AU2020395606A1

AU2020395606A1 - Systems and methods for analysing media in real-time

Info

Publication number: AU2020395606A1
Application number: AU2020395606A
Authority: AU
Inventors: Shaun Lohman
Original assignee: Adgile Media Pty Ltd
Current assignee: Adgile Media Pty Ltd
Priority date: 2019-12-03
Filing date: 2020-04-01
Publication date: 2022-06-16
Also published as: WO2021108831A1

Abstract

Embodiments of the present disclosure provides a media analysing system for analysing a media from media streaming devices. The system includes a media content processing system configured to: monitor media content comprising advertisement streaming on a media streaming device; extract the advertisement from the media content by differentiating between the advertisement and other media content in real-time; identify the advertisement when the at advertisement is aired first time, wherein a signature is created for the advertisement for accurately identifying the advertisement; and analyse the media content comprising at least one of images, subtitles, audio, and electronic program guide in real-time to determine information about the advertisement by using an automated logic and machine learning. The system also includes a metrics determining system for determining metrics about at least one of the media content and advertisement based on the analysis of the media content and advertisement.

Description

SYSTEMS AND METHODS FOR ANALYSING MEDIA IN REAL-TIME

TECHNICAL FIELD

[0001] The presently disclosed subject matter generally relates to the field of data analytics. Particularly, the present subject matter relates to systems and methods for automatically analysing media content streaming on a media streaming device, such as media content streaming on a television, in real time.

BACKGROUND

[0002] Any references to methods, apparatus or documents of the prior art are not to be taken as constituting any evidence or admission that they formed, or form part of the common general knowledge.

[0003] With the emergence of the Internet and hundreds of channels on television, there had been an overflow of media platforms from where people can gather information about almost everything. These days customers do offline and online research to gather information through different media platforms like websites, review portals, social media platforms, television, etc. about products and/or services before making decisions about any purchase of the product like a car, a home, a mobile phone, etc. or a service like a hotel booking. Further, the companies also collect and analyse data from these media platforms to make strategic decision about their business, for promotional optimization, calculating return of investment (like sales resulted based on marketing), cross platform analytics, emerging distribution, advertising optimization of spends, and for determining other valuable insights. The media data generated and collected from the media platforms is huge. Hence analysing the data for deriving various information may require a number of resources like people, computers, etc. and hence may prove to be a time-consuming task.

[0004] An existing system for media analysis receives data from TV Stations directly. Another media analysis system tracks, categorises and makes advert creative available i.e. the system is able to identify brands and what is being advertised from the advertisements. However, these systems rely on a manual method of analysing advertisements on television meaning they are cost inefficient and can take multiple days to process data and produce reports. They are also limited to major broadcast channels (Capital Cities) as it is not cost effective to manually log all channels. [0005] Further, existing knowledge (including Google’s published material) relies on repetition to identify adverts (or advertisements). This differs significantly in that an advert would need to appear multiple times before the advert can be identified.

[0006] Existing media analysing methods or video/image matching are either too low resolution that may not identify small variations in an advert for instance, price differences per state. Other media analysing methods are too high resolution that may be too slow to apply to real time video streams. Further, existing media analysis techniques require manual input or intervention and cannot be performed in real-time.

[0007] In light of above, there exists a need for improved techniques for analysing media. It is an object of the present invention to overcome or ameliorate the above discussed disadvantages of the prior art, or at least offer a useful alternative.

SUMMARY

[0008] To overcome the above-mentioned limitations and problems, the present disclosure provides media analysing systems and methods for automatically analysing media content including digital media content streaming on a number of media streaming devices in real-time. A media analysing system automates the analytics of advertisements within the media, such as on television, websites, etc. in real-time. The system is configured to identify and analyse advertisements on television (TV) and/or websites in real-time and may also recognise a new advertisement (or advert) the first time it is aired. The system may not require any manual input for analysing the media. The system is further configured to automatically analyse media through the development of intelligent, and analytical logic. The system is furthermore configured to build signatures of data for particular advertisements and then recognise these advertisements in real time within a logging system. In some embodiments, the system logs high resolution signatures of advertisements in the logging system and then recognises to develop patterns.

[0009] Further, the system analyses all available channels of television optimally in a broadcast region. Further, the system may categorise and make creative available. It means the system is configured to identify brands and what is being advertised from the advertisements. The system is also configured to differentiate between a TV program content (or actual website content) and advertisements. And may recognise advertisers, brands and products from the advertisements. The system may include multiple computing devices such as, but not limited to, a computer configured to operate independently, yet grow and share learning organically with other computers (or computing devices located in all corners of the country or world in real-time. The system analyses and generates insights from media data in near real-time (2-10 second delay) or real time enabling clients like companies to act on competitor activity, analyse competitor movements, and/or customers’ behaviour. The system is adapted to cope with different broadcast resolutions, transmission noise, and multiple broadcast systems and signal encoding methods. The system may inform clients whilst a campaign is live, to enable the clients to respond proactively.

[0010] An embodiment of the present disclosure provides a media analysing system for analysing a plurality of media from a plurality of media streaming devices. The media analysing system includes a media content processing system connected to at least one media streaming device, configured to: monitor media content streaming on the at least one media streaming device, wherein the media content comprises at least one advertisement; extract the at least one advertisement from the media content by differentiating between the at least one advertisement and other media content in real-time; identify the at least one advertisement when the at least one advertisement is aired first time, wherein a signature is created for the at least one advertisement for accurately identifying the advertisement; and analyse the media content comprising at least one of the images, subtitles, audio, and electronic program guide in real-time to determine specific information about the at least one advertisement by using at least one of an automated logic and machine learning. The media analysing system also includes a metrics determining system configured to determine a plurality of metrics about at least one of the media content and the at least one advertisement based on the analysis of the media content and the at least one advertisement.

[0011] According to an aspect of the present disclosure, the media analysing system also includes a linking system configured to link any advertiser’s product database to an organic product list, wherein the linking system interfaces with a third-party system and passes multiple complex instructions; and a database configured to store one or more analysed media content, brands information, and signatures of a plurality of advertisements.

[0012] Another embodiment of the present disclosure provides a media analysing system for analysing a plurality of media from a plurality of media streaming devices. The media analysing system includes a media capturing system configured to interface with at least one media streaming device for monitoring media content streaming on the at least one media streaming device; and recording and extracting the media content comprising at least one advertisement from a broadcast signal by differentiating between the at least one advertisement and other media content in real time. The media analysing system also includes a media content processing system configured to identify the at least one advertisement when the at least one advertisement is aired first time, wherein a signature is created for the at least one advertisement for accurately identifying the advertisement. The media content processing system is also configured to analyse the media content by identifying and extracting at least one of images, subtitles, audio, and electronic program guide in real-time to determine specific information about the at least one advertisement and the media content by using at least one of an automated logic and machine learning. The media analysing system also includes a metrics determining system configured to determine a plurality of metrics about the at least one of the media content and the at least one advertisement based on the analysis of the media content and the at least one advertisement.

[0013] According to an aspect of the present disclosure, the media analysing system may also include a linking system configured to link any advertiser’s product database to an organic product list. The linking system may interface with a third-party system and may pass multiple complex instructions. Further, the media analysing system may include a database configured to store one or more analysed media content, the plurality of metrics, brand information, signatures of a plurality of advertisements.

[0014] The media content processing system may also be configured to process the media content prior to storing in the database, wherein the processing the media content may include at least one of encoding the media content, trimming, re-sizing the media content, and standardizing the encoding by standardizing the media content from at least one of a high definition and standard definition to one standard output.

[0015] The specific information may include at least one of one or more products and brand being promoted in the at least one advertisement, one or more key indicators for best brand marketing, and a marketing intent of the advertisement comprising a strategic objective and a tactic employed to achieve the objective.

[0016] The media content processing system may also be configured to

[0017] The media content processing system may also be configured to simultaneously cross- reference search engine optimization (SEO) keywords against the subtitles identified and extracted from the media content in real-time; and search for text in the identified at least one advertisement. [0018] The plurality of metrics may include potential audience for the media content, a number count of consumers watching the media content at a particular time, sales, website visits, leads, quotes, and a time at which the media content is being watched.

[0019] In some embodiments the media capturing system may further be configured to stream media content of the at least one media streaming device at least five times more efficiently with increased robustness, higher quality, and no bandwidth restriction.

