DESC:FIELD OF THE INVENTION
Embodiments of the present invention generally relate to digital advertising technologies and more specifically to a system and computer-implemented method for personalized and dynamic advertisement generation using multi-sensor integration.
BACKGROUND OF THE INVENTION
The realm of digital advertising has continuously evolved, seeking to maximize the efficacy and relevance of advertisements to various audiences. A significant challenge in this domain is achieving personalized and dynamic advertisement delivery that accurately resonates with the diverse preferences and immediate needs of individual users. Traditional and many contemporary advertising systems often struggle to effectively target advertisements, resulting in a diminished user experience and reduced engagement. This challenge is particularly pronounced in dynamic environments where user preferences and circumstances can rapidly change, necessitating an advertising approach that is both responsive and highly tailored.
In response to these challenges, various solutions and technologies have been developed in the field of digital advertising. These include targeted online advertising platforms, geolocation-based advertisement systems, and the use of demographic and behavioural data to tailor advertising content. Some systems have integrated basic sensor data, such as location tracking, to contextualize advertisements based on the user's immediate environment. Additionally, advancements in artificial intelligence have led to more sophisticated algorithms capable of predicting user preferences and displaying corresponding advertisements.
Despite these advancements, existing solutions often fall short in delivering truly personalized and dynamic advertisement experiences. Many systems rely heavily on historical data, which may not accurately reflect current user needs or preferences, particularly in rapidly changing contexts. Furthermore, the integration of sensor data in these systems is typically limited in scope and does not fully leverage the potential of multi-sensor integration for real-time, context-aware advertisement generation. This limitation results in a gap between the potential of dynamic advertising and the actual experiences delivered to the users, often leading to irrelevant or untimely advertisements.
Therefore, there is a clear and present need for an improved approach in digital advertising that overcomes the limitations of current technologies. There is a need in the art for a a system and computer-implemented method for personalized and dynamic advertisement generation using multi-sensor integration. This need underscores the importance of developing a solution that aligns with the evolving landscape of digital advertising, meeting both the immediate and future demands of this rapidly progressing field.
OBJECT OF INVENTION
An object of the present invention is to provide a system for personalized and dynamic advertisement generation using multi-sensor integration.
Another object of the present invention is to provide a computer-implemented method for personalized and dynamic advertisement generation using multi-sensor integration.
Yet another object of the present invention is to integrate multi-sensor data in real-time to generate truly personalized and dynamic advertisements.
Yet another object of the present invention is to integrate generative AI for real-time advertisement generation based on gathered data.
SUMMARY OF THE INVENTION
The present invention is described hereinafter by various embodiments. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiment set forth herein.
According to one aspect of the invention, there is provided a system for personalized and dynamic advertisement generation. The system comprises a display device that presents advertisement content, an input means that receives user interactions, one or more sensors that capture real-time user and environmental data, a data repository that stores advertisement content, and a processing module operably connected to the display device, the input means, the one or more sensors, and the data repository. The processing module receives real-time data from the one or more sensors and the input means, the real-time data includes user attributes and environmental parameters. The processing module analyzes the received data to determine contextual and user-specific parameters, but not limited to, user demographics, engagement level, or detected preferences. The processing module retrieves advertisement content from the data repository based on the analyzed parameters or dynamically generates advertisement content by modifying one or more advertisement attributes. The processing module adapts the advertisement content in real time by adjusting one or more attributes, the attributes include, but are not limited to, a visual element, textual element, or subject representation, based on detected user characteristics or environmental conditions. The processing module transmits the retrieved or generated advertisement content to the display device for presentation.
In accordance with an embodiment of the present invention, the one or more sensors comprise, but are not limited to, a camera, a microphone, a motion detector, a biometric sensor, or a geolocation sensor, the sensors are configured to capture user attributes, but not limited to, gender, age, emotion, physical engagement, or detected language.
In accordance with an embodiment of the present invention, the processing module tracks user engagement with the advertisement content by analyzing at least one of eye contact duration, facial expression changes, interaction through the input means, or scanning of a displayed QR code.
In accordance with an embodiment of the present invention, the processing module generates real-time advertisement content by modifying at least one of a background element, subject representation, product depiction, or promotional text based on detected user characteristics and contextual parameters.
In accordance with an embodiment of the present invention, the processing module transmits user engagement data and advertisement performance metrics to enable adaptive advertisement strategies based on detected audience interaction patterns.
In accordance with an embodiment of the present invention, the advertisement content stored in the data repository comprises multiple advertisement layers, the advertisement layers include, but are not limited to, a background layer, a subject layer, a product layer, and a text layer. The processing module dynamically modifies one or more of the advertisement layers based on detected user characteristics and contextual parameters.
In accordance with an embodiment of the present invention, the processing module prioritizes advertisement selection or generation based on contextual factors, but not limited to, time of day, geographical location, detected audience demographics, or real-time user engagement patterns.
According to another aspect of the invention, there is provided a computer-implemented method for personalized and dynamic advertisement generation. The method comprises receiving real-time data from one or more sensors and an input means, the real-time data includes user attributes and environmental parameters. The method comprises analyzing the received data to determine contextual and user-specific parameters, the parameters include, but are not limited to, user demographics, engagement level, or detected preferences. The method comprises retrieving advertisement content from a data repository based on the analyzed parameters or dynamically generating advertisement content by modifying one or more advertisement attributes. The method comprises adapting the advertisement content in real time by adjusting one or more attributes, the attributes include, but are not limited to, a visual element, textual element, or subject representation, based on detected user characteristics or environmental conditions. The method comprises transmitting the retrieved or generated advertisement content to a display device for presentation.
