Set Top Box Contextual Standby via Sensor Fusion
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Solution Overview
Problem
Current Set Top Box (STB) systems lack the ability to automatically control modes based on contextual and sensor information, specifically failing to detect user presence or absence for intelligent power management and content streaming/recording decisions, relying on static and closed models that do not integrate external or internal sensors effectively.
Innovation Solution
A system and method that enables STBs to connect with external smart sensors via wireless connectivity, using cloud computing and AI/ML to identify user presence or absence, and adjust modes such as standby or streaming based on usage preferences and sensor data, including fingerprint, microphone, and accelerometer inputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If STB uses static mode control without sensor integration, then device complexity is reduced, but adaptability to user presence and contextual information deteriorates
Solution Approach 1:
The patent embeds multiple sensor systems (motion sensors, proximity sensors, biometric sensors) within the STB device structure, creating a nested configuration where sensors are integrated into the existing device architecture. This allows the STB to detect user presence and contextual information without requiring a completely new system design, thereby improving adaptability while controlling the increase in device complexity.
Solution Approach 2:
The patent implements a multi-functional sensor integration approach where the STB uses the same sensor array for multiple purposes: detecting user presence, identifying user identity through biometric data, and determining contextual information such as viewing habits and preferences. This universal use of sensors improves adaptability across different scenarios while avoiding the need for separate dedicated devices for each function.
2Reliability
If STB continuously monitors sensor data and contextual information, then user experience and mode control accuracy are improved, but energy consumption increases
Solution Approach 1:
The patent implements periodic sampling of sensor data instead of continuous monitoring. The STB checks sensor inputs at predetermined intervals and uses this periodic data to determine user presence and update mode control decisions. This approach maintains reliable mode control accuracy by frequently enough sampling while significantly reducing energy consumption compared to continuous monitoring.
Solution Approach 2:
The patent employs preliminary analysis of sensor data patterns to predict user presence and preferences before actual viewing sessions. By pre-processing and storing contextual information during periods when the STB is not actively controlling modes, the system prepares decision-making data in advance. This allows the STB to make accurate mode control decisions during operation without requiring intensive real-time processing, thereby reducing energy consumption while maintaining reliability.
3Extent of automation
If STB integrates multiple sensors and cloud computing, then contextual awareness and automatic mode control are improved, but device complexity increases
Solution Approach 1:
The patent introduces a cloud computing platform as an intermediary between the STB sensors and the mode control logic. The STB collects sensor data and contextual information, transmits it to the cloud platform for advanced processing and pattern recognition, and receives automated mode control commands in return. This intermediary approach enables high-level automation through sophisticated cloud-based AI and machine learning while keeping the STB device complexity manageable by offloading complex processing tasks.
Solution Approach 2:
The patent divides the automatic mode control system into segmented functional modules: sensor data acquisition module, cloud communication module, mode control execution module, and user profile management module. Each module performs a specific function and can be independently developed, tested, and maintained. This segmentation of the automated control system reduces device complexity by organizing complex functionality into manageable, modular components while preserving the extent of automation through their coordinated operation.
Data Source
AI summary
A system and method for automatically controlling a mode on a set top box [100]. The method comprises identifying, from a set of pre-stored contextual information, a target pre-stored contextual information associated with an entity. The method further comprises identifying, a usage preference associated with the entity based on the target pre-stored contextual information. Thereafter the method leads to identifying, one of a presence and an absence of the entity in the vicinity of the set top box [100] based on the target pre-stored contextual information and a sensor data. The method thereafter comprises automatically controlling, the mode on the set top box [100] based on the usage preference associated with the entity and one of the presence and the absence of the entity in the vicinity of the set top box [100].