[0020] Another embodiment of the present disclosure provides a method for analysing a plurality of media from a plurality of media streaming devices. The method includes monitoring, by a media capturing system, media content streaming on the at least one media streaming device; recording and extracting, by the media capturing system, the media content including at least one advertisement from a broadcast signal by differentiating between the at least one advertisement and other media content in real-time; identifying by a media content processing system, the at least one advertisement when the at least one advertisement is aired first time, wherein a signature is created for the at least one advertisement for accurately identifies the advertisement; segmenting, by the media content processing system, the media content and extract at least one of images, subtitles, audio, and electronic program guide from the media content in real-time; analysing, by the media content processing system, the at least one of the images, subtitles, audio, and electronic program guide in real-time to determine specific information about the at least one advertisement and the media content by using automated logic and machine learning; and determining, by a metrics determining system, a plurality of metrics based on the analysis of the media content and the at least one advertisement.

[0021] The method may also include linking, by a linking system, an advertiser’s product database to an organic product list, wherein the linking system is configured to interface with a third-party system and pass multiple complex instructions; and storing, in a database, one or more analysed media content, metrics, brand information, and signatures of a plurality of advertisements.

[0022] The method may include simultaneously cross-referencing search engine optimization (SEO) keywords against the extracted subtitles in real-time; and searching text in the at least one advertisement.

[0023] The method may also include processing, by the media content processing system, the media content prior to storing in the database, wherein the processing the media content comprises at least one of encoding the media content, trimming, re-sizing the media content, and standardizing the encoding by standardizing the media content from at least one of a high definition and standard definition to one standard output. In some embodiments, the specific information comprising at least one of one or more products and a brand being promoted in the at least one advertisement, one or more key indicators for best brand marketing, and a marketing intent of the advertisement comprising a strategic objective and a tactic employed to achieve the objective. [0024] The method may also include simultaneously cross-referencing, by the media content processing system, search engine optimization (SEO) keywords against the subtitles extracted from the media content in real-time; and searching, by the media content processing system, for text in the identified at least one advertisement.

[0025] The method may also include streaming, by the media capturing system, media content of the at least one media streaming device at least five times more efficiently with increased robustness, higher quality, and no bandwidth restriction.

[0026] Another embodiment of the present disclosure provides a media analysing and optimizing system for analysing and optimizing digital media in real-time. The system includes a media capturing system configured to interface with at least one media streaming device for: continuously monitoring media content streaming on the at least one media streaming device in real-time; and recording and extracting the media content comprising at least one advertisement from a broadcast signal by differentiating between the at least one advertisement and other media content in real time. The system also includes a media content processing system configured to: identify the at least one advertisement when the at least one advertisement is aired first time, wherein a signature is created for the at least one advertisement for accurately identifying the advertisement; segment the media content to extract at least one of images, subtitles, audio, and electronic program guide from the media content in real-time; and analyse the at least one of the images, subtitles, audio, and electronic program guide in real-time to determine specific information about the at least one advertisement and the media content by using at least one of an automated logic and machine learning. The system also includes digital media optimizing system configured to: calculate at least one of an interest and an intent of a plurality of consumers based on the analysis of the media content; capture and analyse web traffic generated because of the at least one advertisement in real-time; automatically search a plurality of webpages to identify new dynamic content correlated with the at least one advertisement; and correlate the at least one advertisement with sales data of one or more products promoted in the at least one advertisement based on one or more factor. The system also includes a metrics determining system configured to determine a plurality of metrics based on the analysis and correlation; and observe and measure a number of consumers visiting a website of an advertiser of the at least one advertisement based on at least one of the at least one advertisement or an advertisement of a competitor of the advertiser.

[0027] The media analysing and optimizing system may also include a multi-rule based structural hierarchical linking system configured to link any advertiser’s product database to an organic product list, wherein the multi-rule based structural hierarchical linking system interfaces with a third-party system and passes multiple complex instructions.

[0028] Further, the media analysing and optimizing system may also include a database configured to store one or more analysed media content, websites data, the plurality of metrics, and signatures of a plurality of advertisements.

[0029] According to an aspect of the present disclosure, the media content processing system is further configured to process the media content prior to storing in the database, wherein the processing the media content comprising at least one of encoding the media content, trimming, re sizing the media content, and standardizing the encoding by standardizing the media content from at least one of a high definition and standard definition to one standard output.

The digital media optimization system may also be configured to: determine an accuracy and reliability of the plurality of metrics based on one or more variables; determine a varying degree of engagement of the plurality of consumers with the media streaming device based on at least one of a demography, media content dynamics; determine a website engagement pattern to assist in transforming website interactions into usable metrics; receive data comprising sales data, footfall data from a plurality of third-party devices; and analyse the received data based on the analysed media content comprising the at least one advertisement.

[0030] Yet another embodiment of the present disclosure provides a method for analysing and optimizing digital media in real-time. The method includes: continuously monitoring, by a media capturing system, media content streaming on the at least one media streaming device in real-time; recording and extracting, by the media capturing system, the media content comprising at least one advertisement from a broadcast signal by differentiating between the at least one advertisement and other media content in real-time; identifying, by a media content processing system, the at least one advertisement when the at least one advertisement is aired first time, wherein a signature is created for the at least one advertisement for accurately identifying the advertisement; segmenting, by the media content processing system, the media content to extract at least one of images, subtitles, audio, and electronic program guide from the media content in real-time; analysing, by the media content processing system, the at least one of the images, subtitles, audio, and electronic program guide in real-time to determine specific information about the at least one advertisement and the media content by using automated logic and machine learning; calculating, by a digital media optimizing system, at least one of an interest and an intent of a plurality of consumers based on the analysis of the at least one advertisement; capturing and analysing, by the digital media optimizing system, web traffic generated because of the at least one advertisement; automatically searching, by the digital media optimizing system, a plurality of webpages to identify new dynamic content, wherein the new dynamic content is correlated with the at least one advertisement; correlating, by the digital media optimizing system, the at least one advertisement with sales data of one or more products promoted in the at least one advertisement based on one or more factor; determining, by a metrics determining system, a plurality of metrics based on the analysis and correlation; and observing and measuring, by the metrics determining system, a number of consumers visiting a website of an advertiser of the at least one advertisement based on at least one of the at least one advertisement or an advertisement of a competitor of the advertiser. [0031] The method may further include linking, by a multi-rule based structural hierarchical linking system, any advertiser’s product database to an organic product list; and storing, in a database, one or more analysed media content, websites data, metrics, and signatures of a plurality of advertisements.

[0032] The method may also include processing, by the media content processing system, the media content prior to storing on the database, wherein the processing the media content comprising at least one of encoding the media content, trimming, re-sizing the media content, and standardizing the encoding by standardizing the media content from at least one of a high definition and standard definition to one standard output.

[0033] The specific information may include at least one of a brand and one or more products being promoted in the at least one advertisements, one or more key indicators for best brand marketing, and a marketing intent of the advertisement comprising a strategic objective and a tactic employed to achieve the objective, wherein the plurality of metrics comprising potential audience for the media content, a number count of consumers watching the media content at a particular time, sales, website visits, leads, quotes, and a time at which the media content is being watched. [0034] The method may also include simultaneously cross-referencing, by the media content processing system, search engine optimization (SEO) keywords against the extracted subtitles in real-time; and searching, by the media content processing system, for text in the identified at least one advertisement.

[0035] The method may also include determining, by the digital media optimization system, an accuracy and reliability of the plurality of metrics based on one or more variables; determining, by the digital media optimization system, a varying degree of engagement of the plurality of consumers with the media streaming device based on at least one of a demography, media content dynamics; determining, by the digital media optimization system, a website engagement pattern to assist in transforming website interactions into usable metrics; receiving, by the digital media optimization system, data comprising sales data, footfall data from a plurality of third-party devices; and analysing, by the digital media optimization system, the received data based on the analysed media content comprising the at least one advertisement.

[0036] Other and further aspects and features of the disclosure will be evident from reading the following detailed description of the embodiments, which are intended to illustrate, not limit, the present disclosure.

DETAILED DESCRIPTION

[0037] The following detailed description is made with reference to the figures. Exemplary embodiments are described to illustrate the disclosure, not to limit its scope, which is defined by the claims. Those of ordinary skill in the art will recognize a number of equivalent variations in the description that follows.

