claim 5, Beaurepaire, Wold, and Lyman teach the method of claim 3.
Beaurepaire further teaches further comprising determining the sizing criteria based on heatmap data for a region proximate to the subscribing business; (Fig. 2b and 3B extending and redrawing the geofence based on criteria’s and protectories), and (0033: the initially computed boundaries of the geofence can evolve into more dynamic boundaries if the system 100 determines that one or more relevant parking related factors have changed and/or are changing during the time that a user or a driver is searching for parking. In one instance, the system 100 may adjust the geofence area based on the one or more routes covered by the user during the parking seeking process. For example, the system 100 may infer that the already covered routes are unlikely to present available parking within a short amount of time given the fact that a user or a vehicle (e.g., a vehicle 101) was already unable to find parking on such routes. Accordingly, the system 100 can contemporaneously modify the boundaries of the geofenced area to exclude these routes. In one embodiment, the system 100 may also recompute the geofence boundary based on the evolution of the parking situations. For example, parking spaces may become available or may be taken during the ending or starting of an event. In one instance, the system 100 can access the starting and/or ending times of an event (e.g., via the geographic database 111) and can adjust the boundaries of the geofenced area accordingly. In one instance, the system 100 can modify the geofence boundary based on traffic conditions (e.g., a known road closure). By way of example, the system 100 can enlarge the area or size of the geofence boundary during periods of high traffic and, therefore, potentially low available parking times (e.g., rush hour) and minimize the area or size of the geofence boundary (e.g., saving time and computational resources) during periods of low traffic and, therefore, potentially normal to relatively high available parking times (e.g., late at night, early in the morning, and/or during the weekends). In one instance, the system 100 may recompute the geofence boundary based on one or more local rules or regulations when the user or driver is searching for parking between two time periods or regimes (e.g., no parking permitted changing to parking permitted or vice-versa).
As to Claim 6, Beaurepaire, Wold, and Lyman teach the method of claim 3.
Beaurepaire further teaches further comprising determining the sizing criteria based on a subscription level in a hierarchical system that assigns extended sizes to the geometric shape; (Fig. 2b and 3B extending and redrawing the geofence based on criteria’s and protectories), and (0033: the initially computed boundaries of the geofence can evolve into more dynamic boundaries if the system 100 determines that one or more relevant parking related factors have changed and/or are changing during the time that a user or a driver is searching for parking. In one instance, the system 100 may adjust the geofence area based on the one or more routes covered by the user during the parking seeking process. For example, the system 100 may infer that the already covered routes are unlikely to present available parking within a short amount of time given the fact that a user or a vehicle (e.g., a vehicle 101) was already unable to find parking on such routes. Accordingly, the system 100 can contemporaneously modify the boundaries of the geofenced area to exclude these routes. In one embodiment, the system 100 may also recompute the geofence boundary based on the evolution of the parking situations. For example, parking spaces may become available or may be taken during the ending or starting of an event. In one instance, the system 100 can access the starting and/or ending times of an event (e.g., via the geographic database 111) and can adjust the boundaries of the geofenced area accordingly. In one instance, the system 100 can modify the geofence boundary based on traffic conditions (e.g., a known road closure). By way of example, the system 100 can enlarge the area or size of the geofence boundary during periods of high traffic and, therefore, potentially low available parking times (e.g., rush hour) and minimize the area or size of the geofence boundary (e.g., saving time and computational resources) during periods of low traffic and, therefore, potentially normal to relatively high available parking times (e.g., late at night, early in the morning, and/or during the weekends). In one instance, the system 100 may recompute the geofence boundary based on one or more local rules or regulations when the user or driver is searching for parking between two time periods or regimes (e.g., no parking permitted changing to parking permitted or vice-versa), and (0064: In one embodiment, the road classification data 709 can include any data item used to classify or distinguish different types of roads, routes, or links based on size, purpose, ordinary level of traffic, etc. (e.g., a functional classification). In one instance, the road classification data 709 can also include any data related to a status of a road or a route (e.g., based on a road closure report).
As to Claim 7, Beaurepaire, Wold, and Lyman teach the method of claim 1.
Beaurepaire further teaches further comprising, determining an extension of a size of the geometric shape using a hierarchical system that assigns different size extensions of the geometric shape to different size extension tiers; (Fig. 2b and 3B extending and redrawing the geofence based on criteria’s and protectories), and (0033: the initially computed boundaries of the geofence can evolve into more dynamic boundaries if the system 100 determines that one or more relevant parking related factors have changed and/or are changing during the time that a user or a driver is searching for parking. In one instance, the system 100 may adjust the geofence area based on the one or more routes covered by the user during the parking seeking process. For example, the system 100 may infer that the already covered routes are unlikely to present available parking within a short amount of time given the fact that a user or a vehicle (e.g., a vehicle 101) was already unable to find parking on such routes. Accordingly, the system 100 can contemporaneously modify the boundaries of the geofenced area to exclude these routes. In one embodiment, the system 100 may also recompute the geofence boundary based on the evolution of the parking situations. For example, parking spaces may become available or may be taken during the ending or starting of an event. In one instance, the system 100 can access the starting and/or ending times of an event (e.g., via the geographic database 111) and can adjust the boundaries of the geofenced area accordingly. In one instance, the system 100 can modify the geofence boundary based on traffic conditions (e.g., a known road closure). By way of example, the system 100 can enlarge the area or size of the geofence boundary during periods of high traffic and, therefore, potentially low available parking times (e.g., rush hour) and minimize the area or size of the geofence boundary (e.g., saving time and computational resources) during periods of low traffic and, therefore, potentially normal to relatively high available parking times (e.g., late at night, early in the morning, and/or during the weekends). In one instance, the system 100 may recompute the geofence boundary based on one or more local rules or regulations when the user or driver is searching for parking between two time periods or regimes (e.g., no parking permitted changing to parking permitted or vice-versa), and (0064: In one embodiment, the road classification data 709 can include any data item used to classify or distinguish different types of roads, routes, or links based on size, purpose, ordinary level of traffic, etc. (e.g., a functional classification). In one instance, the road classification data 709 can also include any data related to a status of a road or a route (e.g., based on a road closure report).