In accordance with an embodiment of the present invention, analyzing the received real-time data further comprises detecting user attributes, but not limited to, gender, age, emotion, skin tone, facial features, physical fitness, liveliness, eye contact, language, and accessories based on input from the one or more sensors. The method further determines user engagement levels with the displayed advertisement content by evaluating at least one of eye contact duration, facial expression changes, input means interaction, or scanning of a displayed QR code. The method further generates engagement insights based on the detected user attributes and engagement levels to optimize future advertisement selection and presentation.
In accordance with an embodiment of the present invention, retrieving or generating advertisement content further comprises retrieving advertisement content stored in the data repository, wherein the advertisement content comprises multiple advertisement layers, the advertisement layers include, but are not limited to, a background layer, a subject layer, a product layer, and a text layer. The method further dynamically modifies at least one advertisement layer based on detected user attributes and contextual parameters, the contextual parameters include, but are not limited to, time of day, geographical location, detected audience demographics, or real-time user engagement patterns. The method further generates a modified advertisement by adjusting one or more attributes within the advertisement layers to align with the detected user characteristics before transmitting the advertisement content to the display device for presentation.
BRIEF DESCRIPTION OF THE DRAWINGS
So that the above-recited features of the present invention can be understood in detail, a more particular description of the invention, briefly summarized above, may be had by reference to embodiments, some of which are illustrated in the appended drawings. It is to be noted, however, that the appended drawings illustrate only typical embodiments of this invention and are therefore not to be considered limiting of its scope, as the invention may admit to other equally effective embodiments. These and other features, benefits, and advantages of the present invention will become apparent by reference to the following figures, with like reference numbers referring to like structures across the views, wherein:
Fig. 1A illustrates a system for personalized and dynamic advertisement generation, in accordance with an embodiment of the present invention;
Fig. 1B illustrates an exemplary environment where the system is installed inside a public vehicle for a passenger, in accordance with an embodiment of the present invention;
Fig. 2 illustrates a method for personalized and dynamic advertisement generation using real-time data from sensors and AI-driven analysis, in accordance with an embodiment of the present invention;
Figs. 3A-3B illustrate an exemplary implementation of the system and method using an information flow approach to showcase data processing, advertisement selection, and real-time adaptation of advertisements, in accordance with an embodiment of the present invention; and
Figures 4A-4B illustrates exemplary applications of the system in public places, in accordance with an embodiment of the present invention.
DETAILED DESCRIPTION OF THE DRAWINGS
The present invention is described hereinafter by various embodiments with reference to the accompanying drawing, wherein reference numerals used in the accompanying drawing correspond to the like elements throughout the description.
While the present invention is described herein by way of example using embodiments and illustrative drawings, those skilled in the art will recognize that the invention is not limited to the embodiments of drawing or drawings described and are not intended to represent the scale of the various components. Further, some components that may form a part of the invention may not be illustrated in certain figures, for ease of illustration, and such omissions do not limit the embodiments outlined in any way. It should be understood that the drawings and detailed description thereto are not intended to limit the invention to the particular form disclosed, but on the contrary, the invention is to cover all modifications, equivalents, and alternatives falling within the scope of the present invention as defined by the appended claim. As used throughout this description, the word "may" is used in a permissive sense (i.e. meaning having the potential to), rather than the mandatory sense, (i.e. meaning must).
Further, the words "a" or "an" mean "at least one” and the word “plurality” means “one or more” unless otherwise mentioned. Furthermore, the terminology and phraseology used herein is solely used for descriptive purposes and should not be construed as limiting in scope. Language such as "including," "comprising," "having," "containing," or "involving," and variations thereof, is intended to be broad and encompass the subject matter listed thereafter, equivalents, and additional subject matter not recited, and is not intended to exclude other additives, components, integers, or steps. Likewise, the term "comprising" is considered synonymous with the terms "including" or "containing" for applicable legal purposes.
Embodiments of the present invention provide a system and a computer-implemented for personalized and dynamic advertisement generation using multi-sensor integration. In this context, 'personalized advertisements' refer to ad content that is tailored to the individual preferences, behaviours, and current context of each user. This personalization is achieved through analysing a variety of data sources. For example: The integration of multi-sensor data, including but not limited to, location sensors, cameras, and microphones, further enriches this personalization by allowing the system to understand and adapt to the user's immediate environment and circumstances. The goal is to deliver advertisements that are highly relevant and engaging to each individual user, thereby increasing the likelihood of user interaction and satisfaction with the advertised products or services.
'Dynamic advertisements,' on the other hand, emphasize the adaptability and real-time responsiveness of the advertising content. Unlike static ads, dynamic advertisements can change in real time based on various factors such as the time of day, current events, or immediate changes in user behaviour and environment. This dynamic nature allows for a more agile and responsive advertising strategy, ensuring that the content remains relevant not just to the user’s long-term profile but also to their immediate context and needs. By combining personalization with dynamic capabilities, the present invention ensures that each advertisement is not only tailored to the user but also timely and contextually appropriate, significantly enhancing the overall effectiveness and efficiency of the advertising process.