[0038] The functional units described in this specification have been labeled as a system, device or module. A system, device or module may be implemented in programmable hardware devices such as processors, digital signal processors, central processing units, field programmable gate arrays, programmable array logic, programmable logic devices, cloud processing systems, or the like. The devices/modules may also be implemented in software for execution by various types of processors. An identified device may include executable code and may, for instance, comprise one or more physical or logical blocks of computer instructions, which may, for instance, be organized as an object, procedure, function, or other construct. Nevertheless, the executable of an identified device need not be physically located together, but may comprise disparate instructions stored in different locations which, when joined logically together, comprise the device and achieve the stated purpose of the device.

[0039] Indeed, an executable code of a device or module could be a single instruction, or multiple instructions, and may even be distributed over several different code segments, among different applications, and across several memory devices. Similarly, operational data may be identified and illustrated herein within the device, and may be embodied in any suitable form and organized within any suitable type of data structure. The operational data may be collected as a single data set, or may be distributed over different locations including over different storage devices, and may exist, at least partially, as electronic signals on a system or network.

[0040] Reference throughout this specification to “a select embodiment,” “one embodiment,” or “an embodiment” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the disclosed subject matter. Thus, appearances of the phrases “a select embodiment,” “in one embodiment,” or “in an embodiment” in various places throughout this specification are not necessarily referring to the same embodiment.

[0041] Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided, to provide a thorough understanding of embodiments of the disclosed subject matter. One skilled in the relevant art will recognize, however, that the disclosed subject matter can be practiced without one or more of the specific details, or with other methods, components, materials, etc. In other instances, well-known structures, materials, or operations are not shown or described in detail to avoid obscuring aspects of the disclosed subject matter.

[0042] In accordance with the exemplary embodiments, the disclosed computer programs or modules can be executed in many exemplary ways, such as an application that is resident in the memory of a device or as a hosted application that is being executed on a server and communicating with the device application or browser via a number of standard protocols, such as TCP/IP, HTTP, XML, SOAP, REST, JSON, and other sufficient protocols. The disclosed computer programs can be written in exemplary programming languages that execute from memory on the device or from a hosted server, such as BASIC, COBOL, C, C++, Java, Pascal, or scripting languages such as JavaScript, Python, Ruby, PHP, Perl or other existing or future developed programming languages.

[0043] Some of the disclosed embodiments include or otherwise involve data transfer over a network, such as communicating various inputs or files over the network. The network may include, for example, one or more of the Internet, a personal area network (PAN), a storage area network (SAN), a home area network (HAN), a campus area network (CAN), a local area network (LAN), a wide area network (WAN), a metropolitan area network (MAN), a virtual private network (VPN), an enterprise private network (EPN), Internet, a global area network (GAN), Wide Area Networks (WANs), Local Area Networks (LANs), analog or digital wired and wireless telephone networks (e.g., a PSTN, Integrated Services Digital Network (ISDN), a cellular network, and Digital Subscriber Line (xDSL)), cellular telephone network, radio, television, cable, satellite, and/or any other delivery or tunneling mechanism for carrying data. The network may include multiple networks or sub networks, each of which may include, for example, a wired or wireless data pathway. The network may include a circuit-switched voice network, a packet- switched data network, or any other network able to carry electronic communications. For example, the network may include networks based on the Internet protocol (IP) or asynchronous transfer mode (ATM), and may support voice using, for example, VoIP, Voice-over- ATM, or other comparable protocols used for voice data communications.

[0044] The illustrated embodiments of the disclosed subject matter will be best understood by reference to the drawings, wherein like parts are designated by like numerals throughout. The following description is intended only by way of example, and simply illustrates certain selected embodiments of devices, systems, and processes that are consistent with the disclosed subject matter as claimed herein.

[0045] Figure 1A is a schematic diagram illustrating an exemplary environment, where various embodiments of the present disclosure may function;

[0046] Figure IB is a schematic diagram illustrating another exemplary environment, where various embodiments of the present disclosure may function;

[0047] Figure 2 is a block diagram illustrating various system elements of an exemplary media analysing system, in accordance with an embodiment of the present disclosure;

[0048] Figures 3A-3B depicts a flowchart diagram illustrating a method for analysing media content, in accordance with an embodiment of the present disclosure; [0049] Figure 4 is a schematic diagram illustrating another exemplary environment including an exemplary media analysing and optimizing system, in accordance with an embodiment of the present disclosure;

[0050] Figure 5 is a block diagram illustrating various system elements of an exemplary media analysing and optimizing system, in accordance with an embodiment of the present disclosure; and

[0051] Figures 6A-6C depicts a flowchart diagram illustrating a method for analysing and optimizing media content, in accordance with an embodiment of the present disclosure.

[0052] As used herein, the term “media analysing system” refers to a system including a device or a set of multiple devices configured to analyse the media content streaming on the media streaming devices. The media content may include advertisements, television shows, website data, music videos, and so forth.

[0053] As used herein, the term “media streaming device” may refer to a suitable device configured to play or stream media content like shows, concerts, advertisements, blogs, videos, audios, and so forth. Examples of the media streaming devices may include such as, but not limited to, televisions, computers, mobile phones, laptops, smart phones, fitness trackers, smart watches, smart televisions, and so forth.

[0054] As used herein, the term “consumer may refer to a user or buyer of a product or a service being advertised in an advertisement.

[0055] Further, as used herein, the term “advertiser” may refer to a person or a company promoting at least one product via the advertisements on the media streaming devices.

[0056] As used herein, the term “media capturing system” refers to a system including a single device or a combination of multiple devices each comprising hardware, software, firmware, and combination of these. The media capturing system may be configured to interface with a media streaming device and stream the media content faster and efficiently.

[0057] As used herein, the term “media content processing system” refers to a system including a single device or a combination of multiple devices each comprising hardware, software, firmware, and combination of these. The media content processing system is configured to process and/or analyse media content to derive one or more insights and information.

[0058] As used herein, the term “digital media optimizing system” refers to a system including a single device or a combination of multiple devices each comprising hardware, software, firmware, and combination of these. The digital media optimizing system is configured to determine web traffic in relation to the advertisement and/or media content; and receive and process data like sales data etc. from third party system or device. Further, the digital media optimizing system may optimize the digital media based on the analysis of the media content. [0059] As used herein, the term “linking system” or a “multi-rule based structured hierarchical linking system” may refer to a single device or a combination of multiple devices each comprising hardware, software, firmware, and combination of these. The linking system interfaces with a third-party system and passes multiple complex instructions. The linking system configured to link any advertiser’s product database to an organic product list. Throughout the description, the terms linking system and multi-rule based structured hierarchical linking system are used interchangeably without change in its meaning.

[0060] As used herein, the term “metrics determining system” refers to a system including a single device or a combination of multiple devices each comprising hardware, software, firmware, and combination of these. The metrics determining system determines a plurality of metrics about at least one of media content and an advertisement based on the analysis and correlation.

[0061] Figure 1A is a schematic diagram illustrating an exemplary environment 100A, where various embodiments of the present disclosure may function. As shown, the environment 100A includes a media streaming device 102 configured to stream media content. The non-limiting examples of the media streaming device 102 includes a television, a laptop, a computer, a tablet computer, a smart television (TV), a smart watch, a fitness tracker, a smart phone, and so forth. The media content may include live concerts, advertisements, promotional event audio/video clips, shows, and so forth. In some embodiments, the media content may include digital media content. [0062] Further the environment 100 A includes a media analysing system 104 (hereinafter may be referred as system 104) connected to the media streaming device 102. Further the media analysing system 104 may be connected to the media streaming device 102 via a wired or a wireless means. In some embodiments, the system 104 is further configured to stream media content of the media streaming device 102 at least five times more efficiently with increased robustness, higher quality, and no bandwidth restriction. The media analysing system 104 is configured to continuously monitor, extract, and analyse the media content streaming on the media streaming device 102. Based on the analysis, the media analysing system 104 may derive some useful insights about the media content. The system 104 may be configured to identify and analyse advertisements on the device 102 e.g. a television, in real-time or near real-time. Further, the system 104 identifies the advertisements they are aired for the first time and creates a signature automatically for the advertisements. In some embodiments, the system 104 builds signatures of media content for particular advertisements and then recognizes these advertisements in real-time within a logging system. The system 104 may analyse all available channels of the television (i.e. the device 102) optimally in real-time. Further, the system 104 can categorize the advertisements and make creative available. It means the system 104 is able to identify brands and what is being advertised. The system 104 may also be configured to differentiate between the advertisements and rest of the media content like TV program content. The system 104 may also recognize advertisements, advertisers of the advertisements, and brands and products promoted in the advertisements.

