Behavioral Event Measurement via Visual Landscape Reconstruction
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Solution Overview
Problem
Current technologies fail to effectively monitor and analyze user behavior and exposure to digital content and external events, particularly in augmented reality contexts, as they rely on simplistic methods like tracing traffic between devices and the internet, which are inadequate for complex interactions and outdoor media exposure.
Innovation Solution
An electronic system and method using sensors and wearable technologies to collect and reconstruct visual data from digital screens and the environment, determining user attention and exposure to digital and external content, employing local rules and fingerprints for object recognition and validation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If traditional traffic tracing methods are used to monitor user behavior, then device complexity is reduced, but measurement precision and reliability of user behavior data deteriorate
Solution Approach 1:
The system segments user behavior monitoring into multiple independent data collection channels: screen capture module, camera module for external environment, sensor module for device context, and audio module. Each segment collects specific types of data independently, which are then integrated to form comprehensive behavioral profiles, resolving the contradiction by distributing complexity across modular components while maintaining high measurement precision.
Solution Approach 2:
The patent introduces an intermediary processing layer that captures screen content, processes it through image recognition algorithms, and correlates it with camera data and sensor data. This intermediary layer acts as a mediator between raw data collection and final behavior analysis, enabling precise measurement without requiring direct complex interactions between all system components.
2Reliability
If comprehensive sensors and wearable technologies are deployed to capture user exposure, then measurement precision and reliability improve, but device complexity and energy consumption increase
Solution Approach 1:
The system employs universal data collection mechanisms where the screen capture module, camera, and sensors all feed into a unified behavioral event detection framework. Each component serves multiple purposes: the camera captures both external environment and can verify screen visibility, sensors track both device orientation and user physiological responses. This multi-functionality reduces overall system complexity while maintaining comprehensive and reliable exposure measurement.
Solution Approach 2:
The patent dynamically adjusts sampling parameters based on detected behavioral contexts. When user attention is detected through screen capture analysis, the system increases sampling frequency for relevant sensors and reduces frequency for others. This parameter adaptation allows reliable exposure measurement while managing device complexity and energy consumption through intelligent resource allocation.
3Measurement precision
If detailed visual landscape reconstruction is performed to analyze user attention, then measurement precision improves, but processing time and energy consumption increase
Solution Approach 1:
The system extracts only the essential visual features needed for attention detection from complete screen captures and camera images. Instead of processing entire visual landscapes, the patent identifies and extracts key regions of interest, such as advertisement areas, screen content zones, and external objects, then focuses processing only on these extracted elements. This extraction approach maintains high measurement precision while dramatically reducing processing time and energy consumption.
Solution Approach 2:
The patent implements partial processing where the system performs detailed visual landscape reconstruction only when behavioral events are detected or when user attention is suspected. For routine monitoring periods, the system uses lighter-weight analysis methods. This selective application of intensive processing maintains measurement precision for critical events while reducing overall processing time and energy consumption during normal operation.
Data Source
AI summary
Electronic system for obtaining data, via one or more digital devices, on user behavior, digital transactions, and exposure relative to digital content and services, or external exposure and associated events between the user and the environment via sensors attached to digital devices, the system being configured to collect data reflecting the content and objects that the user at least potentially perceives as rendered on one or more digital screens attached to smart devices, reconstruct the at least potentially perceived visual landscape based on the collected data, and determine the target and/or level of user attention in view of the reconstruction and associated exposure events detected therein, and to apply locally stored information about rules or fingerprints in the digital object recognition process involving the collected data and validation of the type or identity of user actions, digital content, or external objects, as reflected by the reconstruction recapturing the visual landscape.