Figure 1A-1B illustrates a system for personalized and dynamic advertisement generation, in accordance with an embodiment of the present invention. Referring to Figure 1A, the system (100) comprises, but is not limited to, a display device (112), an input means (102) such as one or more switches or buttons (1120), one or more sensors (104), and a processing module (106) operably connected to the display device (112), the input means (102), and the one or more sensors (104). The system further includes a data repository (108) configured to store advertisement content and a communication network (110) enabling data exchange between various components.
The display device (112) serves as a fundamental component of the system, acting as the primary medium for presenting personalized and dynamic advertisements to users. In the realm of digital advertising, display devices vary widely, including but not limited to LED displays, LCD displays, TFT displays, OLED displays, electronic paper displays, projection systems, or holographic displays, each uniquely capable of presenting advertisements in various environments and applications. As illustrated in Figure 1B, the display device (112) is implemented within a public vehicle (160), such as a taxi or cab, ensuring advertisement delivery to passengers in transit.
The input means (102) enables user interaction with the system, allowing users to express preferences and provide feedback regarding the advertisements displayed. In interactive digital systems, input devices range from mechanical switches, touch-sensitive switches, voice-activated microphones, gesture recognition sensors, and interactive keypads. In the present invention, the input means (102) may be implemented using one or more switches or buttons (1120), enabling direct user interaction. Additionally, in some embodiments, the display device (112) and input means (102) are integrated, forming a touch-sensitive display, thereby improving user convenience and interaction efficiency.
The one or more sensors (104) are a critical component of the system, playing a pivotal role in data acquisition for personalized and dynamic advertisement generation. These sensors (104) facilitate the collection of contextual and environmental data, thereby enhancing the customization and relevance of advertisements. The sensors may include, but are not limited to, cameras (image sensors), microphones, GPS modules, motion detectors, and biometric sensors.
The cameras enable visual data collection, assisting in understanding the user’s immediate environment and detecting user engagement with displayed advertisements. In some embodiments, by utilizing camera-based advanced algorithms, the system detects a user’s emotional state or reaction to advertisements. This capability allows dynamic adjustment of the advertisement content in real-time, ensuring that advertisements resonate with user preferences and immediate emotional responses. This feature contributes to a more engaging and empathetic advertising experience, where advertisements are tailored not only to user preferences but also to momentary emotional states, thereby increasing personalization and engagement.
The microphones facilitate audio data collection, offering insights into the ambient environment and allowing voice-based user inputs. In some embodiments, the system temporarily processes audio samples to detect user language or brand mentions in real-time, using a predefined list of brands or partners. Importantly, this audio data is neither stored nor transmitted externally, ensuring user privacy and data security. This real-time analysis optimizes advertisement targeting, aligning advertisements with the user’s spoken preferences without compromising privacy.
The motion detectors enhance the system’s ability to understand user activity levels and physical context, while biometric sensors, such as fingerprint scanners or facial recognition modules, enable secure and personalized user interaction.
The GPS modules play a key role in facilitating geolocation-based advertisement targeting. The system leverages real-time location data to present geographically relevant advertisements, ensuring higher contextual relevance. As illustrated in Figure 1B, the display device (112) inside the public vehicle (160) may display advertisements relevant to the user’s travel route or surrounding environment. This approach enables advertisements to dynamically promote local businesses, restaurants, or retail offers, providing users with location-specific incentives.
By integrating multiple sensors (104), the system ensures that advertisements are not only personalized based on user preferences but also timely and contextually relevant. This combination of sensor-driven data acquisition and AI-based advertisement adaptation results in a highly efficient and user-centric digital advertising system.
In some embodiments, the system (100) may further integrate advanced sensors such as temperature sensors, humidity sensors, or light sensors, which provide additional layers of environmental context. As shown in figure 1B, these sensors (104) enable the system to tailor advertisement content based on current weather conditions, ambient lighting, or the time of day, thereby enhancing the dynamism and relevance of the displayed advertisements. Furthermore, the integration of a multi-sensor array ensures a comprehensive understanding of the user’s contextual environment, leading to highly sophisticated advertisement personalization.
It is pertinent to note that none of the collected data is permanently stored by the system in any form and is exclusively used for real-time analysis to generate and display relevant advertisements. The system ensures that all user-related data is processed in-memory, thereby eliminating the risk of unauthorized data retention.
Recognizing the paramount importance of user privacy, in some embodiments, the system (100) includes an additional button (1120) (may be virtual buttons on touch screen display or physical buttons), dedicated to clearing all cache and temporary data from the display device (112) and/or input means (102). This feature is designed for users with heightened privacy concerns, allowing them to manually erase all personal data collected during their interaction, including but not limited to language detection, image processing, and audio processing data. Notably, this function does not impact core system data, ensuring continued operational integrity while offering users tangible control over their data privacy.
In another embodiment, to further underscore the commitment to user privacy and data security, the system (100) is configured with an automatic history and cache clearing mechanism. For instance, following each ride in a public vehicle (160), upon detection of a new user, or at predefined time intervals, the system automatically erases all temporary data gathered during the previous interaction. This ensures that each user’s data remains distinct and private, preventing data mix-ups or unauthorized access to personal information. Additionally, this feature guarantees that the system always operates with current and relevant data, maintaining the accuracy and personalization of advertisement content, and thereby reinforcing both user privacy and the efficacy of the advertisement system.
