Method and device for detection and alternative substitution of advertising on television by means of data frames

Abstract

The invention relates to a method and a device for detection and alternative substitution of advertising on television by means of data frames, which comprises using the data frame by means of which the information regarding the programming broadcast to a television receiver is transported, detecting whether the broadcasting space belongs to a program or film, or if it belongs to advertising and, if so, blocking the broadcast and substituting it with alternative content. Preferably, data frame delimiters are used to protect the start and end of the advertising broadcast. Preferably, a pattern recognition system based on the prior use of the data frames is used to detect the advertisement and substitute it with alternative content.

Description

[0001] DESCRIPTION

[0002] METHOD AND DEVICE FOR DETECTION AND ALTERNATIVE SUBSTITUTION OF TELEVISION ADVERTISING BY MEANS OF DATA FRAME

[0003] OBJECT OF THE INVENTION

[0004] The invention, as expressed in the title of this specification, relates to a method and a device for detecting and replacing television advertising using a data frame, providing advantages and features, described in detail below, which represent an improvement on the current state of the art.

[0005] The object of the present invention lies in a method intended for the detection of a certain type of audiovisual television broadcasts, particularly advertisements, projected on a television or other device suitable for it, whether on networks, digital television or internet television, and the replacement of said advertising broadcast by alternative audio or audio and video content previously chosen by the user, which is distinguished by being totally automatic, that is to say without personnel intervention, and being based, essentially, on the distinction of the data frame through which the information is transported to the receiver, and which indicate the type of program that is being broadcast, and of the delimiters of said frame, which indicate the beginning and the end of each program, as well as, additionally, by means of the recognition of audio and video patterns obtained previously,A second aspect of the invention is a device capable of carrying out said method, which can be external and connected to the receiver or equipment on which the TV program is broadcast or be integrated into it during its manufacture.

[0006] FIELD OF APPLICATION OF THE INVENTION

[0007] The scope of the present invention falls within the audiovisual communication sector and the industry dedicated to the manufacture of audiovisual reproduction apparatus and devices, focusing particularly on the field of televisions and apparatus for reproducing television programs and content. BACKGROUND OF THE INVENTION

[0008] As is well known, most broadcast television programs include commercials, which account for a large part of the funding for the producers and networks that broadcast them.

[0009] However, in addition to the fact that in many cases users don't want to see them, frequently, and contrary to numerous regulations, advertising is often broadcast at a higher volume to attract attention and ensure the viewer is paying attention. Therefore, it is desirable to reduce this effect.

[0010] Application 11202231014, from the same applicant as the present invention, discloses a device that offers a solution to this problem based on increasing the volume to recognize when the television is broadcasting advertisements and replacing the audio, the image, or both.

[0011] However, this system can be triggered at times when the volume of the program being broadcast increases, but this does not correspond to the advertising broadcast.

[0012] Also, from the applicant's own document PCT / ES2023 / 070269, a method and device for blocking and alternative substitution of audiovisual television signals are known, in this case based on the detection of the frequency of the attached signal of the audio module parallel to the main one, of low frequency (frequently 6 - 8 Khz) that identifies its type for audience analysis and other services, and in what is known as fingerprints consisting of inaudible signals, watermarks and logos of the advertiser in advertising, broadcast channel and even the territory corresponding to said broadcast. However, this system, although effective, can be improved to be simpler and more reliable, especially if one takes into account that currently all broadcasts are made digitally through the transmission of computer data.

[0013] The objective of this invention is to develop an alternative, simpler, and more effective system for detecting advertising spaces in broadcast television programs and replacing them with content of the user's choice.

[0014] On the other hand, in the current state of the art, there are also other related documents with similar objectives that, however, propose very different technical solutions.

[0015] Thus, document US 2004237102 A1 discloses an "Ad Replacement" consisting of an ad resale system that sells targeted ads, replacing standard ads in a video signal. Standard ads are detected and replaced with targeted ads. Sponsors of targeted ads are billed when their ads are used to replace other ads. This is achieved by following a method that essentially comprises: receiving a video signal; detecting an ad in the video signal using fingerprint data; and replacing the ad with a replacement segment. To achieve this, as described in said document, the operation is based on a pre-recorded system, either manually or in a delayed manner, and therefore no real-time detection of commercials is performed. Furthermore, when the television detects them, it automatically mutes.