As to Claim 8, Beaurepaire, Wold, and Lyman teach the method of claim 7.
Beaurepaire further teaches further comprising selecting an applicable size extension tier from among the different size extension tiers responsive to heatmap data derived from a heatmap image; (Fig. 2b and 3B extending and redrawing the geofence based on criteria’s and protectories), and (0033: the initially computed boundaries of the geofence can evolve into more dynamic boundaries if the system 100 determines that one or more relevant parking related factors have changed and/or are changing during the time that a user or a driver is searching for parking. In one instance, the system 100 may adjust the geofence area based on the one or more routes covered by the user during the parking seeking process. For example, the system 100 may infer that the already covered routes are unlikely to present available parking within a short amount of time given the fact that a user or a vehicle (e.g., a vehicle 101) was already unable to find parking on such routes. Accordingly, the system 100 can contemporaneously modify the boundaries of the geofenced area to exclude these routes. In one embodiment, the system 100 may also recompute the geofence boundary based on the evolution of the parking situations. For example, parking spaces may become available or may be taken during the ending or starting of an event. In one instance, the system 100 can access the starting and/or ending times of an event (e.g., via the geographic database 111) and can adjust the boundaries of the geofenced area accordingly. In one instance, the system 100 can modify the geofence boundary based on traffic conditions (e.g., a known road closure). By way of example, the system 100 can enlarge the area or size of the geofence boundary during periods of high traffic and, therefore, potentially low available parking times (e.g., rush hour) and minimize the area or size of the geofence boundary (e.g., saving time and computational resources) during periods of low traffic and, therefore, potentially normal to relatively high available parking times (e.g., late at night, early in the morning, and/or during the weekends). In one instance, the system 100 may recompute the geofence boundary based on one or more local rules or regulations when the user or driver is searching for parking between two time periods or regimes (e.g., no parking permitted changing to parking permitted or vice-versa), and (0064: In one embodiment, the road classification data 709 can include any data item used to classify or distinguish different types of roads, routes, or links based on size, purpose, ordinary level of traffic, etc. (e.g., a functional classification). In one instance, the road classification data 709 can also include any data related to a status of a road or a route (e.g., based on a road closure report).
As to Claim 9, Beaurepaire, Wold, and Lyman teach the method of claim 7.
Beaurepaire further teaches further comprising selecting an applicable size extension tier from among the different size extension tiers responsive to subscription data; (Fig. 2b and 3B extending and redrawing the geofence based on criteria’s and protectories), and (0033: the initially computed boundaries of the geofence can evolve into more dynamic boundaries if the system 100 determines that one or more relevant parking related factors have changed and/or are changing during the time that a user or a driver is searching for parking. In one instance, the system 100 may adjust the geofence area based on the one or more routes covered by the user during the parking seeking process. For example, the system 100 may infer that the already covered routes are unlikely to present available parking within a short amount of time given the fact that a user or a vehicle (e.g., a vehicle 101) was already unable to find parking on such routes. Accordingly, the system 100 can contemporaneously modify the boundaries of the geofenced area to exclude these routes. In one embodiment, the system 100 may also recompute the geofence boundary based on the evolution of the parking situations. For example, parking spaces may become available or may be taken during the ending or starting of an event. In one instance, the system 100 can access the starting and/or ending times of an event (e.g., via the geographic database 111) and can adjust the boundaries of the geofenced area accordingly. In one instance, the system 100 can modify the geofence boundary based on traffic conditions (e.g., a known road closure). By way of example, the system 100 can enlarge the area or size of the geofence boundary during periods of high traffic and, therefore, potentially low available parking times (e.g., rush hour) and minimize the area or size of the geofence boundary (e.g., saving time and computational resources) during periods of low traffic and, therefore, potentially normal to relatively high available parking times (e.g., late at night, early in the morning, and/or during the weekends). In one instance, the system 100 may recompute the geofence boundary based on one or more local rules or regulations when the user or driver is searching for parking between two time periods or regimes (e.g., no parking permitted changing to parking permitted or vice-versa), and (0064: In one embodiment, the road classification data 709 can include any data item used to classify or distinguish different types of roads, routes, or links based on size, purpose, ordinary level of traffic, etc. (e.g., a functional classification). In one instance, the road classification data 709 can also include any data related to a status of a road or a route (e.g., based on a road closure report).