In addition to the wide range of communication technologies mentioned above, in some embodiments, the system may also incorporate Near Field Communication (NFC) to facilitate direct and effortless interaction between end-user devices and our smart advertising devices. NFC allows for instant, contactless data exchange by simply bringing an end-user device within close proximity of our smart device, enhancing the user experience with a quick and secure method to receive personalized ads, offers, or additional product information. This feature not only streamlines the process of engaging with the advertisement content but also enables a more interactive and enriched user experience, fostering higher engagement rates and providing advertisers with valuable insights into user preferences and behaviours.
In accordance with an embodiment of the present invention, the system also includes the data repository (108), which is a critical component for storing and managing data essential for the system's operation. This repository can be implemented either as local storage within the system or as cloud-based storage, providing flexibility in terms of scalability and accessibility.
The data repository is configured to hold/store a collection of pre-generated advertisements provided by advertisers. Each of these advertisements is stored with specific parameters or details, such as target audience demographics, environmental triggers, or contextual requirements.
Referring back to the system components, the processing module (106) serves as the central hub facilitating the functionalities of each component. The processing module (106) is operably connected to the display device (112), input means (102), sensors (104), data repository (108), and communication network (110), managing all aspects of personalized and dynamic advertisement creation and delivery.
Equipped with computing capabilities, the processing module (106) comprises at least a memory unit (1062), configured to store machine-readable instructions, which may be loaded from various non-transitory machine-readable mediums such as CD-ROMs, DVD-ROMs, Flash Drives, or computer software programs. The memory unit (1062) may include, but is not limited to, EPROM, EEPROM, and Flash memory.
At its core, the processing module (106) contains a processor (1064) operably connected to the memory unit (1062). The processor (1064) may be a microprocessor, including but not limited to ARM-based processors, Intel-based processors, field-programmable gate arrays (FPGAs), general-purpose processors, or application-specific integrated circuits (ASICs). In certain embodiments, the processing module (106) may be implemented using miniature computing modules, such as a Raspberry Pi or similar control modules, ensuring scalability and efficiency in advertisement processing.
A critical aspect of the processing module's (106) functionality is the implementation of Artificial Intelligence (AI) and Machine Learning (ML) technologies. These technologies enable data analysis, collation, and presentation of advertisements in real-time. Specifically, the processing module (106) employs generative AI, an advanced subset of AI, to create personalized and dynamic advertisements in real time.
The generative AI functionality allows the system to:
1. Analyze user data and environmental inputs obtained via sensors (104).
2. Retrieve or dynamically generate advertisements based on detected user characteristics and engagement levels.
3. Modify at least one advertisement layer in real-time, wherein the advertisement layers include a background layer, a subject layer, a product layer, and a text layer.
4. Adapt the displayed content dynamically to ensure each advertisement aligns with real-time user preferences.
The use of generative AI ensures that advertisements are not just reactive but proactively designed to maximize user engagement, thereby enhancing the overall impact and efficiency of the advertisement system.
In accordance with an embodiment of the present invention, the system (100) further incorporates a communication network (110) that plays a pivotal role in ensuring seamless connectivity among the system components and external entities. Integral to this network is a communication module (not explicitly numbered in the drawings, but part of (110)), which facilitates data exchange, synchronization, and real-time advertisement delivery.
The communication module manages data exchange between the processing module (106), data repository (108), and display device (112).
In some embodiments, the communication module enables external connectivity, allowing the system to interface with third-party servers, emergency services, municipal corporations, hospitals, fire stations, and other relevant authorities. This feature allows real-time detection of emergency situations based on gathered contextual and environmental data, ensuring a broader range of applications beyond advertisement delivery.
The communication network (110) may function as either a short-range or long-range network, depending on system requirements. It may utilize wired or wireless communication technologies, including but not limited to, Bluetooth, Radio Frequency (RF), Wi-Fi, Satellite Communication or Serial or parallel communication interfaces (for wired connectivity)
To ensure compatibility and interoperability with a wide range of devices and networks, the communication network (110) supports multiple communication protocols, such as TCP/IP, 3GPP, 3GPP2, LTE, 4G, 5G and IEEE 802.x standards.
By adopting these communication protocols, the system guarantees robust and secure data exchange, ensuring that advertisements are delivered efficiently, user interactions are processed in real-time, and external services can integrate seamlessly with the system.
In some other embodiments of the present invention, there may be a provision for user devices, such as smartphones, tablets etc, to be connected with the system, should a user desires. This connectivity allows for a more interactive and personalized advertising experience. By linking the smartphones with the system, users can receive additional information about the advertisements displayed, such as detailed product descriptions, special offers, or direct links for online purchases. This integration not only enhances user engagement with the advertisements but also offers a seamless transition from viewing an advertisement to taking action, such as making a purchase or learning more about a product or service. Furthermore, this connection enables the system to gather more precise feedback and preferences from the users, which can be used to refine and improve the personalization algorithms. This feature underscores the system's commitment to providing a user-centric advertising experience, leveraging the ubiquitous presence of smartphones to enhance the relevance and effectiveness of the advertisements presented.
Additionally, all the components of the system may be powered by a power source, selected from power input from power supply of the vehicle or rechargeable or replaceable batteries.
It will be appreciated by a skilled addressee that the system can be implemented/configured in multiple ways. It can be configured either as a localized system or as a remotely distributed system. In a localized setup, all components, including the processing module and data repository, are situated within a single location or device. This arrangement is particularly beneficial for scenarios requiring rapid data processing and display, such as in moving vehicles or in areas with limited network connectivity. Alternatively, the system can be implemented as a remotely distributed system, where processing is handled by a remote server. This setup allows for more robust computing power and larger data handling capabilities, making it suitable for complex processing tasks and large-scale deployments. The remote server can manage multiple display devices spread across various locations, synchronizing content, and ensuring uniformity in advertising. Additionally, this distributed approach can offer enhanced data security and easier system updates and maintenance, as the core processing and data storage are centralized in a secure location.