[0016] The main problem with this system is that a human operator must first detect the program segments that are to be deleted.

[0017] In fact, throughout the description of the cited document, only ideas are proposed that are not technically defined nor do they have a clearly explained operating model, on how to manufacture a device, or how it works and what technique it uses, with the conclusion that, in the end, it always ends up pointing out that the best option is for it to be supervised 24 hours a day by humans to correct errors.

[0018] Furthermore, the background section of said patent also mentions many other patents with different techniques for detecting advertisements, although they all have the same handicap, which is that they must be supervised by a human. Finally, it is worth mentioning document US 6771316 B1, referring to a "Method and apparatus for selectively altering a television video signal in real time", where the method and apparatus operate in a television receiver to identify unwanted transmission segments, such as commercials, of a television signal in real time in order to selectively alter the television display during each unwanted segment.More specifically, this patent is directed to a system, method and computer-readable storage for detecting segments such as advertisements in a video signal and replacing the detected segments with replacement portions such as targeted advertisements in closed-circuit television in bars, hotels, pubs, etc. (hospitality).

[0019] Furthermore, although it mentions a fingerprint, it doesn't describe or define the technique for capturing or identifying this tactile imprint. It is therefore an impractical and inaccurate technique. In fact, in all the schematics presented in the patent, neither the detection technique nor how the prototype for it is created is defined.

[0020] The program calculates the length of the ad to be replaced and searches for other ads of the same length in an internal memory. It also adds frames to fill in the gaps where a video ad can't play at 100%. However, this is all theory and imagination, with no concrete technique for a process that is equally impossible to execute.

[0021] Furthermore, the patent ends by describing the technique as: assigning three people all day long to 8-hour shifts (24 hours a day) to watch two televisions and pressing a button to replace unwanted ads with the one in the memory that stores the ads of interest, which makes the technique ridiculous. In other words, the patent states that ad detection can be achieved with 100% infallible human intervention. But at the same time, it's an obsolete technique.

[0022] Unlike all of this, the method and device object of the present invention, as stated in the claims, involve a much more modern, specific, automatic and effective detection system, innovatively based on the frame. Specifically, based on entering a dual-tuner HD DTT, with open source code in the software, to change the frame detection configuration parameters and give it the exact order so that, in the same way that it accurately detects the start and end of the film, it detects the start and end of the advertisements that are interspersed between films, programs, etc., but always recorded within the same frame and that now go unnoticed because they are not given greater use or interest.

[0023] EXPLANATION OF THE INVENTION

[0024] The method and a device for detection and alternative replacement of television advertising using a data frame that the invention proposes is configured as an optimal solution to the objectives previously indicated, with the characterizing details that make it possible and that distinguish it being conveniently included in the final claims that accompany this description.

[0025] Specifically, what the invention proposes, as noted above, is, on the one hand, a method for detecting audiovisual television broadcasts consisting of advertisements, whether on networks, digital television or internet television, and replacing said advertising with alternative audio or audio and video content, or video and Internet, or applications of all kinds executed by an AI and previously chosen by the user, with the innovative particularity of being based, essentially, on the distinction of the data frame through which the information is transported to the receiver and, additionally, on the recognition of patterns obtained from said frame distinction, a second aspect of the invention being a device capable of carrying out this method, and which can be external or integrated into the television receiver equipment itself during its manufacture.

[0026] It's worth noting that, in networks, digital television, or IP television (internet), a frame is a unit of data transmission. That is, it's a successive series of bits, organized cyclically, that carry information and allow this information to be extracted upon reception.

[0027] The television data frame provides all the information about the program being broadcast. Thus, within the frame, one can find out what type of program is being broadcast at that precise moment. From this, the method and device object of the present invention use this information to simply detect whether the broadcast slot belongs to a program or a movie, or whether it belongs to an advertisement. The device only needs this data to detect the advertisement and, based on this, divert the signal to the internal memory or peripherals to block the broadcast and replace it with other content.

