Streaming Media Device Automatic User Identification via BLE Signals
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Solution Overview
Problem
Current technologies face challenges in accurately identifying users for personalized content recommendations and customized viewing experiences in network-based media streaming, as they often rely on manual login or fail to adapt when users enter or leave the vicinity of a streaming device without proper detection.
Innovation Solution
A method and system that use network-oriented and interaction-based user identification techniques, such as Bluetooth signals, geolocation, and biometric sensing, to automatically detect users within a threshold vicinity of a streaming media device, allowing for real-time configuration of user settings and content delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual login is used for user identification, then system security is maintained, but user convenience and automatic adaptation deteriorate
Solution Approach 1:
The system performs user identification automatically without requiring manual login. The streaming media device detects mobile devices in the vicinity, retrieves associated user profiles, and configures settings autonomously, allowing the system to serve itself in the user identification process.
Solution Approach 2:
The patent replaces manual mechanical interaction (typing login credentials) with electronic detection methods. Bluetooth Low Energy (BLE) signals and other electronic detection mechanisms substitute for the mechanical act of manual login, enabling automatic user identification.
2Measurement precision
If network-based detection methods are implemented, then user identification accuracy improves, but energy consumption increases
Solution Approach 1:
The system uses Bluetooth Low Energy (BLE) technology which operates at lower power levels compared to traditional Bluetooth. By changing the energy parameter of the detection signal to a lower-energy format, the system maintains detection accuracy while reducing power consumption on mobile devices.
Solution Approach 2:
Instead of continuous monitoring, the system uses periodic discovery signals transmitted at intervals. This periodic approach maintains user identification accuracy while significantly reducing the energy consumption compared to continuous active scanning.
3Reliability
If continuous user detection is performed, then user presence accuracy improves, but system resource consumption increases
Solution Approach 1:
The streaming media device transmits discovery signals at periodic intervals rather than continuously. This periodic transmission maintains reliable user presence detection by regularly updating the detection status while conserving system energy resources during periods between detections.
Solution Approach 2:
The system maintains user identification state continuously through periodic updates rather than restarting detection each time. This approach ensures reliable user presence detection while minimizing energy consumption by maintaining context between periodic detection cycles.
Data Source
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AI summary
Disclosed herein are system, method, and computer program product embodiments for network-based user identification. An embodiment operates by transmitting a discovery signal over a network, and receiving a response to the discovery signal from a mobile device coupled to the network. Based on the response it is determined whether the mobile device is within a threshold vicinity of the streaming media device. Which if it is, user settings corresponding to ta user of the mobile device, which may also be a user of another device associated with the settings are determined. The other device is then configured based on the user settings.