As to Claim 10, Beaurepaire, Wold, and Lyman teach the method of claim 1.
Beaurepaire further teaches further comprising, determining a time duration of an extension of a size of the geometric shape using a hierarchical system that assigns different time duration extensions to different time duration tiers; (Fig. 2b and 3B extending and redrawing the geofence based on criteria’s and protectories), and (0033: the initially computed boundaries of the geofence can evolve into more dynamic boundaries if the system 100 determines that one or more relevant parking related factors have changed and/or are changing during the time that a user or a driver is searching for parking. In one instance, the system 100 may adjust the geofence area based on the one or more routes covered by the user during the parking seeking process. For example, the system 100 may infer that the already covered routes are unlikely to present available parking within a short amount of time given the fact that a user or a vehicle (e.g., a vehicle 101) was already unable to find parking on such routes. Accordingly, the system 100 can contemporaneously modify the boundaries of the geofenced area to exclude these routes. In one embodiment, the system 100 may also recompute the geofence boundary based on the evolution of the parking situations. For example, parking spaces may become available or may be taken during the ending or starting of an event. In one instance, the system 100 can access the starting and/or ending times of an event (e.g., via the geographic database 111) and can adjust the boundaries of the geofenced area accordingly. In one instance, the system 100 can modify the geofence boundary based on traffic conditions (e.g., a known road closure). By way of example, the system 100 can enlarge the area or size of the geofence boundary during periods of high traffic and, therefore, potentially low available parking times (e.g., rush hour) and minimize the area or size of the geofence boundary (e.g., saving time and computational resources) during periods of low traffic and, therefore, potentially normal to relatively high available parking times (e.g., late at night, early in the morning, and/or during the weekends). In one instance, the system 100 may recompute the geofence boundary based on one or more local rules or regulations when the user or driver is searching for parking between two time periods or regimes (e.g., no parking permitted changing to parking permitted or vice-versa), and (0064: In one embodiment, the road classification data 709 can include any data item used to classify or distinguish different types of roads, routes, or links based on size, purpose, ordinary level of traffic, etc. (e.g., a functional classification). In one instance, the road classification data 709 can also include any data related to a status of a road or a route (e.g., based on a road closure report).
As to Claim 11, Beaurepaire, Wold, and Lyman teach the method of claim 10.
Beaurepaire further teaches further comprising selecting an applicable time duration tier from among the different time duration tiers responsive to heatmap data derived from a heatmap image; (Fig. 2b and 3B extending and redrawing the geofence based on criteria’s and protectories), and (0033: the initially computed boundaries of the geofence can evolve into more dynamic boundaries if the system 100 determines that one or more relevant parking related factors have changed and/or are changing during the time that a user or a driver is searching for parking. In one instance, the system 100 may adjust the geofence area based on the one or more routes covered by the user during the parking seeking process. For example, the system 100 may infer that the already covered routes are unlikely to present available parking within a short amount of time given the fact that a user or a vehicle (e.g., a vehicle 101) was already unable to find parking on such routes. Accordingly, the system 100 can contemporaneously modify the boundaries of the geofenced area to exclude these routes. In one embodiment, the system 100 may also recompute the geofence boundary based on the evolution of the parking situations. For example, parking spaces may become available or may be taken during the ending or starting of an event. In one instance, the system 100 can access the starting and/or ending times of an event (e.g., via the geographic database 111) and can adjust the boundaries of the geofenced area accordingly. In one instance, the system 100 can modify the geofence boundary based on traffic conditions (e.g., a known road closure). By way of example, the system 100 can enlarge the area or size of the geofence boundary during periods of high traffic and, therefore, potentially low available parking times (e.g., rush hour) and minimize the area or size of the geofence boundary (e.g., saving time and computational resources) during periods of low traffic and, therefore, potentially normal to relatively high available parking times (e.g., late at night, early in the morning, and/or during the weekends). In one instance, the system 100 may recompute the geofence boundary based on one or more local rules or regulations when the user or driver is searching for parking between two time periods or regimes (e.g., no parking permitted changing to parking permitted or vice-versa), and (0064: In one embodiment, the road classification data 709 can include any data item used to classify or distinguish different types of roads, routes, or links based on size, purpose, ordinary level of traffic, etc. (e.g., a functional classification). In one instance, the road classification data 709 can also include any data related to a status of a road or a route (e.g., based on a road closure report).
As to Claim 12, Beaurepaire, Wold, and Lyman teach the method of claim 10.
