Communication Mode Selection via Environmental Context Adaptation
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Solution Overview
Problem
Existing communication systems lack the ability to dynamically and automatically select the most appropriate communication mode based on environmental factors, leading to unwanted voice calls or text messages in inappropriate situations, such as during meetings or while driving.
Innovation Solution
A system and method for real-time automatic communication mode selection using a crowdsourcing server that collects environmental data from user equipment devices to generate machine learning models for determining preferred communication modes, allowing for dynamic conversion between voice and text-based communications based on location, time, and user preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system automatically selects communication mode based on environmental factors, then the appropriateness of communication delivery is improved, but the system complexity increases
Solution Approach 1:
The patent introduces an intermediary system (server or device) that collects environmental data, processes it through machine learning models, and determines the appropriate communication mode. This intermediary handles the complexity of environmental assessment and mode selection, relieving the burden from individual communication devices while ensuring reliable and context-appropriate communication delivery.
2Adaptability or versatility
If the system dynamically converts communication modes in real-time, then the adaptability to environmental context is improved, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-collecting environmental data and pre-processing it through machine learning models to determine communication modes before actual communication events occur. This advance preparation reduces the processing time required at the moment of communication, allowing for rapid mode conversion while maintaining high adaptability to environmental context.
3Measurement precision
If the system collects environmental data from multiple sources to improve mode selection accuracy, then the precision of communication mode determination is improved, but the data collection and processing complexity increases
Solution Approach 1:
The patent segments the data collection and processing tasks across multiple independent sources and systems. Different environmental factors (location, time, user activity) are collected from separate sources, processed independently through specialized machine learning models, and then integrated to determine the final communication mode. This segmentation improves measurement precision through comprehensive data gathering while managing complexity through modular processing architecture.
Data Source
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AI summary
Disclosed is an apparatus and method for automatic communication mode selection. The method may include detecting a communication by a user equipment. The method may also include determining one or more characteristics associated with the communication, wherein the one or more characteristics comprise user environmental data, public environmental data, or a combination thereof associated with the communication. Furthermore, the method may include selecting a mode for the communication that is different from an original mode of the detected communication based on the one or more characteristics