[0063] The system 104 may be configured to process the volume of data generated by the monitoring of multiple, such as more than 200, broadcast channels on the media streaming device 102.

[0064] The system 104 is configured to calculate metrics and performance indicators leveraging the data being generated by the analysis of the media content. Further, the system 104 may capture signals (like broadcast signal) from the media streaming device 102 to calculate an interest and an intent of consumers based on advertisements analysis. The consumers may be people watching the media content streaming on the media streaming device or may be people buying or using the one or more products or services promoted in the advertisements.

[0065] The environment 100A also includes a central database 106. The system 104 may store data or analysed media content on the central database 106. Further, the system 104 may process the analysed media content like encrypting, segmenting the data prior to storing on the central database 106. The system 104 may update the central database 106 in real-time.

[0066] The system 104 may communicate with other media analysing systems 108 as shown in environment 100B of Figure IB. In some embodiments, the system 104 may communicate with other systems 108 via a network. The media streaming device 104 and the systems 108 may include a storage device configured to store analysed media content, and signatures of the advertisements. Further, the media streaming device 104 and the systems 108 may operate independently, yet grow and share learning organically with each other in real-time. [0067] The media analysing systems 104 and 108 are configured to calculate metrics and performance indicators leveraging the data being generated by the analysis of the media content. The non-limiting examples of the metrics may include web visits, leads, quotes, sales and so forth. Further, the system 104 may measure effectiveness of the advertisement over time and also may measure immediate impact of the advertisement. For example, the system 104 can measure and track real-time performance on web-visits and sales to understand immediate response/impact. Similarly, the system 104 can determine longer time impact like “Is there an evidence that advertising is growing a brand over time?”.

[0068] In some embodiments, the system 104 is configured to monitor media content stream on at least one media streaming device i.e. the media streaming device 102. The system 104 may record and extract the media content comprising at least one advertisement from a broadcast signal by differentiating between the at least one advertisement and other media content in real-time. The system 104 may identify the at least one advertisement when the at least one advertisement is aired first time. The system 104 may create a signature for the at least one advertisement for accurately identifying the advertisement when it is aired for the first time. The system 104 may segment the media content and extract at least one of images, subtitles, audio, and electronic program guide from the media content in real-time. The system 104 may also analyse the at least one of the images, subtitles, audio, and electronic program guide in real-time to determine specific information about the at least one advertisement and the media content by using automated logic and machine learning. The non-limiting examples of the specific information may include at least one of one or more products and brand(s) being promoted in the at least one advertisement, one or more key indicators for best brand marketing, and a marketing intent of the advertisement comprising a strategic objective and a tactic employed to achieve the objective. The system 104 may also determine a plurality of metrics about at least one of the media content and the at least one advertisement based on the analysis. Examples of the plurality of metrics may include, but are not limited to, potential audience for the media content, a number count of consumers watching the media content at a particular time, sales, website visits, leads, quotes, and a time at which the media content is being watched.

[0069] The system 104 may also link any advertiser’s product database to an organic product list, wherein the linking system may interface with a third-party system and passes multiple complex instructions. The system 104 may store one or more analysed media content, metrics, and signatures of a plurality of advertisements in a database. The database may be at least one of a local storage device, a local database, or the central database 106. The central database 106 may be located in a cloud or in a network device like a server. The system 104 is further configured to process the media content prior to storing in the database. In some embodiments, the processing of the media content may include such as, but not limited to, encoding the media content, trimming, re-sizing the media content, and standardizing the encoding by standardizing the media content from at least one of a high definition and standard definition to one standard output.

[0070] Figure 2 is a block diagram 200 illustrating various system elements of an exemplary media analysing system 202, in accordance with an embodiment of the present disclosure. As shown, the system 202 includes a media capturing system 204, a media content processing system 206, a linking system 208, a metrics determining system 210, and a database 212.

[0071] The media capturing system 204 may interface with at least one media streaming device such as, a television for monitoring media content streaming on the at least one media streaming device; and recording and extracting the media content including at least one advertisement from a broadcast signal by differentiating between the at least one advertisement and other media content in real-time. In some embodiments, the media capturing system 204 is further configured to stream media content of the at least one media streaming device at least five times more efficiently with increased robustness, higher quality, and no bandwidth restriction.

[0072] The media content processing system 206 is configured to identify the at least one advertisement when the at least one advertisement is aired first time, and creates a signature for the at least one advertisement for accurately identifying the advertisement. In some embodiments, the media content processing system 206 may create a high-resolution signature of data for the at least one advertisement, and then may use the same to cross reference and recognize the at least one advertisement promptly within a real-time logging system. In some embodiments, the media content processing system 206 may create a reliable signature for the advertisement that may accurately identify the advertisement by ignoring variations in the broadcast signal strength, audio quality, and video quality for example bad signal due to weather.

[0073] The media content processing system 206 is configured to segment the media content and extract at least one of images, subtitles, audio, and electronic program guide from the media content in real-time. The media content processing system 206 is configured to analyse the at least one of the images, subtitles, audio, and electronic program guide in real-time to determine specific information about the at least one advertisement and the media content by using automated logic and machine learning. The specific information may include, but are not limited to, a brand and one or more products being promoted in the at least one advertisement, one or more key indicators for best brand marketing, and a marketing intent of the advertisement comprising a strategic objective and a tactic employed to achieve the objective. In some embodiments, the media content processing system 206 may analyse the media content by using at least one of subtitle recognition techniques, optical character recognition (OCR), image recognition, and so forth. The media content processing system 206 is configured to analyse the advertisement(s) from frame to frame of the advertisement(s).

[0074] In some embodiments, the media content processing system 206 is configured to determine patterns in the at least one advertisement. Further, the media content processing system 206 may accurately identify advertisements on the media streaming device 102. For example, the media content processing system 206 may distinguish between advertisements from a same brand for a same product or products that are different in length of airplay i.e. 15 seconds version and 30 seconds version. Further, the media content processing system 206 may identify near identical advertisements specific to particular regional centers i.e. airfare sales departing Sydney versus Melbourne.

[0075] Further, the media content processing system 206 can analyse all types of media content. For example, different formats of the media content being broadcasted on different channels in variation in standard definition to high definition, different file formats of advertisements from different studios, region specific formats of media content or advertisements being broadcast in different regions. The media content processing system 206 is configured to instantly update monitoring stations i.e. other media analysing systems 108 using minimal bandwidth.

[0076] In some embodiments, the media content processing system 206 is configured to simultaneously cross-reference search engine optimization (SEO) keywords against the extracted subtitles in real-time; and search text in the at least one advertisement. Further, the media content processing system 206 may process the images in the advertisement(s) and may determine colors and patterns in the advertisement(s) quickly like in 4-10 milliseconds. The media content processing system 206 can process high definition images and millions of pixels in the images in fraction of a second. [0077] In some embodiment, the media content processing system 206 may pre-vet incoming data of the media content to determine if it is worth running more complex signature data against it with incredible accuracy while taking into account noisy and lossy data streams.

[0078] The linking system 208 is configured to link any advertiser’s product database to an organic product list, wherein the linking system interfaces with a third-party system and passes multiple complex instructions. The linking system 208 may be a multi-rule based structured hierarchical linking system configured to tie any advertiser’s product database to an organic product list, interface with any third-party system or device, and pass multiple complex instructions.

[0079] The metrics determining system 210 is configured to determine a plurality of metrics about at least one of the media content and the at least one advertisement based on the analysis. Examples of the plurality of metrics may include, but are not limited to, potential audience for the media content, a number count of consumers watching the media content at a particular time, sales, website visits, leads, quotes, and a time at which the media content is being watched. For example, what a viewer could watch instead of the Sunday afternoon football, mentioned above. Once this was determined a number can be given to the metrics determining system 210 which is then divided by a sample universe to produce the results in real-time.