Beaurepaire further teaches further comprising selecting an applicable time duration tier from among the different time duration tiers responsive to subscription data; (Fig. 3C geometric shape can be the 303 shape, the business can be the 301 pizza place), and (0042: the parking initiation module 403 can collect and process trajectory or probe data from the vehicle 101 and/or vehicle sensors 103 to analyze for parking related behaviors (e.g., looping or circling over the same set of streets, slowing down, etc.), and (0038: the system 100 computes relevant geofenced areas 203 and 303 around the destinations 201 and 301, respectively, as depicted in FIGS. 2B and 3B. In both examples, the system 100 delimits the geofences 203 and 303 on or along the higher FC roads of the areas 200 and 300, respectively. In both examples, the higher FC roads are wider and busier roads relative to the other roads or routes in the respective areas. Consequently, the higher FC roads are likely to have more traffic and often pose more challenges when attempting to quickly find parking (e.g., due to a lack of easy maneuverability). In both examples, the system 100 designates the geofences 203 and 303 such that they surround the destinations 201 and 301, respectively, on three sides. In one embodiment, the system 100 then identifies the segments 205 and 305 that lead to exiting the geofences 203 and 303, respectively. In one instance, the system 100 computes one or more routes 207 and 307 (e.g., 1-N routes) that enable the user to avoid the segments 205 and 305 and, therefore, remain within the geofences 203 and 303, respectively, while searching for parking. By way of example, “avoiding” in this instance may mean that the one or more routes driven by the user or the driver (e.g., routes 207 and 307) are self-contained within in the geofences 203 and 303, respectively (i.e., the user or driver need not cross or drive on the higher FC roads of the geofences 203 and 303). For example, referring to FIG. 2C, a driver could make one or two different circles around the destination 201 on the routes 207 while looking for parking without having to travel on a segment 205 or drive on or across the geofence 203. Similarly, referring to FIG. 3C, a driver could make a circle adjacent to the destination 301 on the routes 307 without having to travel on a segment 305 or drive on or across the geofence 303. In one embodiment, if the user or the driver has already searched or explored all “internal” links (e.g., segments 203 and routes 207), then the system 100 can provide the user or the driver with the next best route that allows the user or driver to leave the geofence 203 and come back shortly thereafter (e.g., route 209).
As to Claim 13, Beaurepaire, Wold, and Lyman teach the method of claim 1.
Beaurepaire further teaches further comprising generating different representations of the physical region of interest proximate to the user that respectively correspond to different subscribing businesses(0033).
As to Claim 14, Beaurepaire, Wold, and Lyman teach the method of claim 13.
Beaurepaire further teaches further comprising generating geometric shapes corresponding to at least two of the different representations to have different sizes; (Fig. 3C reguion 1 can be the different shapes found in the fig.).
As to Claim 15, Beaurepaire, Wold, and Lyman teach the method of claim 13.
Beaurepaire further teaches further comprising generating geometric shapes corresponding to at least two of the different representations to have different durations during which sizes of geometric shapes are extended; (Fig. 3C region 1 can be the different shapes found in the figure and one is bigger than the other).
As to Claim 16, Beaurepaire, Wold, and Lyman teach the method of claim 14.
Beaurepaire further teaches further comprising dynamically creating the different representations responsive to the user moving proximate to the different subscribing businesses; (Fig. 2b-c and 3b-c can change based on the moving vehicle).
As to Claim 17, Beaurepaire, Wold, and Lyman teach the method of claim 1.
Beaurepaire further teaches further comprising providing marketing and traffic information to the businesses using a hierarchical system that assigns different access levels to the marketing and traffic information to different tiers; (access level to different advertisements can be the level of where the vehicle is located, if the vehicle is located close to the pizza place the driver is given an access level of an advertisement being displayed for the pizza place on the device).
As to Claim 18, Beaurepaire, Wold, and Lyman teach the method of claim 17.
Beaurepaire further teaches wherein the marketing and traffic information comprises foot traffic information corresponding to a respective one or more areas proximate to the businesses; (Fig. 2b-c and 3b-c).
As to Claim 19, Beaurepaire teaches a system for filtering data transmitted to a user device of a subscribing consumer, comprising:represent based on the location information of a subscribing business, a physical region of interest proximate to the subscribing business by a geometric shape; and; (Fig. 3C geometric shape can be the 303 shape, the business can be the 301 pizza place), and (0042: the parking initiation module 403 can collect and process trajectory or probe data from the vehicle 101 and/or vehicle sensors 103 to analyze for parking related behaviors (e.g., looping or circling over the same set of streets, slowing down, etc.), and (0038: the system 100 computes relevant geofenced areas 203 and 303 around the destinations 201 and 301, respectively, as depicted in FIGS. 2B and 3B. In both examples, the system 100 delimits the geofences 203 and 303 on or along the higher FC roads of the areas 200 and 300, respectively. In both examples, the higher FC roads are wider and busier roads relative to the other roads or routes in the respective areas. Consequently, the higher FC roads are likely to have more traffic and often pose more challenges when attempting to quickly find parking (e.g., due to a lack of easy maneuverability). In both examples, the system 100 designates the geofences 203 and 303 such that they surround the destinations 201 and 301, respectively, on three sides. In one embodiment, the system 100 then identifies the segments 205 and 305 that lead to exiting the geofences 203 and 303, respectively. In one instance, the system 100 computes one or more routes 207 and 307 (e.g., 1-N routes) that enable the user to avoid the segments 205 and 305 and, therefore, remain within the geofences 203 and 303, respectively, while searching for parking. By way of example, “avoiding” in this instance may mean that the one or more routes driven by the user or the driver (e.g., routes 207 and 307) are self-contained within in the geofences 203 and 303, respectively (i.e., the user or driver need not cross or drive on the higher FC roads of the geofences 203 and 303). For example, referring to FIG. 2C, a driver could make one or two different circles around the destination 201 on the routes 207 while looking for parking without having to travel on a segment 205 or drive on or across the geofence 203. Similarly, referring to FIG. 3C, a driver could make a circle adjacent to the destination 301 on the routes 307 without having to travel on a segment 305 or drive on or across the geofence 303. In one embodiment, if the user or the driver has already searched or explored all “internal” links (e.g., segments 203 and routes 207), then the system 100 can provide the user or the driver with the next best route that allows the user or driver to leave the geofence 203 and come back shortly thereafter (e.g., route 209), (Examiner notes: Fig. 3C geometric shape can be the 303 shape, the business can be the 301 pizza place and based on the protectory of the vehicle or the user and the subscribed business inside the geofence with the geometric shape, it provides an advertisement for the pizza place 301 to the user.).