[0028] Furthermore, this data frame contains delimiters, which indicate not only the program being broadcast, but also the beginning and end of each frame. Therefore, these delimiters allow us to determine the start and end times of commercials or spots.

[0029] Currently, any digital television receiver can access a portion of the data frame, as it is neither more nor less than that offered, for example, in programming guide menus, where the information that appears accessible to the viewer is limited to a specific layer of the frame that only refers to programs, movies, etc., not including advertising spaces.

[0030] However, such information about the advertising spots that will be broadcast interspersed or between programs is also there, although not accessible to viewers, so the method and device object of the invention is based on detecting and using such information to divert the signal as appropriate during the space provided for the advertisements.

[0031] In this way, the device obtains bits of information about the start and end of scheduled commercials with instantaneous speed, making the signal change extremely rapid, practically instantaneous.

[0032] It's worth remembering that the program information frame is legally embedded in all television broadcasts: The Program and System Information Protocol (PIPS, or PSIP) is the communications protocol used in the ATSC digital television system. This protocol is used to transport metadata about each channel in a television station's transport stream and to publish information about television programs. This allows viewers to select what they want to watch through a title and description.

[0033] This is why viewers can now see what program is currently airing at any given time, and each time they change channels, they can automatically see the title of the program currently airing, its end time, and the channel that broadcast it (Metadata).

[0034] However, all data can also be accessible through the use of appropriate digital software tools, the objective of this method and device being the use of a processor with specific software implemented therein to achieve such access; as well as with the use of software adapted to AI (artificial intelligence) that accelerates and guarantees the ad selection process, providing countless variants such as the use of voice, or avatars in the execution of software functions, such as asking which ads to discard, which program to record, which channel to watch, on / off.

[0035] Thus, in the data frame, schematically represented in Figure 2, you can find various bits of information such as: delimiters, preamble, sending or receiving address, data transmission speed, etc.

[0036] Within this entire data frame, the device's method and processor only use the layer that indicates the type of program being broadcast, to detect advertising and be able to divert the signal with complete safety and efficiency, since the frame is inserted globally.

[0037] This also has the advantage of enabling the device to operate in any country in the world and on any channel, whether broadcast on DTT or the internet. It can also work seamlessly on platforms like Netflix, Rakuten, and more.

[0038] Additionally, the method and processor of the device object of the invention, in addition to the described detection of advertising in the programming based on the frame information, contemplates the use of a pattern recognition system to detect said advertising and divert the signal.

[0039] To achieve this, the method, using the device's processor software, monitors the programming at all times using the data frame. It also simultaneously classifies and stores the previously classified advertising spaces in memory, storing the frames and audio tracks of the ads, which are often repetitive in campaigns that last a certain amount of time.

[0040] In this way, ads that have already been broadcast previously, and therefore classified as such, will be instantly recognized by the processor using the frames or audio stored in their memory, in addition to the data frame.

[0041] In any case, it is important to highlight that both the method and the device described constitute a completely automatic system that does not require any person or external assistance in its operation.

[0042] All of this makes the method and device proposed by the present invention a practically infallible and 100% effective system in the recognition of advertising space broadcasts.

[0043] The main steps of the method object of the invention and its operation for detecting advertisements using AI (artificial intelligence) are detailed in more detail below.

[0044] To detect TV advertising, artificial intelligence can use a combination of audio and video signal processing techniques, as well as machine learning algorithms.

[0045] - Audio and video signal processing.

[0046] Audio and video signal processing involves the analysis and manipulation of audio and video data to extract relevant information and perform various tasks. In the case of audio signal processing, techniques such as frequency analysis, sound wave pattern detection, noise reduction, and data compression can be used to effectively represent and manipulate audio signals. On the other hand, in video signal processing, algorithms can be applied for motion detection, object segmentation, video compression, and visual quality enhancement. These techniques make it possible to efficiently analyze, transform, and manipulate audio and video signals, which is critical for a wide range of applications, including media streaming, audiovisual production, and pattern recognition technology.

[0047] - Machine learning:

[0048] Machine learning (AI) is a subfield of computer science and a branch of artificial intelligence that focuses on developing techniques that enable systems to learn to solve problems and improve over time based on data. This is achieved through the use of machine learning algorithms that allow machines to learn patterns and make decisions based on available data.