Method of Operation:
Figure 2 illustrates a computer-implemented method (200) for personalized and dynamic advertisement generation, in accordance with an embodiment of the present invention. This method integrates multi-sensor data (104), artificial intelligence (AI), and generative AI to analyze user-specific and contextual parameters, retrieve or generate personalized advertisements, and dynamically adapt the advertisement content in real-time.
To better understand the stepwise implementation of the method, Figures 3A and 3B illustrate an exemplary information flow diagram detailing how data moves within the processing module (106) and other system components. The processing module (106), which includes a memory unit (1062) and a processor (1064), orchestrates the method by receiving, analyzing, retrieving/generating, adapting, and transmitting advertisement content in real-time.
Step 202: Data Collection - The first step in the method involves collecting real-time data from the system’s one or more sensors (104), input means (102), and communication module (part of 110). The collected data includes both user attributes and environmental parameters that serve as inputs for personalized advertisement generation.
In a practical implementation, consider a user, Alex, who is traveling in a public vehicle (160), such as a taxi. The system (100) installed inside the vehicle continuously captures relevant data to determine Alex’s current context, preferences, and engagement level. The following data streams contribute to real-time analysis:
1. Cameras (104) capture visual indicators, such as wearables, accessories, or physical features (e.g., glasses, headphones, clothing brands), to infer potential brand preferences. Cameras may also detect facial expressions, enabling emotion-based ad customization.
2. Microphones (104) analyze small, transient audio samples to detect the user's spoken language or brand mentions. However, to protect privacy, no audio recordings are stored or transmitted—all analysis occurs in real-time and is immediately discarded after processing.
3. GPS modules (104) determine the geographical location, allowing the system to prioritize advertisements relevant to nearby businesses.
4. Motion detectors (104) infer user activity level, ensuring that advertisements align with the user's current engagement state (e.g., passive browsing vs. active interaction).
5. Biometric sensors (104) provide additional contextual personalization, for instance, by analyzing the user's physical fitness level and tailoring advertisements for health and wellness products.
6. Environmental sensors (104) such as temperature, humidity, or light sensors help contextualize advertisements based on the current weather or time of day.
As seen in Figure 3A, the processing module (106) receives and processes this real-time data stream, constructing a detailed user context for dynamic advertisement generation.
Step 204: Data Analysis and Context Understanding
Once the real-time data is received, the processing module (106) utilizes AI and machine learning algorithms to analyze and interpret the data, determining contextual and user-specific parameters. These parameters include, but are not limited to:
- User demographics (age, gender, physical attributes).
- Engagement level, such as eye contact duration with the display device (112), facial expression changes, and interaction through the input means (102).
- Detected preferences, inferred from brand interactions, location data, and language detection.
This analysis ensures that advertisement selection or generation is not solely based on static historical data but dynamically aligns with the user’s immediate behavior and surroundings.
In Figure 3A, the processing module (106) processes the analyzed data and determines whether a pre-existing advertisement should be retrieved from the data repository (108) or if an AI-generated advertisement should be created dynamically.
Step 206: Advertisement Retrieval or Generation
Once the processing module (106) establishes user-specific and contextual parameters, it determines whether an appropriate advertisement is already available in the data repository (108) or if a new advertisement needs to be generated dynamically.
If a relevant pre-generated advertisement exists, the processing module (106) retrieves the advertisement content from the data repository (108) and transmits it to the display device (112).
If no exact match is found, or if the system is set to create real-time adaptive advertisements, the generative AI within the processing module (106) dynamically constructs an advertisement by modifying elements of pre-existing advertisements.
A key feature of the generative AI-based advertisement generation process is the use of multiple advertisement layers. The system decomposes advertisements into layers, including:
- Background Layer (scenery, environmental setting).
- Subject Layer (a person representing the intended audience).
- Product Layer (the advertised item or service).
- Text Layer (promotional messaging, discounts, or call-to-action).
Based on real-time context, these layers are dynamically modified before being transmitted to the display device (112).
Step 208: Adaptation of Advertisement Content
Before the advertisement is displayed, the processing module (106) dynamically adapts and customizes the advertisement content based on:
- Time of day, weather conditions, or real-time environmental inputs.
- User characteristics, including gender, age, and engagement patterns.
- Immediate engagement tracking, such as detecting if the user is actively looking at the screen or is visibly engaged with the ad.
As seen in Figure 3B, once the advertisement content is fully adapted, it is prepared for display on the display device (112).
Step 210: Transmission and Display of Advertisement Content
Once final adjustments are made to the advertisement, the processing module (106) transmits the final advertisement content to the display device (112) for presentation.
To enhance user interaction, the system allows multiple engagement mechanisms, such as:
- Physical interaction via input means (102), including switches (1120).
- QR code scanning, allowing users to access exclusive offers, promotions, or product pages directly from the advertisement.
- NFC-based interaction, enabling contactless retrieval of additional advertisement information by simply bringing a smartphone near the display device (112).
In some embodiments, the system tracks engagement metrics, such as Eye contact duration with the advertisement, Facial expressions indicating interest or disengagement and Direct interactions with QR codes or NFC.