Beaurepaire does not teach one or more memories, individually or in combination, having instructions and an advertisements database that includes one or more advertisements and location information for each respective business from a subscriber database;
one or more processors each coupled to at least one of the one or more memories and configurable/operable to execute the instructions to:subscribe users from among businesses and consumers to a proximity-based mobile advertising service to form a subscriber database;
filter the advertisements database, to select for display to a subscribing consumer, at least one advertisement corresponding to the subscribing business, responsive to a user trajectory being within at least a portion the geometric shape; and.
However Wold teaches one or more memories, individually or in combination, having instructions and an advertisements database that includes one or more advertisements and location information for each respective business from a subscriber database; (0037: a subscribed advertiser is stored in subscribed advertiser database 402… 0049: promotional codes is stored in subscribed advertiser database 402),one or more processors each coupled to at least one of the one or more memories and configurable/operable to execute the instructions to:subscribe users from among businesses and consumers to a proximity-based mobile advertising service to form a subscriber database; (0037: a subscribed advertiser is stored in subscribed advertiser database 402… 0049: promotional codes is stored in subscribed advertiser database 402), filter the advertisements database, to select for display to a subscribing consumer, at least one advertisement corresponding to the subscribing business, responsive to a user trajectory being within at least a portion the geometric shape; and (0018: targeted content 141 can be selected and sent based upon the new geographic position of mobile electronic device… automatically send an instance of targeted content 141 to mobile electronic device 110 based upon the geographic position of a store or outlet of a subscribed advertiser and its proximity to mobile electronic device 110),
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Beaurepaire to include filter the advertisements database, to select for display to a subscribing consumer, at least one advertisement corresponding to the subscribing business, responsive to a user trajectory being within at least a portion the geometric shape of Wold. Motivation to do so comes from the knowledge well known in the art that filter the advertisements database, to select for display to a subscribing consumer, at least one advertisement corresponding to the subscribing business, responsive to a user trajectory being within at least a portion the geometric shape would increase the likelihood that the user will review and engage with such advertisement and that would promote an increase in the sales and would therefore make the method/system more profitable.
Beaurepaire does not teach a receiver configured to receive location information and trajectory information of the subscribing consumer;
a transmitter configured to transmit the at least one advertisement to the user device of the subscribing consumer.
However Lyman teaches a receiver configured to receive location information and trajectory information of the subscribing consumer; (0019: location data points can also be used to detect and receive movement trajectories, which can be used to refine detection of presence within geofences representing a physical location (e.g., retail store, user's residence, etc. . . . )),a transmitter configured to transmit the at least one advertisement to the user device of the subscribing consumer; (0025: serve location-based advertising relevant to the specific electronic retailer store location only when one of the users 110 is in geographic proximity to the store (based on the mobile device 115 detecting a location within one of the monitored child geofences).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Beaurepaire to include a transmitter configured to transmit the at least one advertisement to the user device of the subscribing consumer of Lyman. Motivation to do so comes from the knowledge well known in the art that a transmitter configured to transmit the at least one advertisement to the user device of the subscribing consumer would increase the likelihood that the user will review and engage with such advertisement and that would promote an increase in the sales and would therefore make the method/system more profitable.
As to Claim 20, Beaurepaire teaches a method for filtering data transmitted to a user device of a user, comprising:representing, by the one or more processors based on the location information and the trajectory information of the user, a physical region of interest proximate to the user by a geometric shape; (Fig. 3C geometric shape can be the 303 shape, the business can be the 301 pizza place), and (0042: the parking initiation module 403 can collect and process trajectory or probe data from the vehicle 101 and/or vehicle sensors 103 to analyze for parking related behaviors (e.g., looping or circling over the same set of streets, slowing down, etc.), and (0038: the system 100 computes relevant geofenced areas 203 and 303 around the destinations 201 and 301, respectively, as depicted in FIGS. 2B and 3B. In both examples, the system 100 delimits the geofences 203 and 303 on or along the higher FC roads of the areas 200 and 300, respectively. In both examples, the higher FC roads are wider and busier roads relative to the other roads or routes in the respective areas. Consequently, the higher FC roads are likely to have more traffic and often pose more challenges when attempting to quickly find parking (e.g., due to a lack of easy maneuverability). In both examples, the system 100 designates the geofences 203 and 303 such that they surround the destinations 201 and 301, respectively, on three sides. In one embodiment, the system 100 then identifies the segments 205 and 305 that lead to exiting the geofences 203 and 303, respectively. In one instance, the system 100 computes one or more routes 207 and 307 (e.g., 1-N routes) that enable the user to avoid the segments 205 and 305 and, therefore, remain within the geofences 203 and 303, respectively, while searching for parking. By way of example, “avoiding” in this instance may mean that the one or more routes driven by the user or the driver (e.g., routes 207 and 307) are self-contained within in the geofences 203 and 303, respectively (i.e., the user or driver need not cross or drive on the higher FC roads of the geofences 203 and 303). For example, referring to FIG. 2C, a driver could make one or two different circles around the destination 201 on the routes 207 while looking for parking without having to travel on a segment 205 or drive on or across the geofence 203. Similarly, referring to FIG. 3C, a driver could make a circle adjacent to the destination 301 on the routes 307 without having to travel on a segment 305 or drive on or across the geofence 303. In one embodiment, if the user or the driver has already searched or explored all “internal” links (e.g., segments 203 and routes 207), then the system 100 can provide the user or the driver with the next best route that allows the user or driver to leave the geofence 203 and come back shortly thereafter (e.g., route 209), (Examiner notes: Fig. 3C geometric shape can be the 303 shape, the business can be the 301 pizza place and based on the protectory of the vehicle or the user and the subscribed business inside the geofence with the geometric shape, it provides an advertisement for the pizza place 301 to the user.).