[0080] The database 212 is configured to store one or more analysed media content and signatures of a plurality of advertisements. The database 212 may be a distributed storage system for speed and performance. The media content processing system 206 is further configured to process the media content prior to storing in the database 212. The processing of the media content may include such as, but not limited to, encoding the media content, trimming, re-sizing the media content, and standardizing the encoding by standardizing the media content from at least one of a high definition and standard definition to one standard output. In some embodiments, the media content processing system 206 stores data like analysed media content or part of the analysed media content in the central database 106.

[0081] Figures 3A-3B is a flowchart diagram illustrating a method 300 for analysing media content, in accordance with an embodiment of the present disclosure. As discussed with reference to the Figure 2, the media analysing system 202 is configured to analyse media content captured and extracted from the at least one media streaming device like a media streaming device 102 of

Figures 1A-1B. [0082] At step 302, the media capturing system 204 monitors media content streaming on the media streaming device 102. The media content may include actual media content like TV show, etc. and at least one advertisement. At step 304, the media capturing system 204 records and extracts the media content including the at least one advertisement (advert) from a broadcast signal by differentiating between the at least one advert and the other actual media content i.e. The TV show content.

[0083] At step 306, the media content processing system 206 identifies the advertisement and create a signature to identify the advertisement when the advert is aired first time. For example, if an advert of a product is new and aired first time on a channel of the TV then the media content processing system 206 may identify the advert as a new advert and create a signature of the same to identify the advert. The signature of the new advert is then stored in a database like the central database 106. The central database 106 may be accessed by the other media analysing systems 108.

[0084] At step 308, the media content processing system 206 segments the media content to extract at least one of images, subtitles, audio, and electronic program guides (EPG) from the media content. At step 310, the media content processing system 206 analyses the at least one of the images, subtitles, audio, and EPG in real-time to determine specific information about the advertisement and/or the media content using automated logic (or artificial intelligence) and/or machine learning. In some embodiments, the media content processing system 206 may analyse subtitles in real-time for example by searching text, simultaneously loading and processing from the central database 106, and referencing against SEO keywords in real-time.

[0085] Thereafter at step 312, the metrics determining system 210 determines a plurality of metrics based on the analysis of the media content and/or the at least one advertisement. Examples of the metrics may include, but are not limited to, potential audience for the media content, a number count of consumers watching the media content at a particular time, sales, website visits, leads, quotes, and a time at which the media content is being watched.

[0086] The one or more analysed media content, metrics, and signatures of a plurality of advertisements may be stored in a database. The database may be at least one of a local storage device, a local database, or the central database 106. The central database 106 may be located in a cloud or in a network device. The media content processing system 206 may process the media content prior to storing in the database. In some embodiments, the processing of the media content may include at least one of encoding the media content, trimming, re-sizing the media content, and standardizing the encoding by standardizing the media content from at least one of a high definition and standard definition to one standard output.

[0087] Figure 4 is a schematic diagram illustrating another environment 400, where various embodiments of the present disclosure may function. The environment 400 primarily includes a media streaming device 402, a media analysing and optimizing system 404 (hereinafter may be referred as system 404), and a central database 406. The media streaming device 402 is configured to stream media content. Non-limiting examples of the media streaming device 102 includes a television, a laptop, a computer, a tablet computer, a smart television (TV), a smart watch, a fitness tracker, and so forth. The media content may include live concerts, advertisements, promotional event audio/video clips, shows, and so forth. In some embodiments, the media content comprises digital media content.

[0088] Further the system 404 may be connected to the media streaming device 402 via wired or wireless means. In some embodiments, the system 404 is further configured to stream media content of the media streaming device 402 at least five times more efficiently with increased robustness, higher quality, and no bandwidth restriction. The system 404 is configured to continuously monitor and analyse the media content streaming on the media streaming device 402. Based on the analysis, the system 404 may derive some useful insights about the media content. [0089] The system 404 is configured to identify and analyse advertisements on the device 402 e.g. a television, in real-time or near real-time. Further, the system 404 identifies the advertisements they are aired for the first time and creates a signature automatically for the advertisements. The system 404 builds signatures of media content for particular advertisements and then recognizes these advertisements in real-time within a logging system. The system 404 may analyse all available channels of the television (i.e. the device 402) optimally. Further, the system 404 can categorize the advertisements and make creative available. The system 404 may also differentiate between the advertisements and rest of the media content like TV program content. The system 404 may also recognize advertisements, advertisers of the advertisements, and brands and products promoted in the advertisements.

[0090] The system 404 may segment the media content to extract at least one of images, subtitles, audio, and electronic program guide from the media content in real-time; and analyse the at least one of the images, subtitles, audio, and electronic program guide in real-time to determine specific information about the at least one advertisement and the media content by using automated logic and machine learning. Examples of the specific information may include a brand and one or more products being promoted in the at least one advertisement, one or more key indicators for best brand marketing, and a marketing intent of the advertisement comprising a strategic objective and a tactic employed to achieve the objective.

[0091] The system 404 is also configured to determine a plurality of metrics about at least one of the media content and the at least one advertisement based on the analysis and correlation; and observe and measure a number of consumers visiting a website of an advertiser of the at least one advertisement based on at least one of the at least one advertisement or an advertisement of a competitor of the advertiser. In some embodiments, the system 404 is configured to calculate the plurality of metrics and performance indicators leveraging the data being generated by the analysis of the media content. Examples of the plurality of metrics includes, but are not limited to, a potential audience for the media content, a number count of consumers watching the media content at a particular time, sales, website visits, leads, quotes, and a time at which the media content is being watched.

[0092] Further, the system 404 is configured to capture signals from the media streaming device 402 to calculate an interest and an intent of consumers based on advertisements analysis. The consumers may be people watching the media content streaming on the media streaming device or may be people buying or using the one or more products or services promoted in the advertisements.

[0093] Further, the system 404 may include a digital media optimizing system (or a web analytics device) for analysing website content and web traffic. The system 404 may capture and analyse web traffic generated because of the at least one advertisement automatically search a plurality of webpages to identify new dynamic content, wherein the new dynamic content is correlated with the at least one advertisement. The system 404 may calculate at least one of an interest and an intent of a plurality of consumers based on the at least one advertisement. The system 404 is also configured to receive or capture data from third party devices such as, but not limited to, in-store Wi-Fi device, store databases, foot counters in-store, and customer relationship management systems. The data may also include store location to consumer residency, geographic location of a TV broadcast, products returns data, sales data, advertisements’ data, and so forth. Based on the received data, the system 404 can determine how the data affects a correlation of sales data to television or web advertising. The system 404 is configured to correlate the at least one advertisement with sales data of one or more products promoted in the at least one advertisement based on one or more factor. The non-limiting examples of the one or more factor may include, but are not limited to, a residency of the consumer i.e. a geographic location of the consumer, whether an advertisement has promoted multiple products, cross-selling means whether an advertisement for a similar product influences a purchase, and so forth. The system 404 is configured to determine if return of product data influences sales data and may provide accurate metrics.

[0094] The system 404 may also determine relevant dynamic content added to websites and correlate the dynamic content to the advertisements in real-time automatically. The system 404 then generates one or more metrics based on the correlation. In some embodiments, the websites of clients or companies may be crawled manually daily or at regular intervals for new content, to train the system 404 to learn what is new content i.e. search words and search terms. This new content is then correlated with the advertisements that consumers are exposed to using a hierarchical process. In some embodiments, the system 404 may also determine consumers behavior.

[0095] In some embodiments, the system 404 may include a reporting system configured to produce data based on an accuracy and reliability of the metric based on the following factors comprising when an advertisement is shown like during a live event or during a show (or TV show), a time of day the advertisement is shown, whether the advertisement is shown back to back with a competitor or by itself, and so forth.

[0096] The system 404 is configured to correlate advertisements with sales data considering following variables: residency of the consumer i.e. geographical location; whether an advertisement has promoted multiple products; cross-selling- whether an advertisement for a similar product influences a purchase.