[0049] There are several types of machine learning, including supervised, unsupervised, and reinforcement learning. In supervised learning, algorithms are trained using labeled data, allowing them to learn to make predictions or classifications based on previously labeled examples. On the other hand, in unsupervised learning, algorithms find patterns and structures in data without the need for labels. Reinforcement learning, on the other hand, involves algorithms learning through interaction with an environment, receiving feedback in the form of rewards or punishments based on their actions.

[0050] The process of training a machine learning model involves providing training data to a learning algorithm, from which the algorithm learns to perform specific tasks. The output of this process is a machine learning model, which is the artifact resulting from training and can be used to make predictions or decisions based on new data. In short, machine learning allows machines to learn from data and improve over time, making it essential in a wide range of applications, from pattern recognition to automated decision-making.

[0051] - Data integration.

[0052] Data integration is the process of combining heterogeneous data from various sources into the form and structure of a single application. Data integration can involve task automation, the use of artificial intelligence and machine learning, and the use of specialized tools and solutions to increase accuracy and efficiency in managing large volumes of data.

[0053] Artificial intelligence (AI) is considered the best way to detect TV ads in real time for several fundamental reasons.

[0054] Efficient analysis: AI tools can analyze large volumes of video content in real time, enabling fast and accurate detection of ads in live broadcasts.

[0055] Pattern Identification: AI can identify specific visual and auditory patterns in ads, such as brand logos, jingles, distinctive colors, or certain types of scenes, making it easier to accurately detect ads.

[0056] Personalization and Optimization: AI solutions can be tailored and optimized to identify relevant ads for specific audiences, enabling more effective and personalized advertising.

[0057] Real-time alerts: AI tools can provide real-time alerts and notifications about the presence of specific ads, allowing advertisers and media outlets to make quick and accurate decisions.

[0058] These AI capabilities, supported by the continuous development and improvement of AI content detection tools, make it the best option for detecting TV ads in real time.

[0059] The device of the invention incorporates a built-in television advertisement detection system. This means that in addition to the aforementioned detections, the device also features artificial intelligence (AI), which can be flawless and accurate in detecting television advertisements.

[0060] Artificial intelligence can detect TV commercials through various technologies and approaches. Programmatic technology, which uses AI and data collection, is used to increase the efficiency of personalization in TV advertising, providing ads that match the interests of the audience watching a particular channel or program.

[0061] Additionally, smart cameras equipped with artificial intelligence can detect and classify different vehicle categories and models, including the ability to identify when TV ads are airing by detecting certain visual or audio patterns.

[0062] Artificial intelligence is also used to analyze user behavior patterns and predict trends, allowing advertisers to target their campaigns more effectively based on general behaviors and preferences rather than specific personal data.

[0063] Additionally, contextual targeting, where ads are placed based on a web page's content rather than user behavior, is gaining popularity, and artificial intelligence is enhancing this technique by analyzing page content at a deeper level for more precise ad placement.

[0064] In short, artificial intelligence can detect TV commercials by analyzing audience data, recognizing visual and audio patterns, and optimizing ad placement based on content and viewer behavior. It works like this:

[0065] - Video signal capture:

[0066] The process begins with capturing the video signal from the television broadcast. This can be done using specialized television signal capture equipment or by accessing online video streams.

[0067] - Video preprocessing:

[0068] The video signal undergoes various reprocessing techniques. This includes color correction, lighting normalization, and noise reduction to ensure optimal image quality for analysis.

[0069] - Frame segmentation:

[0070] The video is broken down into individual frames so that each image can be analyzed separately. This allows artificial intelligence to examine each frame for advertising content.

[0071] - Feature Extraction:

[0072] Relevant features are extracted from each frame. This involves identifying visual patterns, colors, shapes, and other elements that may be indicative of an advertisement.

[0073] - Machine learning model:

[0074] A machine learning model, such as a convolutional neural network (CNN), is used to train the system to identify advertisements. This model is fed training data that includes examples of frames with and without ads.

[0075] ■Supervised learning:

[0076] During the training phase, the model adjusts its parameters to minimize the difference between its predictions and the actual labels provided in the training data. This allows the model to learn to recognize specific patterns associated with advertisements.