Beaurepaire does not teach subscribing, by a server having one or more processors, one or more memories, a transmitter and a receiver, users from among businesses and consumers, to a proximity-based event and content access service to form a subscriber database of subscriber information;
storing, by the one or more memories, exclusive digital content provided by the businesses in an exclusive digital content database;
filtering, by the one or more processors, the exclusive digital content database to identify one or more items of exclusive digital content provided by one or more of the businesses that are within a trajectory of at least a portion of the geometric shape; and.
However Wold teaches subscribing, by a server having one or more processors, one or more memories, a transmitter and a receiver, users from among businesses and consumers, to a proximity-based event and content access service to form a subscriber database of subscriber information; (0037: Targeted content generator 140 further comprises a subscribed advertiser database 402. In one embodiment, advertisers subscribe to the service provided by targeted content generator 140. In one embodiment, each store or outlet of a subscribed advertiser is also listed in subscribed advertiser database 402. More specifically, the geographic position of each store, or outlet, of a subscribed advertiser is stored in subscribed advertiser database 402. It is noted that the geographic position of a store or outlet may be formatted as a latitude and longitude of a location, an address of a location, the boundaries of a region, or may be represented in another format which permits conveying the location of the store or outlet.), storing, by the one or more memories, exclusive digital content provided by the businesses in an exclusive digital content database; (0037: a subscribed advertiser is stored in subscribed advertiser database 402… 0049: promotional codes is stored in subscribed advertiser database 402), filtering, by the one or more processors, the exclusive digital content database to identify one or more items of exclusive digital content provided by one or more of the businesses that are within a trajectory of at least a portion of the geometric shape; and (0018: targeted content 141 can be selected and sent based upon the new geographic position of mobile electronic device… automatically send an instance of targeted content 141 to mobile electronic device 110 based upon the geographic position of a store or outlet of a subscribed advertiser and its proximity to mobile electronic device 110).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Beaurepaire to include filtering, by the one or more processors, the exclusive digital content database to identify one or more items of exclusive digital content provided by one or more of the businesses that are within a trajectory of at least a portion of the geometric shape of Wold. Motivation to do so comes from the knowledge well known in the art that filtering, by the one or more processors, the exclusive digital content database to identify one or more items of exclusive digital content provided by one or more of the businesses that are within a trajectory of at least a portion of the geometric shape would increase the likelihood that the user will review and engage with such advertisement and that would promote an increase in the sales and would therefore make the method/system more profitable.
Beaurepaire does not teach receiving, by the receiver, location information and trajectory information of the user;
transmitting, by the transmitter to the user device, the one or more items of exclusive digital content.
However Lyman teaches receiving, by the receiver, location information and trajectory information of the user; (0019: location data points can also be used to detect and receive movement trajectories, which can be used to refine detection of presence within geofences representing a physical location (e.g., retail store, user's residence, etc. . . . )),transmitting, by the transmitter to the user device, the one or more items of exclusive digital content; (0025: serve location-based advertising relevant to the specific electronic retailer store location only when one of the users 110 is in geographic proximity to the store (based on the mobile device 115 detecting a location within one of the monitored child geofences).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Beaurepaire to include transmitting, by the transmitter to the user device, the one or more items of exclusive digital content of Lyman. Motivation to do so comes from the knowledge well known in the art that transmitting, by the transmitter to the user device, the one or more items of exclusive digital content would increase the likelihood that the user will review and engage with such advertisement and that would promote an increase in the sales and would therefore make the method/system more profitable.
As to Claim 21, Beaurepaire, Wold, and Lyman teach the method of claim 20.
