Media Guidance Application Biometric Training for IoT Devices
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Solution Overview
Problem
Current smart devices struggle to coordinate diverse features and functions effectively, particularly in media content systems, leading to user dissatisfaction due to manual adjustments and lack of personalized settings during media events, and existing IoT solutions fail to automatically determine user preferences based on biometric data.
Innovation Solution
A media guidance application that uses IoT technology to store configuration settings and biometric data, allowing network-connected objects to adjust automatically in response to media events, eliminating the need for user input by training devices through biometric feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual adjustment of device settings is required during media events, then user control over device configuration is maintained, but user experience deteriorates due to distraction and missed content
Solution Approach 1:
The system enables devices to automatically adjust their own configuration settings in response to detected media events without requiring user intervention. The media player detects events such as scene changes or important moments and autonomously coordinates with connected devices to optimize their settings, allowing the system to serve itself rather than requiring manual user control.
Solution Approach 2:
The system implements a feedback loop where the media player monitors media content for specific events, detects when adjustments are needed, and automatically communicates with network-connected devices to modify their configurations. This closed-loop feedback mechanism ensures settings are optimized at the appropriate moments without user distraction.
2Adaptability or versatility
If diverse smart devices are coordinated through basic communication techniques, then device compatibility is maintained, but coordination capability deteriorates for advanced features and functions
Solution Approach 1:
The system employs a universal coordination platform that enables diverse devices with different features and functions to work together through a common interface. The media player acts as a central coordinator that can communicate with various types of network-connected devices (lights, blinds, audio equipment, etc.) using standardized protocols, allowing advanced coordination capabilities while maintaining broad device compatibility.
3Speed
If configuration settings are pre-programmed for media events, then device response time is reduced, but user preference accuracy deteriorates without personalized training
Solution Approach 1:
The system performs preliminary configuration by pre-programming devices with potential configuration settings for various media events before actual viewing occurs. During media playback, when events are detected, devices can immediately implement these pre-prepared configurations without delay, achieving fast response times while the initial setup work was done in advance.
Solution Approach 2:
The system automatically trains itself by monitoring user manual adjustments and biometric data to refine configuration settings over time. Through self-service learning, the system observes when users manually change device settings during media events and uses this feedback, along with biometric measurements, to automatically update and personalize configuration profiles, improving accuracy without requiring explicit user programming.
4Measurement precision
If user preferences are collected through manual input, then configuration accuracy is improved, but system complexity increases due to extensive user setup requirements
Solution Approach 1:
The system automatically collects and processes user preference data through passive observation of manual adjustments and active biometric measurement, eliminating the need for complex manual setup processes. The system serves itself by autonomously analyzing user behavior patterns and physiological responses to infer preferences, reducing setup complexity while maintaining or improving preference accuracy.
Solution Approach 2:
The system replaces manual user input mechanisms with automated biometric sensing and behavioral analysis. Instead of requiring users to manually configure numerous settings, the system uses biometric devices to measure physiological responses and observes actual user adjustments, substituting mechanical/manual configuration processes with automated sensing and learning systems.
Data Source
AI summary
Systems and methods for training network-connected objects to provide configurations in association with events within media assets. A respective configuration setting of a network-connected object and a baseline biometric state of a user may be stored in a database for each event within a media asset. An event within a media asset (for display) may be detected. In response, a command may be sent to the network-connected object to implement the respective configuration setting. A determination may be made whether the user adjusts the respective configuration setting to a new configuration setting within a predefined time of the event. A biometric state of the user may be retrieved from a biometric device in response to the adjustment to a new configuration setting. If the biometric state does not correspond to the baseline biometric state, the respective configuration setting may be replaced with the new configuration setting.