[0077] - Real-time inference: Once the model has been trained, it is used to perform real-time inferences during the live stream. Each frame is fed into the model, which determines whether it contains an advertisement based on the patterns learned during training.

[0078] - Post-processing and filtering:

[0079] Post-processing techniques are applied to filter out false positives and improve detection accuracy. This may include the addition of additional rules or the use of filtering algorithms to reduce errors.

[0080] - Inference post-processing:

[0081] After the AI ​​model performs real-time inferences, post-processing is performed to analyze the results. This may include removing false positives and false negatives.

[0082] - False positive filtering:

[0083] Since no model is perfect, false positives can occur—since the model incorrectly identifies a frame as an advertisement. To address this, additional techniques are implemented, such as the use of filtering algorithms that analyze specific features or sequence patterns to confirm or refute the presence of an ad.

[0084] - Confidence Threshold:

[0085] A confidence threshold is set for the model's predictions. If the confidence in the prediction falls below the threshold, the frame is discarded or flagged for further review. This threshold can be adjusted according to needs and tolerance for false positives or false negatives.

[0086] - Integration of heuristic rules:

[0087] Additional heuristic rules are incorporated to improve accuracy. These rules can be based on domain-specific knowledge, such as typical ad length, the frequency of appearance of certain visual elements, or specific patterns associated with ads. - Continuous learning:

[0088] The system can be designed to learn continuously, adapting to changes in advertising content over time. This involves periodically updating the model with new training data to maintain its detection ability under changing conditions.

[0089] - Disregard for human validation:

[0090] In no case will human validation be necessary, as artificial intelligence is capable of analyzing data segments, frames, patterns, times, and plots in an estimated time of thousandths of a second.

[0091] - Results and applications:

[0092] The result is a system capable of detecting commercials during television broadcasts, with applications ranging from ad monitoring to personalizing services based on TV content. Overall, the method involves a combination of advanced signal processing and machine learning techniques to achieve accurate ad detection in real-time TV environments.

[0093] The processing capacity required by the device of the invention to detect advertisements in television broadcasts using artificial intelligence depends on several factors, including the complexity of the machine learning model, the frame resolution, the frame rate per second (fps) of the broadcast, and the required degree of accuracy. Some general considerations are detailed below:

[0094] - GPU (Graphics Processing Unit):

[0095] In many cases, using GPUs significantly accelerates the training and inference of machine learning models. GPUs are designed to handle parallel operations and are especially efficient at computer vision-related tasks. RAM:

[0096] The amount of RAM available is crucial, especially when working with large data sets and complex models. The device of the invention has enough RAM to analyze up to six channels simultaneously.

[0097] -Storage:

[0098] Fast and efficient storage is also essential, as video data can be voluminous. High-performance storage can speed up loading and manipulation of TB of data.

[0099] -Parallelization:

[0100] The processor's parallelization capability is important, as some algorithms and operations can benefit significantly from simultaneous execution on multiple cores.

[0101] - Model customization:

[0102] Depending on the customization of the model and the complexity of the problem, the required hardware may vary. For example, if a pre-trained model architecture is used and fine-tuned for specific ad detection, fewer resources will be required than training a model from scratch.

[0103] DESCRIPTION OF THE DRAWINGS

[0104] To complement the description being made and in order to help better understand the characteristics of the invention, a drawing is attached to this specification, as an integral part thereof, in which the following has been represented for illustrative and non-limiting purposes:

[0105] Figure 1 shows a schematic diagram of the method and device for detecting and replacing television advertising using a data frame, which is the object of the invention, showing the operating basis and essential parts it comprises; Figure 2 shows a diagram of the structure of fields or sequences in the data frame of an Ethernet frame; and Figure 3 shows the representation of an image of an example of the information visible to viewers in a programming guide.

[0106] PREFERRED EMBODIMENT OF THE INVENTION

[0107] In view of the figures described, and in accordance with the numbering adopted, a non-limiting embodiment of the invention can be observed, which includes what is described in detail below.

