DETAILED ACTION
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 .
Claim Rejections - 35 USC § 101
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.
The claims herein are directed to a method and system which would be classified under one of the listed statutory classifications (i.e., 2019 Revised Patent Subject Matter Eligibility Guidance (hereinafter “PEG”) “PEG” Step 1=Yes). Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more. The claim(s) recite(s) the following limitations that are considered to be abstract ideas:
Claim 1, 10, and 20
obtain one or more attributes associated with each of the plurality of digital screens;
receive scheduling data associated with one or more advertisements;
generate a proof of performance report associated with the one or more advertisements;
generate advertisement contextual schedule data associated with the one or more advertisements for the plurality of digital screens of the digital signage network based on advertisement product taxonomy, the performance report, the one or more attributes, and the scheduling data; and
provide the one or more advertisements to the plurality of digital screens of the digital signage network based on the contextual advertisement schedule data.
The limitations of independent claim 1, 10 and 20, as detailed above, as drafted, falls within the “Certain Method of Organizing Human Activity” grouping of abstract ideas namely commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations) because the system is configured to provide the advertisements to the plurality of digital screens of the digital signage network based on the contextual advertisement schedule data. This judicial exception is not integrated into a practical application. In particular the claims recite the additional elements of using memory, computer, digital screens, network, , processor, computer readable storage medium. The aforementioned additional generic computing elements perform the steps of the claims at a high level of generality (i.e. As a generic medium performing generic computer function of obtain, receive, generate, provide such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to
amount to significantly more than the judicial exception. The claims does not include additional elements that are sufficient to amount to significantly more than the judicial exception As discussed above with respect to integration of the abstract idea into a practical application, the additional element of memory, computer, digital screens, network, , processor, computer readable storage medium, to obtain, receive, generate, provide … amounts to no more than mere instruction to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim is not patent eligible. Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of the computer or improves any other technology. Their collective functions merely provide generic computer implementation.
Thus, taken individually and in combination, the additional elements do not amount to
significantly more than the above-identified judicial exception (the abstract idea).
The dependent claims 2-9 and 11-19 appear to merely further limit the abstract idea and as such, the analysis of dependent 2-9 and 11-19 results in the claims “reciting” an abstract idea. The claims do not recite additional elements that integrate the exception into a practical application. the additional elements do not amount to an inventive concept (significantly more) other than the above-identified judicial exception (the abstract idea). Thus, based on the detailed analysis above, claims 1-20 are not patent eligible.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticiapted by Kuzma et al. (US 2017/0068995)
Claim 1, 10 and 20: Kuzma discloses a system for smart programmatic advertisement scheduling on a plurality of digital screens of a digital signage network, the system comprising:
a processor; ([0015], processor) and
a memory communicatively coupled to the processor, wherein the memory stores processor-executable instructions, which, on execution, causes the processor to:
obtain one or more attributes associated with each of the plurality of digital screens; ([0023] discloses sign location and deviceID for the digital sign)
receive scheduling data associated with one or more advertisements; ([0048], he advertisements repository 125, includes the date and time a particular digital advertisement was scheduled for display on the digital sign, as well a devicelD or alternatively a displayID that indicates a location at which the ad was scheduled to be displayed, and a duration or length of the digital advertisement)
generate a proof of performance report associated with the one or more advertisements;([0016], AVA data can be correlated with “proof-of-play” data, that is data relating to what, where, and when an ad was displayed on the digital sign, to determine content-specific viewership metrics by demographics and time of day.)