[0097] The system 404 is an automated system configured to search webpages to identify new dynamic content and correlate the new content data to advertisements. Further, the system 404 may be configured to analyse the media content in real-time or near real time for example in less than a 20 milliseconds lag. The system 404 may also determine an accuracy and reliability of the developed metric based on the following variables such as, but not limited to: when the advertisement is shown-like during a live event or during a regular TV show; time of day/day of week the advertisement is shown; whether the advertisement is shown back to back with a competitor or by itself. The system 404 may also determine if following variables affect the correlation of TV advertisements with sales data. The variable may include residency of the consumer like geographical location of the consumer, whether an advertisement has promoted multiple products, cross selling of similar products.

[0098] In some embodiments, the system 404 is configured to simultaneously cross-reference search engine optimization (SEO) keywords against the identified and/or extracted subtitles in real-time; and search text in the at least one advertisement.

[0099] In some embodiments, the system 404 is configured to to identify and analyse advertisements via Video input (Non-Free to Air Broadcast Signals). Further, the system 404 may identify and track promoted brands featured within a single advert. For examples, in a Supermarket advert identifying products like Coca Cola, juice, Chocolate brands, and Australian Pork that are being promoted. Further, the system 404 may be configured to do real-time link up of advertisements with current events on television - e.g. an advertisement for soccer boots when a Socceroos match is on TV.

[00100] The system 404 may also monitor website users in real-time and track actions and correlate individual user activity with dual screening behavior. The system 404 may observe and measure the number of people visiting a brand’s or advertiser’s website in relationship to advertiser’s activity or advertiser’s competitor’s activity.

[00101] Figure 5 is a block diagram 500 illustrating various system elements of an exemplary media analysing and optimizing system 502, in accordance with an embodiment of the present disclosure. As shown, the media analysing and optimizing system 502 (hereinafter may be referred as system 502) includes a media capturing system 504, a media content processing system 506, a linking system 508, a metrics determining system 510, a database 512, and a digital media optimizing system 514.

[00102] The media capturing system 504 is configured to interface with at least one media streaming device such as device 402 of Figure 4. The media capturing system 504 continuously monitors media content streaming on the at least one media streaming device 504. The media capturing system 504 may record and extract the media content comprising at least one advertisement from a broadcast signal by differentiating between the at least one advertisement and other media content in real-time. [00103] The media content processing system 506 is configured to identify the at least one advertisement when the at least one advertisement is aired first time, and create a signature for the at least one advertisement for accurately identifying the advertisement. The media content processing system 506 may also segment the media content to extract at least one of images, subtitles, audio, electronic program guide, and so forth from the media content in real-time. The media content processing system 506 is also configured to analyse the at least one of the images, subtitles, audio, and electronic program guide in real-time to determine specific information about the at least one advertisement and the media content by using automated logic and machine learning. The specific information may include at least one of one or more products and brand(s) being promoted in the at least one advertisement, one or more key indicators for best brand marketing, and a marketing intent of the advertisement including a strategic objective and a tactic employed to achieve the objective.

[00104] In some embodiments, the media content processing system 506 is further configured to simultaneously cross-reference search engine optimization (SEO) keywords against the extracted subtitles in real-time; and search text in the at least one advertisement.

[00105] The digital media optimizing system 514 is configured to calculate at least one of an interest and an intent of a plurality of consumers based on the at least one advertisement (advert). The digital media optimizing system 514 captures and analyzes web traffic generated because of the at least one advert in real-time. Further, the digital media optimizing system 514 may automatically search a plurality of webpages to identify new dynamic content. The digital media optimizing system 514 then may correlate the new dynamic content with the at least one advertisement. The digital media optimizing system 514 may also correlate the at least one advertisement with sales data of one or more products promoted in the at least one advertisement based on one or more factor.

[00106] Further, the digital media optimizing system 514 is configured to determine an accuracy and reliability of the plurality of metrics based on one or more variables. Further, the digital media optimizing system 514 is configured to determine a varying degree of engagement of the plurality of consumers with the media streaming device based on at least one of a demography, media content dynamics; and determine a website engagement pattern to assist in transforming website interactions into usable metrics. In some embodiments, the digital media optimization system is configured to receive data comprising sales data, footfall data from a plurality of third-party devices and analyse the received data based on the analysed media content comprising the at least one advertisement. The third-party devices may include sale stores, WIFI of sale stores, foot counters of sale stores, and so forth.

[00107] The metrics determining system 510 may determine a plurality of metrics about at least one of the media content and the at least one advertisement based on the analysis and correlation. Further, the metrics determining system 510 may observe and measure a number of consumers visiting a website of an advertiser of the at least one advertisement based on at least one of the at least one advertisement or an advertisement of a competitor of the advertiser. In some embodiments, the plurality of metrics may include potential audience for the media content, a number count of consumers watching the media content at a particular time, sales, website visits, leads, quotes, and a time at which the media content is being watched. The metrics determining system 510 may determine how many consumers or people would be watching a television or accessing a website of the advertiser at a particular time or date. Such metrics may help the advertiser to plan and invest in the advertising on the TV or websites accordingly.

[00108] The linking system 508 may be a multi-rule based structural hierarchical linking system configured to link any advertiser’s product database to an organic product list. Hereinafter, the linking system 508 may be referred as the multi-rule based structural hierarchical linking system. The linking system 508 may interface with a third-party system and pass multiple complex instructions. The linking system 508 may also to differentiate between audience types, and the relevance each advertised product and offer had to each audience type. In some embodiments, the linking system 508 may identify the key variables of the advertisement. For example, the advertisement for a flight was to Europe, but was also business class with an airline company. The linking system 508 may determine that an advert should be delivered to people or an audience who are more likely to fly business class.

[00109] The database 512 may be configured to store one or more analysed media content, websites, metrics, and signatures of a plurality of advertisements. In some embodiments, the media content processing system 506 is further configured to process the media content prior to storing in the database 512. The processing of the media content may include at least one of encoding the media content, trimming, re-sizing the media content, and standardizing the encoding by standardizing the media content from at least one of a high definition and standard definition to one standard output. [00110] Figures 6A-6C depicts a flowchart diagram illustrating a method 600 for analysing and optimizing media content in real-time, in accordance with an embodiment of the present disclosure. As discussed with reference to the Figures 4 and 5, the media analysing and optimizing system 502 (or 404) is configured to analyse and optimize the media content streaming on the media streaming device 402.

[00111] At step 602, the media capturing system 504 continuously monitors media content streaming on the media streaming device 402 in real-time. At step 604, the media capturing system 504 records and extracts the media content comprising at least one advertisement from a broadcast signal by differentiating between the at least one advertisement and other media content in real time.

[00112] Then at step 606, the media content processing system 506 identifies the at least one advertisement when the at least one advertisement is aired first time, and also creates a signature for the at least one advertisement for accurately identifying the advertisement in future.

[00113] At step 608, the media content processing system 506 segments the media content to extract at least one of images, subtitles, audio, and electronic program guide from the media content in real-time. Then at step 610, the media content processing system 506 analyzes the at least one of images, subtitles, audio, and electronic program guide in real-time to determine specific information about the at least one advertisement and the media content by using automated logic and machine learning. Examples of the specific information may include but are not limited to, a brand and one or more products being promoted in the at least one advertisements, one or more key indicators for best brand marketing, and a marketing intent of the advertisement comprising a strategic objective and a tactic employed to achieve the objective, wherein the plurality of metrics comprising potential audience for the media content, a number count of consumers watching the media content at a particular time, sales, website visits, leads, quotes, and a time at which the media content is being watched.

[00114] In some embodiments, the media content is analysed by simultaneously cross-referencing search engine optimization (SEO) keywords against the extracted subtitles in real-time and searching for text in the advertisement.

[00115] At step 612, the digital optimizing system 514 calculates at least one of an interest and an intent of a plurality of consumers based on the analysis of the media content. Then at step 614, the digital optimizing system 514 captures and analyzes web traffic generated because of the at least one advertisement in real-time. At step 616, the digital media optimizing system 514 automatically searches a plurality of webpages to identify new dynamic content correlated with the at least one advertisement. At step 618, the digital media optimizing system 514 correlates the at least one advertisement with sales data of one or more products promoted in the at least one advertisement based on one or more factor.

[00116] At step 620, the metrics determining system 510 determine a plurality of metrics based on the analysis and correlation. Thereafter, at step 622, the metrics determining system 510 observes and measures a number of consumers visiting a website of an advertiser of the at least one advertisement based on at least one of the at least one advertisement or an advertisement of a competitor of the advertiser. An accuracy and reliability of the metrics may be determined based on one or more variables. The one or more variables may include such as, but not limited to, a time when the at least one advertisement is shown, a duration of the at least one advertisement, the advertisement is shown back to back of a competitor’s advertisement.