[0108] Thus, as can be seen in said figures, the method of the invention, being of the type intended for the detection of a certain type of audiovisual television broadcasts, particularly advertisements, projected on a television or other device suitable for this purpose, on networks, digital television or internet television, and its replacement by alternative audio or audio and video content previously chosen by the user, is essentially distinguished by comprising, in a completely automatic manner, that is to say, it does not require any person or external help for its operation, the use of the data frame by means of which the information of the programming that is broadcast to the television receiver is transported, to detect whether the broadcast space belongs to a program or a film or if it belongs to advertising,preferably comprising the use of the delimiters of said data frames to detect the start and end of the advertising broadcast, and, where appropriate, block the broadcast and replace it with alternative content, as previously programmed by the user.

[0109] More specifically, this method comprises the following steps:

[0110] - Step A. Signal input through antenna (1) to a decoder (2).

[0111] - Step B. The decoder (2) collects the frame data and “translates” or converts it into an image. - Step C. Tuners (3, 4) store the channel access parameters.

[0112] - Step D. Once these data have passed through one of the tuners (4), they reach a processor (5) where, by means of an audio signal sample, executed every 10 milliseconds, said processor (5) calculates the silence times and the audio frequencies, as well as the data deciphered by the decoder (2).

[0113] - Step E. The processor (5) detects the frames and, using the specific software it incorporates and with the help of AI, it discriminates the data frame that corresponds to the advertisements and gives the order to a signal selector (6) to divert the signal and send the screen broadcast to the peripherals (internet (7), internal memory (8), external memory (9)) or to another channel recorded in the tuner (4) whose program does not correspond to the broadcast of advertisements, based on what was previously planned.

[0114] Thus the next step may include any of the following:

[0115] - Step F1. Request to return the signal to the tuners (3, 4) to show another channel that is not broadcasting advertisements.

[0116] - Step F2. Signal diversion to the internal memory (8), where the desired replacement content will be recorded, games, work, office, excel, applications of all kinds...

[0117] - Step F3. Signal diversion to an external memory (9), enabled with a USB connection, suitable for connecting a pendrive type memory, external hard drive, or mp3 devices, video game consoles, computers, or others.

[0118] - Step F4. Divert the signal to the Internet (7), to be able to browse any web page, email, playlists such as Spotify, YouTube, or any desired streaming platform.

[0119] In any case, in a preferred embodiment, the method of the invention further comprises the use of a pattern recognition system based on the described use of frame data, to detect said advertising and replace it with alternative content. To this end, in the intermediate step E, where the processor (5) detects the frames and, by means of specific software, discriminates the data frame that corresponds to the advertisements, the method comprises in parallel a pattern recognition step in which said processor stores in memory said discriminated frames as belonging to advertising spaces, such that it subsequently recognizes them when they are broadcast again by means of the frames or audio stored in memory thereof, and instantly gives the order to the signal selector (6) to send the screen broadcast to the pre-established peripherals.

[0120] On the other hand, in said step E, of detection of the frame by the processor (5), it also detects patterns, silences, frequencies... by means of the software controlled by AI through a system with audio, home automation or 3D avatar by means of hologram, in order to be able to interact in first person with the system to give it direct instructions to turn it on and off, what program you want to see, what type of advertising is accepted and which has to be rejected.

[0121] For its part, the device object of the invention for carrying out said method of detection and alternative replacement of television advertising by means of data frames, and whose operation is also completely automatic, essentially comprises the following elements:

[0122] - A decoder (2), installed between the antenna (1) and the screen and audio equipment of the television receiver / player (not shown), capable of converting the information from the data frames of TV broadcasts into image and sound.

[0123] - Two or more tuners (3, 4) to save the access parameters to the channels, connected to the decoder (2).

[0124] - A processor (5) connected to the tuners and incorporating specific software and AI (artificial intelligence) and which every 10 milliseconds executes an audio signal sample, to calculate the silence times and audio frequencies, as well as the data decoded by the decoder (2).

[0125] - And a signal selector (6) connected to the processor (5) and to the channel tuners (3, 4) and to different peripherals (internet (7), internal memory (8), external memory (9)), to divert the program broadcast signal to one or the other depending on what was previously planned.

[0126] Preferably, the device also comprises a Wi-Fi connection module (10) to connect the device to the Internet, which provides access to the cloud in which movies, music, etc. are saved, and a Bluetooth connection module (not shown) to connect or send data via the mobile phone or other devices.