generate advertisement contextual schedule data associated with the one or more advertisements for the plurality of digital screens of the digital signage network based on advertisement product taxonomy, the performance report, the one or more attributes, and the scheduling data;([0024] generates at 220 trained advertising models which according to an embodiment of the invention are used to predict suitable advertising categories as well as future viewer types based on previous viewer types (“passer pattern types”). Once a trained advertising model 115 is generated it is transmitted by the data mining module and received and stored by the content management system (CMS) 120 where along with advertising data, a customized advertising list is generated and stored at 225. (Indeed, the CMS stores all trained advertising models, advertisement lists, advertiser preferences, and advertising data.) CMS 120 transmits the customized advertising list at 140 to digital sign 105 for display. Thus the trained models are the contextual data that weighs performance results, viewer attributes, and scheduling history to influence future selections) and
provide the one or more advertisements to the plurality of digital screens of the digital signage network based on the contextual advertisement schedule data. ([0054-0056], CMS 120 transfers the ad list at 140 to the digital sign module 105. And Scheduler module 525 contains following three sub modules, an online sub-module that selects an advertisement based on a probability distribution and associates it with an actual advertisement that is then scheduled and sent to display at 545, an offline sub-module that selects an advertisement from a default play list based on the scheduling time and associates it with an actual advertisement that is then scheduled and sent to display at 545, and a preference sub-module that checks for an advertiser preference and schedules an advertiser preferred advertisement for display )
Claim 2 and 11: Kuzma discloses the system as claimed in claim 1, wherein the one or more attributes comprise a screen identifier, a screen size, a resolution, an orientation, a location, and a position associated with each of the plurality of digital screens. [0023]
Claim 3, 12. Kuzma discloses the e system as claimed in claim 1, wherein the processor is further configured to:
store the one or more attributes associated with each of the plurality of digital screens of the digital signage network in a database; [0021 and 0022]
recommend one or more alterations to the advertisement contextual schedule data based on a historical data of the proof of performance report using at least one of: a first prediction model and a second prediction model, wherein the historical data is indicative of a schedule of the one or more advertisements displayed on the plurality of digital screens across one or more time durations at one or more time instants;[0056]
determine a necessity to recommend the one or more alterations to the advertisement contextual schedule data based on the historical data of the proof of performance report using the first prediction model;[0016]
predict the advertisement product taxonomy and the one or more advertisement provider for each of the plurality of digital screens using the second prediction model, wherein the one or more alterations comprise an increase in a time duration of the one or more advertisements, decrease in the time duration of the one or more advertisements, a change in time instant for displaying the one or more advertisements, a change in the one or more advertisement provider, and a frequency associated with the displaying of the one or more advertisements;[0050] and
update the advertisement contextual schedule data based on the recommended one or more alterations. [0054-0056],
Claim 4, 13: Kuzma discloses the system as claimed in claim 1, wherein the advertisement contextual schedule data comprises advertisement product taxonomy, one or more advertisement provider for each of the plurality of digital screens, a corresponding advertisement time duration for the one or more advertisement provider, and a time instant for displaying the one or more advertisements. [0016]
Claim 5, 14: Kuzma discloses the system as claimed in claim 1, wherein the processor is further configured to: segment and label the audience data based on demographic information of target audience; [0023]and
prepare an audience taxonomy corresponding to each of the plurality of digital screens based on the segmented and labelled audience data. [0040 and 0043]
Claims 6, 15: Kuzma discloses the system as claimed in claim 1, wherein the processor is further configured to:
generate the proof of performance report associated with each of the one or more advertisements for each of the advertisement provider based on one or more metrics of advertisement delivery from the one or more advertisement providers for the one or more advertisements, advertisement playback on the plurality of digital screens, and advertisement performance against the displaying of the one or more advertisements on the plurality of digital screens of the digital signage network; [0020 – 0023]and
generate one or more rules for prioritizing the one or more advertisement providers based on a user input and a plurality of factors being indicative of maximization of Return on
Investment (RoI) for the one or more advertisement providers and owners associated with each of the plurality of digital screens. [0014, 0016]