These insights allow the system to continuously optimize advertisement strategies, ensuring that future advertisements are more precisely targeted.
Working Example: Personalized and Dynamic Advertisement Generation in a Public Vehicle (Taxi)
To illustrate the operation of the system, consider a real-world scenario where a person, Alex, enters a public vehicle (160), such as a taxi, equipped with the advertisement system (100) as shown in Figure 1B. The system is integrated with a display device (112) mounted on the back of the front seat, a set of sensors (104) for real-time data collection, and an input means (102) with interactive buttons (1120) that allow Alex to interact with the advertisements.
As soon as Alex enters the vehicle, the system begins executing the computer-implemented method (200) in real time.
In Step 202 (Data Collection), the one or more sensors (104) collect relevant contextual and environmental data.
- The cameras (104) analyze Alex’s physical features, detecting characteristics such as age group, gender, and presence of accessories like glasses or headphones.
- The microphones (104) process a short audio sample to detect Alex’s language while ensuring that no personal data is stored or transmitted.
- The GPS module (104) identifies the vehicle’s current location and route, allowing the system to prioritize advertisements relevant to nearby stores, restaurants, or services.
- The motion detector (104) confirms that Alex is seated and looking toward the display device (112), indicating potential engagement with advertisements.
In Step 204 (Data Analysis and Context Understanding), the processing module (106) interprets the collected data. Based on the sensor inputs, the system determines that Alex is a young adult wearing headphones and traveling through a commercial district in the evening. The AI engine further analyzes facial expressions to infer Alex’s mood and engagement level.
In Step 206 (Advertisement Retrieval or Generation), the processing module (106) accesses the data repository (108) to determine the most relevant advertisement. Since Alex is traveling near a shopping center, the system searches for advertisements related to stores and promotions in that area. No exact match is found for Alex’s current context and engagement pattern, so the generative AI dynamically creates a new advertisement by modifying pre-existing advertisement layers. The advertisement consists of multiple layers, including a background layer (showing the shopping center), a subject layer (showing a young person like Alex), a product layer (showing headphones), and a text layer (displaying a 15% discount offer on electronics at a nearby store).
In Step 208 (Adaptation of Advertisement Content), the AI dynamically modifies elements of the advertisement before display. Since the microphone detected English as the spoken language, the advertisement text is adjusted accordingly. The display brightness is adjusted based on ambient light conditions detected by the light sensor (104). The advertisement is optimized for engagement, ensuring it aligns with Alex’s detected age group, accessories, and interests.
In Step 210 (Transmission and Display of Advertisement Content), the final advertisement is presented on the display device (112) inside the taxi. The advertisement features an interactive QR code that allows Alex to scan and redeem the offer at the electronics store near the upcoming destination. If Alex presses a button (1120) on the input means (102) to request more details, the system displays additional product options or nearby deals. The system tracks Alex’s engagement, analyzing eye contact duration and facial expressions to measure interest.
If Alex scans the QR code, the system logs this as a conversion event, providing valuable performance data to advertisers. Once Alex exits the taxi, the system automatically clears all temporary data, ensuring that the next user starts with a fresh, privacy-secured experience.
This example illustrates how the system and method of the present invention would work in real-world scenario.
In some embodiments, as part of its advanced advertising capabilities, the system (100) uniquely incorporates a real-time pricing mechanism that enables dynamic adjustment of advertisement costs. This pricing strategy aligns with current market conditions, user engagement levels, and specific advertisement performance metrics. By continuously analyzing real-time engagement data, such as eye contact duration, user interaction via input means (102), and QR code scanning, the processing module (106) determines the effectiveness of each advertisement. This allows advertisers, particularly small and medium-sized businesses, to optimize their advertising expenditures, ensuring they achieve the best possible return on investment. The system further incorporates a revenue-sharing model, which incentivizes display partners, such as taxi operators and public venue owners, by allocating a portion of the advertising revenue to them. This model fosters broader adoption of the system and encourages partnerships between the platform and various display providers, creating an ecosystem where both advertisers and display operators mutually benefit.
In some embodiments, the display device (112) may be equipped with interactive elements, such as virtual or physical buttons (1120) and a microphone, to enable direct user input. This functionality allows users to actively communicate their preferences or immediate needs regarding the types of advertisements they wish to see, thereby enhancing the relevance and personalization of the advertising content. For instance, a user traveling in a taxi may interact with the system by using touch buttons or voice input to indicate an interest in local dining options or hotels. Once the input is received, the system employs its voice recognition and user input processing capabilities to identify relevant advertisement content. Based on real-time data analysis, advertisements closely matching the user’s expressed preferences are displayed, such as promotions for nearby restaurants, special offers on accommodations, or discount coupons for entertainment venues.
The integration of voice recognition technology through the microphone plays a crucial role in interpreting verbal inputs, while the virtual or physical buttons offer a non-verbal means of engagement, ensuring accessibility across diverse user preferences. The system’s AI algorithms dynamically adjust the displayed advertisements in real time based on user inputs, ensuring that content remains both relevant and contextually appropriate. This interactive feature enhances user engagement by providing an immediate, responsive advertising experience, particularly useful in scenarios where the user is actively searching for specific services or offers. The ability for users to influence the advertisement content significantly increases the value proposition, shifting the advertising model from passive display to an interactive engagement platform.
