Wireless Set-Top Box Ad Viewing Detection via Wi-Fi Sensing
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Solution Overview
Problem
Advertisers lack the ability to determine if users are watching advertisements and discern their sentiments, leading to inefficiencies in ad placement and customization.
Innovation Solution
A system comprising a set-top box (STB) and router that utilize machine learning models to detect user presence and sentiment through Wi-Fi sensing, voice detection, remote control activity, and television state, generating reports for advertisers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If advertisers purchase advertisement slots, then they can promote their products or services, but they have no way of knowing if users are watching the advertisement
Solution Approach 1:
The patent introduces a wireless communication system as an intermediary between the advertisement delivery system and the advertiser. The system uses wireless signals to detect user presence and watching status, transmitting this information back to advertisers without requiring direct integration into the advertisement playback infrastructure. This mediator approach enables information collection while maintaining system simplicity.
Solution Approach 2:
The detection system leverages existing wireless communication infrastructure and user devices to perform self-service monitoring. The system uses standard wireless protocols to detect user presence and interaction patterns, eliminating the need for specialized hardware or complex custom detection mechanisms. The system serves itself by utilizing already-deployed technology to solve the information loss problem.
2Adaptability or versatility
If advertisers want to customize advertisements based on user sentiment, then they can improve ad relevance, but they currently have no way of discerning user sentiment
Solution Approach 1:
The system implements feedback mechanisms that continuously monitor user interaction patterns during advertisement playback. By analyzing wireless communication signals and user device responses, the system gathers real-time feedback about user engagement and sentiment. This feedback loop enables advertisers to receive actionable information about how users are responding to advertisements, facilitating informed customization decisions.
Solution Approach 2:
The system performs preliminary detection of user presence and engagement patterns before finalizing advertisement customization. By pre-analyzing user behavior data collected through wireless communications, the system prepares customization parameters in advance, enabling rapid adaptation of advertisements to individual user preferences without requiring complex real-time processing during playback.
3Productivity
If advertisers continue to pay for advertisement slots with low viewing, then they maintain revenue flow, but they waste money on ineffective ad placement
Solution Approach 1:
The patent replaces traditional mechanical or manual ad placement verification methods with wireless communication-based detection systems. Instead of relying on physical presence checks or simple viewing counters, the system uses wireless signal analysis to intelligently determine actual user engagement. This substitution enables more precise measurement of ad effectiveness, allowing advertisers to optimize their budgets by reallocating funds from low-performing slots to high-value opportunities.
Solution Approach 2:
The system changes the parameters used to measure advertisement effectiveness from basic viewing counts to comprehensive wireless-based engagement metrics. By transforming the measurement parameters to include user presence detection, interaction patterns, and sentiment analysis, the system provides advertisers with richer data about actual ad performance. This parameter transformation enables more accurate evaluation of ad slot value and informs better budget allocation decisions.
Data Source
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AI summary
A wireless set top box (STB) determines whether a user is watching an advertisement on a display device. When playback of the advertisement starts, the STB requests a router to determine the presence of the user, and the router determines the presence by performing sensing (such as Wi-Fi sensing) in conjunction with using a machine learning model. The router sends a response to the STB that indicates whether the user is present. The STB uses the response in combination with various events detected by the STB to determine whether the user is watching the advertisement. The STB also analyzes feedback from the user to determine whether the user has a positive or negative sentiment towards the advertisement.