Claim 7, 16: Kuzma discloses the The system as claimed in claim 6, wherein the user input comprises a priority associated with each of the one or more advertisement providers, and a price for display of each of the one or more advertisements for a time duration, wherein the plurality of factors comprises a priority assigned to the one or more advertisement providers, a historical price paid by each of the one or more advertisement providers for each time instant, a time duration of the one or more advertisements, contextual relevance to location of each of the plurality of digital screens. [0023]
Claim 8, 17: Kuzma discloses the system as claimed in claim 1, wherein the processor is further configured to:
select at least one of a set of advertisement providers from the one or more advertisement providers, a type of advertisement for at least one of the plurality of digital screens of a digital signage network, a time duration, and a time instant for displaying the one or more advertisements; [0056]
determine a relevance of the scheduling data based on the generated advertisement contextual schedule data, and wherein the scheduling data comprises a time duration, a time instant, date of advertising, and a week of advertising;[0046]
transmit interaction data associated with an activity of one or more target audiences on each of the plurality of digital screens to the one or more advertisement provider; [0016, 0039, and 0040]and
analyze the interaction data to update the advertisement contextual schedule data, wherein the interaction data being captured using at least one of computer vision & Artificial Intelligence (AI) techniques, wherein the interaction data comprises number of viewers in front of the plurality of digital screens, viewers looked at the plurality of digital screens screen at least once, a sum of the watching time of all the watchers, an average dwelling time of all viewers, an attraction ratio, a gender split, and an age split.[0016, 0020, 0028, 0030, 0034]
Claim 9, 19:Kuzma discloses the system as claimed in claim 1, wherein the processor is further configured to display the one or more advertisements on the plurality of digital screens of the digital signage network.[0015]
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Publicover et al. (US 2022/0036405) - Targeted Content solutions can be provided using a variety of techniques. Targeted Content can be provided in place of generic advertisements on a first device or on personal computing devices. Targeted Content can be presented during, or in place of, generic advertisements in Content (e.g., television content, streaming content, etc.). Targeted Content can include customized video content to improve a user's viewing experience and thereby provide increased revenue opportunities for advertisers and content providers. The video content and/or customized content that is provided to a user can be paused or substituted to permit customized content to be delivered to the user. The video content and/or customized content can be of sporting events, and can facilitate and improve participation in a Fantasy Sports league.
Yelisetti et al. (US 2013/0132170) - An example method is provided and includes analyzing a digital advertisement configured for display on a digital sign; identifying a tag event that includes a keyword provided in the digital advertisement; identifying a time interval associated with the tag event; and recording the tag event and the time interval in a log. In more specific embodiments, the tag event further comprises an identification of a speaker in the digital advertisement. The digital advertisement can be identified by a token that may be associated with a hash having a time derived attribute.
Tian et al. (US 2017/0091822) - Described herein is an electronic digital display screen having a content scheduler operable via a cloud based Content Management System (CMS) including related systems, methods, and apparatuses for implementing the same. In accordance with a particular embodiment there is an electronic digital display screen having a scheduler to receive advertiser preferences and a default playlist from a content management system, in which the scheduler is to display multimedia content during a plurality of time slots according to the default playlist when viewership information is not available. The electronic digital display screen further includes sensors to capture video analytic data for analysis by analyzing pixels of the video analytic data captured to detect a number of viewers and to determine demographic characteristics for viewers detected; and further wherein the scheduler is to select and display multimedia content via the electronic digital display screen in at least one of the plurality of time slots different than the default play list based on the number of viewers detected and the demographics characteristics for the number of viewers detected according to the one or more advertiser preferences when the viewers are detected at the electronic digital display screen.
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Any inquiry concerning this communication or earlier communications from the examiner should be directed to DARNELL A POUNCIL whose telephone number is (571)270-3509. The examiner can normally be reached Monday - Friday 10:00 - 6:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ilana Spar can be reached at (571) 270-7537. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/D.A.P/Examiner, Art Unit 3622
/ILANA L SPAR/Supervisory Patent Examiner, Art Unit 3622