[0127] Finally, it should be mentioned that all, several or some of the aforementioned elements of the device, either form part of an external equipment to the receiver / player of the television programs whose advertising spaces are intended to be detected and replaced by other programming, which is connected to it for this purpose, or all of them are directly integrated into the device itself during its manufacture.

[0128] Looking at the diagram in Figure 2, an example of the sequence structure of the data frame of an Ethernet frame (11) can be seen. The following fields or sequences are included in this frame (11):

[0129] - a first sequence (11 1 ), Preamble: It is a sequence of bits used for synchronization and configuration of the receivers before receiving the actual data.

[0130] - a second stream (1 12) SD (Data Stream) with the main information transmitted in the data frame, which can be video, audio, text, commands, etc.

[0131] - a third sequence (1 13) of destination address at the data link layer (MAC

[0132] - Media Access Control). It is the unique hardware address that identifies the destination network interface to which the frame is sent.

[0133] - a fourth sequence (1 14) of source MAC address, similar to the previous one, but in this case indicating the address of the network interface from which the frame is sent.

[0134] - a fifth sequence (115) Type, which indicates the type of upper layer protocol being used. For example, it could indicate whether the data is IPv4, IPv6, ARP, etc.

[0135] - a sixth sequence (1 16) of information, referring to the actual data being transmitted, such as video, audio, or any other type of information being sent over the network.

[0136] - a seventh padding sequence (1 17), sometimes necessary to meet certain frame size requirements, to bring it to a minimum length and consisting of null bits or random data containing no useful information.

[0137] - and an eighth frame check sequence (118) containing an error check value, used to detect errors in the frame during transmission.

[0138] Furthermore, in that example, the type value greater than 0x600 indicates the protocol type IP.ARP.RARP (IP (Internet Protocol), ARP (Address Resolution Protocol) or RARP (Reverse Address Resolution Protocol); and the type value less than 0x600 indicates the length of the information field, that is, instead of identifying a specific protocol, it indicates how many bytes of data are in the "Information" sequence (115) of the Ethernet frame.

[0139] Figure 3 shows an image (12) of an example of the information visible to viewers in a television programming guide, where the plot information (the part visible to viewers) can be seen. The information in this example shows that a weather program is being broadcast.

[0140] This would simply be a layer of the data frame. This layer of the frame is intended for television viewers to provide real-time broadcast information. However, within this frame space are also advertising spaces, which are also delimited and indicated as advertising in the same frame. However, the advertising information is not visible to television viewers since it is not relevant in this case. The device of the invention uses it to divert the signal to the user's convenience. In this way, the device will obtain bits of information about the beginning and end of commercials with instantaneous speed, making signal switching extremely rapid or instantaneous.

[0141] Having sufficiently described the nature of the present invention, as well as the manner of putting it into practice, it is not considered necessary to make its explanation more extensive so that any expert in the field understands its scope and the advantages derived from it.