[00117] One or more analysed media content, websites data, metrics, and signatures of a plurality of advertisements may be stored in a database such as the central database 406. In some embodiments, the media content may be processed prior to storing on the database. For example, the media content may be encrypted or re-sized before storing or uploading in the database. [00118] The disclosed systems and methods may enable analysis of the media content with a 70% accuracy rate and 99% real-time processing uptime. The disclosed system may also analyse brand behavior. In some scenarios, as TV channels migrate to high resolution, and brand identities change, for example companies may change their logo treatment, then disclosed systems can recognize, learn and adapt to this fundamental shift in brand behavior. The disclosed systems are compatible with new broadcast and distribution platforms like online streaming services.

[00119] The disclosed systems and methods analyzes subtitles, images, etc. in the advertisements in real-time. Further, the systems and methods may link advertisements with current events on media streaming device like TV in real-time. For example, the system links an advertisement for soccer boots when a soccer match is on TV. Further, the system can identify multiple promoted brands featured within a single advertisement. Further, the media analysing system can identify a new advertisement the first time it is aired. The system can categorize and identify brands, campaigns, and products from the advertisements. Further, the system may inform a client like a company or advertiser whilst a campaign is live, to enable a proactive response. The disclosed system may enable real-time tracking and identification of promoted brands by the advertising brands, and may also determine real-time metrics that are able to estimate the potential audience reach of an advertisement.

[00120] The disclosed system may understand, collect, and track every advertisement on air in real-time through machine learning. Further, the media analysing system may use prediction algorithms for identifying the advertising brand or recognizing brands from a dynamic database including a plurality of brand information. The disclosed system may also perform high resolution advert image recognition to identify advertisements whilst they are being broadcast. The system may use a four-stage multi-layered validation process to ensure accuracy and differentiation between offers and products. The disclosed media analysing system analyzes the media content in real-time, offering TV insights at speed and with the granularity of digital.

[00121] The disclosed system may be an end to end TV analytics and digital media optimization platform configured to deliver accurate, granular real-time data. The disclosed system may provide real-time TV effectiveness measurement through tracking of web/app traffic and sales influenced by TV advertising with total competitive context. The disclosed system may also provide automated digital media bid adjustments in real-time maximizing second screen usage. The disclosed system is further configured to provide automated competitive intelligence dashboards delivering real-time competitive insights. The disclosed system may further provide a real-time TV advert sport catalogue for media strategy and creative interrogation. The disclosed system may also track delivery, and measure performance of premium TV (or media streaming device) sponsorships in real-time.

[00122] The disclosed system may help the companies to optimize creative (i.e. advert creative), daypart, channel, program, and frequency to maximize effectiveness. Further, the system may help the companies to amplify search, online video, online display and social to minimize CPR and CPA. The disclosed system may help the companies to conquest competitor TV in real-time to capitalize on their traffic. Further, the system helps the companies to combine the strengths of TV and digital media to improve the effectiveness of advertising campaigns and increase return of investment. Further, the system may help the companies to activate while their advert is on air in real-time, for any specified period, target the demographic watching TV, and target other Demographics to extend reach. Further, the system may help the companies to target products, brands etc. [00123] It will be understood that the devices and the databases referred to in the previous sections are not necessarily utilized together in method or system of the embodiments. Rather, these devices are merely exemplary of the various devices that may be implemented within a computing device or the server device, and can be implemented in exemplary another device, and other devices as appropriate, that can communicate via a network to the exemplary server device.

[00124] It will be appreciated that several of the above-disclosed and other features and functions, or alternatives thereof, may be desirably combined into many other different systems or applications. Various presently unforeseen or unanticipated alternatives, modifications, variations, or improvements therein may be subsequently made by those skilled in the art, which are also intended to be encompassed by the following claims.

[00125] The above description does not provide specific details of manufacture or design of the various components. Those of skill in the art are familiar with such details, and unless departures from those techniques are set out, techniques, known, related art or later developed designs and materials should be employed. Those in the art are capable of choosing suitable manufacturing and design details.

[00126] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. It will be appreciated that several of the above disclosed and other features and functions, or alternatives thereof, may be combined into other systems, methods, or applications. Various presently unforeseen or unanticipated alternatives, modifications, variations, or improvements therein may subsequently be made by those skilled in the art without departing from the scope of the present disclosure as encompassed by the following claims.

Claims

CLAIMS What is claimed is:

1. A media analysing system for analysing a plurality of media from a plurality of media streaming devices, comprising: a media content processing system connected to at least one media streaming device, configured to: monitor media content streaming on the at least one media streaming device, wherein the media content comprises at least one advertisement; extract the at least one advertisement from the media content by differentiating between the at least one advertisement and other media content in real-time; identify the at least one advertisement when the at least one advertisement is aired first time, wherein a signature is created for the at least one advertisement for accurately identifying the advertisement; and analyse the media content comprising at least one of images, subtitles, audio, and electronic program guide in real-time to determine specific information about the at least one advertisement by using at least one of an automated logic and machine learning; and a metrics determining system configured to determine a plurality of metrics about at least one of the media content and the at least one advertisement based on the analysis of the media content and the at least one advertisement.

2. The media analysing system of claim 1 further comprising: a linking system configured to link any advertiser’s product database to an organic product list, wherein the linking system interfaces with a third-party system and passes multiple complex instructions; and a database configured to store one or more analysed media content, the plurality of metrics, brand information, and signatures of a plurality of advertisements.

3. A media analysing system for analysing a plurality of media from a plurality of media streaming devices, comprising: a media capturing system configured to interface with at least one media streaming device for: monitoring media content streaming on the at least one media streaming device; and recording and extracting the media content comprising at least one advertisement from a broadcast signal by differentiating between the at least one advertisement and other media content in real-time; a media content processing system configured to: identify the at least one advertisement when the at least one advertisement is aired first time, wherein a signature is created for the at least one advertisement for accurately identifying the advertisement; and analyse the media content by identifying and extracting at least one of images, subtitles, audio, and electronic program guide in real-time to determine specific information about the at least one advertisement and the media content by using at least one of an automated logic and machine learning; and a metrics determining system configured to determine a plurality of metrics about the at least one of the media content and the at least one advertisement based on the analysis of the media content and the at least one advertisement.

4. The media analysing system of claim 3 further comprising: a linking system configured to link any advertiser’s product database to an organic product list, wherein the linking system interfaces with a third-party system and passes multiple complex instructions; and a database configured to store one or more analysed media content, the plurality of metrics, brand information, and signatures of a plurality of advertisements.

5. The media analysing system of claim 4, wherein the media content processing system is further configured to process the media content prior to storing in the database, wherein the processing the media content comprises at least one of encoding the media content, trimming, re sizing the media content, and standardizing the encoding by standardizing the media content from at least one of a high definition and standard definition to one standard output.

6. The media analysing system of claim 3, wherein the specific information comprising at least one of one or more products and brand being promoted in the at least one advertisement, one or more key indicators for best brand marketing, and a marketing intent of the advertisement comprising a strategic objective and a tactic employed to achieve the objective.

7. The media analysing system of claim 3, wherein the media content processing system is further configured to: simultaneously cross-reference search engine optimization (SEO) keywords against the subtitles identified and extracted from the media content in real-time; and search for text in the identified at least one advertisement.

8. The media analysing system of claim 3, wherein the plurality of metrics comprising potential audience for the media content, a number count of consumers watching the media content at a particular time, sales, website visits, leads, quotes, and a time at which the media content is being watched.

9. The media analysing system of claim 3, wherein the media capturing system is further configured to stream media content of the at least one media streaming device at least five times more efficiently with increased robustness, higher quality, and no bandwidth restriction.