To ensure privacy and data security, this embodiment is designed in compliance with applicable privacy regulations. Any data input by the user is processed in real time and is not stored beyond the necessary duration, maintaining a balance between customization and privacy. Once an advertisement is delivered based on the user’s request, any associated interaction data is automatically cleared, preventing long-term retention of personal preferences. This ensures that users retain control over their engagement with the system without concerns over persistent tracking or data storage.
The system is highly adaptable and can be deployed across various use cases, accommodating both individual users in private environments and larger audiences in public spaces. In an individual setting, such as a taxi, auto-rickshaw, or private vehicle, the system’s sensors (104) capture real-time contextual data to generate and display advertisements that are directly relevant to the user’s current environment and preferences. This level of personalization ensures that advertisements are tailored to the specific interests and immediate needs of the user, maximizing engagement and effectiveness.
This will be better understood in reference to exemplary implementations of Figures 4A-4B. Figures 4A and 4B illustrate exemplary implementations of the system in different public environments, demonstrating its ability to dynamically adjust advertisement content based on broader contextual factors rather than individual user preferences. Figure 4A shows an implementation of the system within an auto-rickshaw (402), where the display device (112) is positioned at the back of the driver’s seat for easy visibility to passengers. The one or more sensors (104) are configured to analyze real-time data, such as the passenger's demographics, detected accessories, or language preferences, to generate advertisements that are highly relevant to the individual user. For example, if the system detects that the passenger is wearing headphones, it may display an advertisement for a nearby electronics store offering discounts on audio devices. Additionally, a QR code embedded in the advertisement may be scanned using a user device, such as a smartphone, allowing passengers to instantly interact with the content—for example, availing discounts, navigating to a product page, or making an online reservation. The input means (1120) enables manual interaction with the system, allowing passengers to further refine displayed advertisements based on their preferences.
Figure 4B illustrates another implementation of the system in a hotel lobby (452), where the advertisement content is dynamically adapted based on a collective audience rather than a single user. Unlike the auto-rickshaw implementation, which focuses on an individual passenger, the hotel lobby setting involves a larger number of people, requiring the system to analyze environmental data on a broader scale. The one or more sensors (104) are strategically placed to capture real-time contextual data, such as crowd density, movement patterns, and predominant demographics of visitors. By processing this data, the system determines the most relevant advertisement content for the collective audience. For instance, if the system detects a high number of tourists in the lobby, it may prioritize advertisements promoting nearby landmarks, guided tours, or local experiences. Conversely, if the detected audience consists mainly of business professionals, the system may display advertisements for executive services, business lounges, or corporate dining options.
Additionally, QR codes displayed on the advertisement screens in such public spaces can be scanned by individual users through their smartphones, allowing them to instantly engage with the promotional content, access exclusive offers, or book services. This interactive feature enhances the accessibility and engagement of advertisements, bridging the gap between digital ad displays and real-time user interaction. The ability to transition seamlessly between individual and collective targeting highlights the system’s versatility in delivering advertisements that dynamically respond to different user environments.
The system’s adaptability ensures it can cater to a wide spectrum of users while maintaining high standards of privacy and data protection. The ability to analyze both individual and collective audience characteristics allows the system to optimize advertising strategies for maximum effectiveness. The possibilities for implementation extend across multiple domains, including smart city applications, airport terminals, stadiums, and retail complexes, demonstrating the scalability of the present invention. By integrating real-time engagement tracking, AI-driven advertisement adaptation, and privacy-centric user interaction, the system provides a comprehensive, future-ready solution for personalized and dynamic advertising across diverse environments.
The present invention offers several significant advantages in the realm of advertising technology:
• Personalized Advertising Experience: By integrating advanced AI algorithms and multi-sensor data analysis, the system provides highly personalized advertisements, tailored to individual user preferences and current context. This ensures that each user receives content that is relevant and engaging to them.
• Dynamic Content Delivery: The system's ability to dynamically adjust and generate advertisements in real-time based on environmental factors and user inputs allows for a highly responsive advertising approach, keeping the content fresh and pertinent.
• Efficient Use of Advertising Resources: With real-time pricing and a revenue-sharing model, the system offers a cost-effective solution for advertisers, particularly benefiting small businesses by providing affordable access to sophisticated advertising tools.
• Enhanced User Engagement: The interactive features of the system, such as touch-input displays and voice recognition, allow users to actively engage with the advertisements, enhancing their overall experience and potentially leading to higher conversion rates.
• Versatility in Application: The system can be effectively implemented in various environments, from individual settings like cabs to public spaces like transport stations and hotel lobbies, making it versatile for different advertising needs.
• Data Privacy Compliance: Despite the extensive use of user data and environmental inputs, the system prioritizes user privacy by not storing sensitive information and adhering to data protection regulations, ensuring a balance between personalization and privacy.
• Scalable and Flexible System Design: The system's design allows for both localized and remotely distributed implementations, offering flexibility in deployment based on specific requirements and environments.
• Real-time Data Processing: The system's processing module, equipped with AI and ML technologies, ensures rapid and efficient processing of data, leading to timely and contextually relevant advertisement generation.
• Enhanced Commercial Appeal: By offering a tailored and engaging user experience, the system increases its commercial appeal to both advertisers and users, potentially leading to higher adoption rates and market penetration.
These advantages collectively contribute to the present invention’s potential to transform the advertising landscape, making it a pioneering solution in the field of digital advertising technology.