Beaurepaire further teaches further comprising: accessing the subscriber information in the subscriber database to determine user preferences with respect to types of digital content to be received by the user, wherein filtering the exclusive digital content database comprises filtering the exclusive digital content provided by one or more of the businesses that are within the trajectory of at least the portion of the geometric shape based on the user preferences with respect to types of digital content to be received by the user; (Fig. 3C geometric shape can be the 303 shape, the business can be the 301 pizza place), and (0042: the parking initiation module 403 can collect and process trajectory or probe data from the vehicle 101 and/or vehicle sensors 103 to analyze for parking related behaviors (e.g., looping or circling over the same set of streets, slowing down, etc.), and (0038: the system 100 computes relevant geofenced areas 203 and 303 around the destinations 201 and 301, respectively, as depicted in FIGS. 2B and 3B. In both examples, the system 100 delimits the geofences 203 and 303 on or along the higher FC roads of the areas 200 and 300, respectively. In both examples, the higher FC roads are wider and busier roads relative to the other roads or routes in the respective areas. Consequently, the higher FC roads are likely to have more traffic and often pose more challenges when attempting to quickly find parking (e.g., due to a lack of easy maneuverability). In both examples, the system 100 designates the geofences 203 and 303 such that they surround the destinations 201 and 301, respectively, on three sides. In one embodiment, the system 100 then identifies the segments 205 and 305 that lead to exiting the geofences 203 and 303, respectively. In one instance, the system 100 computes one or more routes 207 and 307 (e.g., 1-N routes) that enable the user to avoid the segments 205 and 305 and, therefore, remain within the geofences 203 and 303, respectively, while searching for parking. By way of example, “avoiding” in this instance may mean that the one or more routes driven by the user or the driver (e.g., routes 207 and 307) are self-contained within in the geofences 203 and 303, respectively (i.e., the user or driver need not cross or drive on the higher FC roads of the geofences 203 and 303). For example, referring to FIG. 2C, a driver could make one or two different circles around the destination 201 on the routes 207 while looking for parking without having to travel on a segment 205 or drive on or across the geofence 203. Similarly, referring to FIG. 3C, a driver could make a circle adjacent to the destination 301 on the routes 307 without having to travel on a segment 305 or drive on or across the geofence 303. In one embodiment, if the user or the driver has already searched or explored all “internal” links (e.g., segments 203 and routes 207), then the system 100 can provide the user or the driver with the next best route that allows the user or driver to leave the geofence 203 and come back shortly thereafter (e.g., route 209), (Examiner notes: Fig. 3C geometric shape can be the 303 shape, the business can be the 301 pizza place and based on the protectory of the vehicle or the user and the subscribed business inside the geofence with the geometric shape, it provides an advertisement for the pizza place 301 to the user.).
As to Claim 1, Beaurepaire teaches a system for filtering data trans mitted to a user device of a user, comprising: represent, based on the location information and the trajectory information of the user, a physical region of interest proximate to the user by a geometric shape; and (Fig. 3C geometric shape can be the 303 shape, the business can be the 301 pizza place), and (0042: the parking initiation module 403 can collect and process trajectory or probe data from the vehicle 101 and/or vehicle sensors 103 to analyze for parking related behaviors (e.g., looping or circling over the same set of streets, slowing down, etc.), and (0038: the system 100 computes relevant geofenced areas 203 and 303 around the destinations 201 and 301, respectively, as depicted in FIGS. 2B and 3B. In both examples, the system 100 delimits the geofences 203 and 303 on or along the higher FC roads of the areas 200 and 300, respectively. In both examples, the higher FC roads are wider and busier roads relative to the other roads or routes in the respective areas. Consequently, the higher FC roads are likely to have more traffic and often pose more challenges when attempting to quickly find parking (e.g., due to a lack of easy maneuverability). In both examples, the system 100 designates the geofences 203 and 303 such that they surround the destinations 201 and 301, respectively, on three sides. In one embodiment, the system 100 then identifies the segments 205 and 305 that lead to exiting the geofences 203 and 303, respectively. In one instance, the system 100 computes one or more routes 207 and 307 (e.g., 1-N routes) that enable the user to avoid the segments 205 and 305 and, therefore, remain within the geofences 203 and 303, respectively, while searching for parking. By way of example, “avoiding” in this instance may mean that the one or more routes driven by the user or the driver (e.g., routes 207 and 307) are self-contained within in the geofences 203 and 303, respectively (i.e., the user or driver need not cross or drive on the higher FC roads of the geofences 203 and 303). For example, referring to FIG. 2C, a driver could make one or two different circles around the destination 201 on the routes 207 while looking for parking without having to travel on a segment 205 or drive on or across the geofence 203. Similarly, referring to FIG. 3C, a driver could make a circle adjacent to the destination 301 on the routes 307 without having to travel on a segment 305 or drive on or across the geofence 303. In one embodiment, if the user or the driver has already searched or explored all “internal” links (e.g., segments 203 and routes 207), then the system 100 can provide the user or the driver with the next best route that allows the user or driver to leave the geofence 203 and come back shortly thereafter (e.g., route 209), (Examiner notes: Fig. 3C geometric shape can be the 303 shape, the business can be the 301 pizza place and based on the protectory of the vehicle or the user and the subscribed business inside the geofence with the geometric shape, it provides an advertisement for the pizza place 301 to the user.).
Beaurepaire does not teach one or more memories, individually or in combination, having instructions and an exclusive digital content database including exclusive digital content provided by businesses;
one or more processors each coupled to at least one of the one or more memories and configurable/operable to execute the instructions to:subscribe users from among the businesses and consumers, to a proximity based event and content access service to form a subscriber database of subscriber information;
store exclusive digital content provided by the businesses in an exclusive digital content database; and
filter the exclusive digital content database to identify one or more items of exclusive digital content provided by one or more of the businesses that are within a trajectory of at least a portion of the geometric shape.