Claims

CLAIMS 1 Method for detection and alternative replacement of television advertising by means of a data frame which, intended for the detection of a certain type of audiovisual television broadcasts, particularly commercials, projected on a television or other device suitable for this purpose, on networks, digital television or internet television, and its replacement by alternative audio or audio and video content previously chosen by the user, is characterized by comprising, in a completely automatic manner, the use of the data frame by means of which the information of the programming that is broadcast to the television receiver is transported, detecting whether the broadcast space belongs to a program or a film or if it belongs to advertising and, where appropriate, blocking the broadcast and replacing it with alternative content. 2.- Method for detection and alternative replacement of television advertising using a data frame, according to claim 1, characterized by comprising the use of the delimiters of said data frames to detect the start and end of the advertising broadcast. 3.- Method for detection and alternative replacement of television advertising using a data frame, according to claim 1 or 2, characterized by comprising the following steps: - Step A. Signal input via antenna (1) to a decoder (2), - Step B. Collection, by the decoder (2), of the frame data and “translation” or conversion of these into images, - Step C. Saving by the tuners (3, 4) connected to the decoder (2), of the access parameters to the channels, - Step D. Once the data passes through one of the tuners (4) and reaches a processor (5), said processor (5), by means of an audio signal sample executed every 10 milliseconds, calculates the silence times and the audio frequencies, as well as the data decrypted by the decoder (2), - Step E. The processor (5), using specific software and with the help of AI, detects the frames and discriminates the data frame that corresponds to advertisements and gives the order to a signal selector (6) to divert the signal and send the screen broadcast to peripherals or to another channel recorded in the tuner (4) whose program does not correspond to the broadcast of advertisements, based on what was previously planned. 4.- Method for detection and alternative replacement of television advertising using a data frame, according to claim 3, characterized by comprising a step F1 of requesting the return of the signal to the tuners (3, 4) to show another channel that is not broadcasting advertisements. 5.- Method for detection and alternative replacement of television advertising using a data frame, according to claim 3, characterized by comprising a step F2 of diverting the signal to the internal memory (8), where the desired replacement content will be recorded, games, work, office, excel, applications of all kinds... 6.- Method for detection and alternative replacement of television advertising using a data frame, according to claim 3, characterized by comprising a step F3 of diverting the signal to an external memory (9), enabled with a USB connection, to connect a pendrive type memory, external hard drive, or mp3 devices, video game consoles, computers, or others. 7.- Method for detection and alternative replacement of television advertising using a data frame, according to claim 3, characterized by comprising a step F4 of signal diversion to the Internet (7) to be able to browse any web page, email, playlists such as Spotify, YouTube, or any desired streaming platform. 8.- Method for detection and alternative replacement of television advertising using a data frame, according to any of the preceding claims, characterized by also comprising the use of a pattern recognition system from the prior use of frame data to detect such advertising and replace it with alternative content. 9.- Method for alternative detection and replacement of television advertising by means of a data frame, according to claim 8 and any of claims 3 to 7, characterized in that, in the intermediate step E, where the processor (5) detects the frames and discriminates the data frame that corresponds to advertisements, it comprises a parallel step of pattern recognition in which the processor (5) saves in memory said discriminated frames as belonging to advertising spaces, so that it subsequently recognizes them when they are broadcast again by means of the frames or audio stored in memory thereof, and instantly gives the order to the signal selector (6) to send the screen broadcast to the pre-established peripherals. 10.- Method for alternative detection and replacement of television advertising using a data frame, according to claim 8 and 9 and any of claims 3 to 7, characterized in that, in step E, the processor (5) detects patterns, silences, frequencies... using the software, or also software controlled by AI that uses a system with audio, home automation or 3D avatar using a hologram, in order to be able to interact in the first person with the system to give it direct instructions to turn it on and off, which program you want to watch, what type of advertising is accepted and which has to be rejected. 11.- Device for detection and alternative replacement of television advertising by means of data frames, according to the method described in claims 1 to 10, characterized by comprising: - a decoder (2), installed between the antenna (1) and the screen and audio equipment of the television receiver / player, capable of converting the information of the data frames of the TV broadcasts into image and sound, - tuners (3, 4) for saving the access parameters to the channels, connected to the decoder (2), - a processor (5) connected to the tuners and incorporating specific software and AI and which every 10 milliseconds executes an audio signal sample, to calculate the silence times and audio frequencies, as well as the data decoded by the decoder (2), and - a signal selector (6) connected to the processor (5) and to the channel tuners (3, 4) and to different peripherals, such as the Internet (7), internal memory (8), external memory (9), to divert the broadcast signal of the program to one or the other depending on what was previously planned. 12.- Device for detection and alternative replacement of television advertising using a data frame, according to claim 11, characterized by comprising a Wi-Fi connection module (10) to connect the device to the Internet and a Bluetooth connection module. 13.- Device for detection and alternative replacement of television advertising by means of a data frame, according to claim 11 or 12, characterized in that all, several or some of its elements form part of equipment external to the receiver / player of the television programs whose advertising spaces are intended to be detected and replaced by other programming, which is connected to it for this purpose. 14.- Device for detection and alternative replacement of television advertising by means of data frame, according to claim 11 or 12, characterized in that all its elements are directly integrated into the receiver / player of the television programs whose advertising spaces are intended to be detected and replaced by other programming, during the actual manufacture of the same.

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