In general, the word “module,” as used herein, refers to logic embodied in hardware or firmware, or to a collection of software instructions, written in a programming language, such as, for example, Java, C, or assembly. One or more software instructions in the modules may be embedded in firmware, such as an EPROM. It will be appreciated that modules may comprised connected logic units, such as gates and flip-flops, and may comprise programmable units, such as programmable gate arrays or processors. The modules described herein may be implemented as either software and/or hardware modules and may be stored in any type of computer-readable medium or other computer storage device.
Further, while one or more operations have been described as being performed by or otherwise related to certain modules, devices or entities, the operations may be performed by or otherwise related to any module, device, or entity. As such, any function or operation that has been described as being performed by a module could alternatively be performed by a different server, by the cloud computing platform, or a combination thereof.
Various modifications to these embodiments are apparent to those skilled in the art from the description and the accompanying drawings. The principles associated with the various embodiments described herein may be applied to other embodiments. Therefore, the description is not intended to be limited to the embodiments shown along with the accompanying drawings but is to be providing broadest scope of consistent with the principles and the novel and inventive features disclosed or suggested herein. Accordingly, the invention is anticipated to hold on to all other such alternatives, modifications, and variations that fall within the scope of the present invention and appended claims.

,CLAIMS:We Claim:
1. A system (100) for personalized and dynamic advertisement generation, comprising:
a display device (112) configured to present advertisement content;
an input means (102) configured to receive user interactions;
one or more sensors (104) configured to capture real-time user and environmental data;
a data repository (108) configured to store advertisement content;
a processing module (106) operably connected to the display device (112), the input means (102), the one or more sensors (104), and the data repository (108);
wherein the processing module (106) is configured to:
receive real-time data from the one or more sensors (104), and the input means (102), the real-time data including user attributes and environmental parameters;
analyze the received data to determine contextual and user-specific parameters, including at least one of user demographics, engagement level, or detected preferences;
retrieve advertisement content from the data repository (108) based on the analyzed parameters or dynamically generate advertisement content by modifying one or more advertisement attributes;
adapt the advertisement content in real-time by adjusting one or more attributes, the attributes including at least a visual element, textual element, or subject representation, based on detected user characteristics or environmental conditions; and
transmit the retrieved or generated advertisement content to the display device (112) for presentation.
2. The system (100) as claimed in claim 1, wherein the one or more sensors (104) comprise at least one of a camera, a microphone, a motion detector, a biometric sensor, or a geolocation sensor, the sensors (104) being configured to capture user attributes including at least gender, age, emotion, physical engagement, or detected language.
3. The system (100) as claimed in claim 1, wherein the processing module (106) is configured to track user engagement with the advertisement content by analyzing at least one of eye contact duration, facial expression changes, interaction through the input means (102), or scanning of a displayed QR code.
4. The system (100) as claimed in claim 1, wherein the processing module (106) is configured to generate real-time advertisement content by modifying at least one of a background element, subject representation, product depiction, or promotional text based on detected user characteristics and contextual parameters.
5. The system (100) as claimed in claim 1, wherein the processing module (106) is configured to transmit user engagement data and advertisement performance metrics to enable adaptive advertisement strategies based on detected audience interaction patterns.
6. The system (100) as claimed in claim 1, wherein the advertisement content stored in the data repository (108) comprises multiple advertisement layers, the advertisement layers including at least a background layer, a subject layer, a product layer, and a text layer, wherein the processing module (106) is configured to dynamically modify one or more of the advertisement layers based on detected user characteristics and contextual parameters.
7. The system (100) as claimed in claim 1, wherein the processing module (106) is configured to prioritize advertisement selection or generation based on contextual factors including at least time of day, geographical location, detected audience demographics, or real-time user engagement patterns.
8. A computer-implemented method (200) for personalized and dynamic advertisement generation, comprising:
receiving (202) real-time data from one or more sensors (104), and an input means (102), the real-time data including user attributes and environmental parameters;
analyzing (204) the received data to determine contextual and user-specific parameters, the parameters including at least one of user demographics, engagement level, or detected preferences;
retrieving (206) advertisement content from a data repository (108) based on the analyzed parameters or dynamically generating advertisement content by modifying one or more advertisement attributes;
adapting (208) the advertisement content in real-time by adjusting one or more attributes, the attributes including at least a visual element, textual element, or subject representation, based on detected user characteristics or environmental conditions; and
transmitting (210) the retrieved or generated advertisement content to a display device (112) for presentation.
9. The computer-implemented method (200) as claimed in claim 8, wherein analyzing the received real-time data comprises:
detecting user attributes including at least gender, age, emotion, skin tone, facial features, physical fitness, liveliness, eye contact, language, and accessories based on input from the one or more sensors (104);
determining user engagement levels with the displayed advertisement content by evaluating at least one of eye contact duration, facial expression changes, input means (102) interaction, or scanning of a displayed QR code; and
generating engagement insights based on the detected user attributes and engagement levels to optimize future advertisement selection and presentation.
10. The computer-implemented method (200) as claimed in claim 8, wherein retrieving or generating advertisement content comprises:
retrieving advertisement content stored in the data repository (108), wherein the advertisement content comprises multiple advertisement layers including at least a background layer, a subject layer, a product layer, and a text layer;
dynamically modifying at least one advertisement layer based on detected user attributes and contextual parameters, the contextual parameters including at least time of day, geographical location, detected audience demographics, or real-time user engagement patterns; and
generating a modified advertisement by adjusting one or more attributes within the advertisement layers to align with the detected user characteristics before transmitting the advertisement content to the display device (112) for presentation.