However Wold teaches one or more memories, individually or in combination, having instructions and an exclusive digital content database including exclusive digital content provided by businesses; (0037: Targeted content generator 140 further comprises a subscribed advertiser database 402. In one embodiment, advertisers subscribe to the service provided by targeted content generator 140. In one embodiment, each store or outlet of a subscribed advertiser is also listed in subscribed advertiser database 402. More specifically, the geographic position of each store, or outlet, of a subscribed advertiser is stored in subscribed advertiser database 402. It is noted that the geographic position of a store or outlet may be formatted as a latitude and longitude of a location, an address of a location, the boundaries of a region, or may be represented in another format which permits conveying the location of the store or outlet.), one or more processors each coupled to at least one of the one or more memories and configurable/operable to execute the instructions to:subscribe users from among the businesses and consumers, to a proximity based event and content access service to form a subscriber database of subscriber information; (0018: targeted content 141 can be selected and sent based upon the new geographic position of mobile electronic device… automatically send an instance of targeted content 141 to mobile electronic device 110 based upon the geographic position of a store or outlet of a subscribed advertiser and its proximity to mobile electronic device 110),store exclusive digital content provided by the businesses in an exclusive digital content database; (0037: a subscribed advertiser is stored in subscribed advertiser database 402… 0049: promotional codes is stored in subscribed advertiser database 402),filter the exclusive digital content database to identify one or more items of exclusive digital content provided by one or more of the businesses that are within a trajectory of at least a portion of the geometric shape; and (0018: targeted content 141 can be selected and sent based upon the new geographic position of mobile electronic device… automatically send an instance of targeted content 141 to mobile electronic device 110 based upon the geographic position of a store or outlet of a subscribed advertiser and its proximity to mobile electronic device 110).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Beaurepaire to include filter the exclusive digital content database to identify one or more items of exclusive digital content provided by one or more of the businesses that are within a trajectory of at least a portion of the geometric shape of Wold. Motivation to do so comes from the knowledge well known in the art that filter the exclusive digital content database to identify one or more items of exclusive digital content provided by one or more of the businesses that are within a trajectory of at least a portion of the geometric shape would increase the likelihood that the user will review and engage with such advertisement and that would promote an increase in the sales and would therefore make the method/system more profitable.
Beaurepaire does not teach a receiver configured to receive location information and trajectory information of the user;
a transmitter configured to transmit the one or more items of exclusive digital content.
However Lyman teaches a receiver configured to receive location information and trajectory information of the user; (0019: location data points can also be used to detect and receive movement trajectories, which can be used to refine detection of presence within geofences representing a physical location (e.g., retail store, user's residence, etc. . . . )),a transmitter configured to transmit the one or more items of exclusive digital content; (0025: serve location-based advertising relevant to the specific electronic retailer store location only when one of the users 110 is in geographic proximity to the store (based on the mobile device 115 detecting a location within one of the monitored child geofences).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Beaurepaire to include a transmitter configured to transmit the one or more items of exclusive digital content of Lyman. Motivation to do so comes from the knowledge well known in the art that a transmitter configured to transmit the one or more items of exclusive digital content would increase the likelihood that the user will review and engage with such advertisement and that would promote an increase in the sales and would therefore make the method/system more profitable.
NPL Reference
6. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. The NPL “What is Pub/Sub? The Publish/Subscribe model explained” describes “Pub/Sub (or Publish/Subscribe) is an architectural design pattern used in distributed systems for asynchronous communication between different components or services. Although Publish/Subscribe is based on earlier design patterns like message queuing and event brokers, it is more flexible and scalable. The key to this is the fact that Pub/Sub enables the movement of messages between different components of the system without the components being aware of each other’s identity (they are decoupled).”.
Pertinent Art
7. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Reference# 20120310717 teaches similar invention which describes the system 100 includes a merchant/advertiser platform 121 for providing access to the functions of the advertising platform 101 to merchants and other advertisers. For example, the merchant/advertiser platform 121 provides self-service interfaces to enable merchants and/or advertisers to register their listing for location-based results (e.g., a place or point of interest), buy advertisements and search placements, access reporting metrics, etc. In one embodiment, the merchant/advertiser platform 121 maintains an advertisement database 123 for storing advertisements, criteria for targeted users, advertising campaigns, coupons, and other related information. In one embodiment, the content information (e.g., media files, graphics, etc.) for the advertisements may be obtained from or provided directly by the service platform 109, the services 111a-111n, and/or the content providers 113a-113m. In one embodiment, the merchant/advertiser platform 121 also provides access to analytical reports generated by the advertising platform 101 to merchants/developers. In one embodiment, access to the information on the advertisement database 125 is controlled to only privileged services (e.g., the advertising engine 119). In some embodiments, access is obtained through an API 125.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TAREK ELCHANTI whose telephone number is (571) 272-9638. The examiner can normally be reached on Flex Mon - Thur 7-7:00 and Fri 7-4:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Waseem Ashraf can be reached on (571) 270-3948. The fax phone number for the organization where this application or proceeding is assigned is (571) 273-8300.
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/TAREK ELCHANTI/Primary Examiner, Art Unit 3621B
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