10. A method for analysing a plurality of media from a plurality of media streaming devices, comprising: monitoring, by a media capturing system, media content streaming on the at least one media streaming device; recording and extracting, by the media capturing system, the media content comprising at least one advertisement from a broadcast signal by differentiating between the at least one advertisement and other media content in real-time; identifying, by a media content processing system, the at least one advertisement when the at least one advertisement is aired first time, wherein a signature is created for the at least one advertisement for accurately identifies the advertisement; segmenting, by the media content processing system, the media content to extract at least one of images, subtitles, audio, and electronic program guide from the media content in real-time; analysing, by the media content processing system, the at least one of the images, subtitles, audio, and electronic program guide in real-time to determine specific information about the at least one advertisement and the media content by using automated logic and machine learning; and determining, by a metrics determining system, a plurality of metrics based on the analysis of the media content and the at least one advertisement.

11. The method of claim 10 further comprising: linking, by a linking system, an advertiser’s product database to an organic product list, wherein the linking system is configured to interface with a third-party system and pass multiple complex instructions; and storing, in a database, one or more analysed media content, a plurality of metrics, brand information, and signatures of a plurality of advertisements.

12. The method of claim 11 further comprising processing, by the media content processing system, the media content prior to storing in the database, wherein the processing the media content comprises at least one of encoding the media content, trimming, re-sizing the media content, and standardizing the encoding by standardizing the media content from at least one of a high definition and standard definition to one standard output.

13. The method of claim 10, wherein the specific information comprising at least one of one or more products and a brand being promoted in the at least one advertisement, one or more key indicators for best brand marketing, and a marketing intent of the advertisement comprising a strategic objective and a tactic employed to achieve the objective.

14. The method of claim 10 further comprising: simultaneously cross-referencing, by the media content processing system, search engine optimization (SEO) keywords against the subtitles extracted from the media content in real-time; and searching, by the media content processing system, for text in the identified at least one advertisement.

15. The method of claim 10, wherein the plurality of metrics comprising potential audience for the media content, a number count of consumers watching the media content at a particular time, sales, website visits, leads, quotes, and a time at which the media content is being watched.

16. The method of claim 10 further comprising streaming, by the media capturing system, media content of the at least one media streaming device at least five times more efficiently with increased robustness, higher quality, and no bandwidth restriction.

17. A media analysing and optimizing system for analysing and optimizing digital media in real-time comprising: a media capturing system configured to interface with at least one media streaming device for: continuously monitoring media content streaming on the at least one media streaming device in real-time; and recording and extracting the media content comprising at least one advertisement from a broadcast signal by differentiating between the at least one advertisement and other media content in real-time; a media content processing system configured to: identify the at least one advertisement when the at least one advertisement is aired first time, wherein a signature is created for the at least one advertisement for accurately identifying the advertisement; segment the media content to extract at least one of images, subtitles, audio, and electronic program guide from the media content in real-time; and analyse the at least one of the images, subtitles, audio, and electronic program guide in real-time to determine specific information about the at least one advertisement and the media content by using at least one of an automated logic and machine learning; a digital media optimizing system configured to: calculate at least one of an interest and an intent of a plurality of consumers based on the analysis of the media content; capture and analyse web traffic generated because of the at least one advertisement in real-time; automatically search a plurality of webpages to identify new dynamic content correlated with the at least one advertisement; and correlate the at least one advertisement with sales data of one or more products promoted in the at least one advertisement based on one or more factor; and a metrics determining system configured to: determine a plurality of metrics based on the analysis and correlation; and observe and measure a number of consumers visiting a website of an advertiser of the at least one advertisement based on at least one of the at least one advertisement or an advertisement of a competitor of the advertiser.

18. The media analysing and optimizing system of claim 17 further comprising: a multi-rule based structural hierarchical linking system configured to link any advertiser’s product database to an organic product list, wherein the multi -rule based structural hierarchical linking system interfaces with a third-party system and passes multiple complex instructions; and a database configured to store one or more analysed media content, websites data, the plurality of metrics, and signatures of a plurality of advertisements.

19. The media analysing and optimizing system of claim 17, wherein the media content processing system is further configured to process the media content prior to storing in the database, wherein the processing the media content comprising at least one of encoding the media content, trimming, re-sizing the media content, and standardizing the encoding by standardizing the media content from at least one of a high definition and standard definition to one standard output.

20. The media analysing and optimizing system of claim 17, wherein the specific information comprising at least one of a brand and one or more products being promoted in the at least one advertisements, one or more key indicators for best brand marketing, and a marketing intent of the advertisement comprising a strategic objective and a tactic employed to achieve the objective, wherein the plurality of metrics comprising potential audience for the media content, a number count of consumers watching the media content at a particular time, sales, website visits, leads, quotes, and a time at which the media content is being watched.

21. The media analysing and optimizing system of claim 17, wherein the media content processing system is further configured to: simultaneously cross-reference search engine optimization (SEO) keywords against the subtitles extracted from the media content in real-time; and search for text in the identified at least one advertisement.

22. The media analysing and optimizing system of claim 17, wherein the digital media optimization system is further configured to: determine an accuracy and reliability of the plurality of metrics based on one or more variables; determine a varying degree of engagement of the plurality of consumers with the media streaming device based on at least one of a demography, media content dynamics; determine a website engagement pattern to assist in transforming website interactions into usable metrics; receive data comprising sales data, footfall data from a plurality of third-party devices; and analyse the received data based on the analysed media content comprising the at least one advertisement.

23. A method for analysing and optimizing digital media in real-time, comprising: continuously monitoring, by a media capturing system, media content streaming on the at least one media streaming device in real-time; recording and extracting, by the media capturing system, the media content comprising at least one advertisement from a broadcast signal by differentiating between the at least one advertisement and other media content in real-time; identifying, by a media content processing system, the at least one advertisement when the at least one advertisement is aired first time, wherein a signature is created for the at least one advertisement for accurately identifying the advertisement; segmenting, by the media content processing system, the media content to extract at least one of images, subtitles, audio, and electronic program guide from the media content in real-time; analysing, by the media content processing system, the at least one of the images, subtitles, audio, and electronic program guide in real-time to determine specific information about the at least one advertisement and the media content by using automated logic and machine learning; calculating, by a digital media optimizing system, at least one of an interest and an intent of a plurality of consumers based on the analysis of the at least one advertisement; capturing and analysing, by the digital media optimizing system, web traffic generated because of the at least one advertisement; automatically searching, by the digital media optimizing system, a plurality of webpages to identify new dynamic content, wherein the new dynamic content is correlated with the at least one advertisement; correlating, by the digital media optimizing system, the at least one advertisement with sales data of one or more products promoted in the at least one advertisement based on one or more factor; determining, by a metrics determining system, a plurality of metrics based on the analysis and correlation; and observing and measuring, by the metrics determining system, a number of consumers visiting a website of an advertiser of the at least one advertisement based on at least one of the at least one advertisement or an advertisement of a competitor of the advertiser.

24. The method of claim 23 further comprising: linking, by a multi -rule based structural hierarchical linking system, any advertiser’s product database to an organic product list; and storing, in a database, one or more analysed media content, websites data, metrics, and signatures of a plurality of advertisements.

25. The method of claim 23 further comprising processing, by the media content processing system, the media content prior to storing on the database, wherein the processing the media content comprising at least one of encoding the media content, trimming, re-sizing the media content, and standardizing the encoding by standardizing the media content from at least one of a high definition and standard definition to one standard output.

26. The method of claim 23, wherein the specific information comprising at least one of a brand and one or more products being promoted in the at least one advertisements, one or more key indicators for best brand marketing, and a marketing intent of the advertisement comprising a strategic objective and a tactic employed to achieve the objective, wherein the plurality of metrics comprising potential audience for the media content, a number count of consumers watching the media content at a particular time, sales, website visits, leads, quotes, and a time at which the media content is being watched.

27. The method of claim 23 further comprising: simultaneously cross-referencing, by the media content processing system, search engine optimization (SEO) keywords against the extracted subtitles in real-time; and searching, by the media content processing system, for text in the identified at least one advertisement.

28. The method of claim 23 further comprising: determining, by the digital media optimization system, an accuracy and reliability of the plurality of metrics based on one or more variables; determining, by the digital media optimization system, a varying degree of engagement of the plurality of consumers with the media streaming device based on at least one of a demography, media content dynamics; determining, by the digital media optimization system, a website engagement pattern to assist in transforming website interactions into usable metrics; receiving, by the digital media optimization system, data comprising sales data, footfall data from a plurality of third-party devices; and analysing, by the digital media optimization system, the received data based on the analysed media content comprising the at least one advertisement.