Pre-Call Content Prioritization for Faster Incoming Call Decisions
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Solution Overview
Problem
Wireless communication systems face inefficiencies due to users receiving unwanted calls, leading to wasted network resources and degraded call quality, as users often need to access external information during calls to recall relevant details, causing prolonged calls and excess bandwidth usage.
Innovation Solution
Implementing a pre-call analysis and content prioritization system that generates and presents relevant information to users before accepting a call, using contextual data and machine learning models to provide pre-call content, reducing the need for external information retrieval during calls and optimizing network usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If users access external information during calls to refresh recollection, then call information completeness is improved, but call duration increases and network bandwidth is excessively consumed
Solution Approach 1:
The system performs preliminary actions by fetching and presenting relevant information to the user before the call starts. The pre-call interface proactively retrieves data from calendars, messages, contacts, and other applications based on the called party's identity, so the user has all necessary information ready before the call begins, eliminating the need to access external sources during the call.
Solution Approach 2:
The pre-call interface acts as an intermediary between the user and external information sources. Instead of the user directly accessing multiple applications during the call, the pre-call interface consolidates and presents relevant information from various sources in a unified manner, reducing the need for users to switch between applications and prolong the call.
2Loss of information
If users access external information during calls, then call information completeness is improved, but network bandwidth usage increases
Solution Approach 1:
The system performs preliminary information retrieval before the call starts, when network conditions may be more favorable and user attention is not divided. By fetching data in advance during the pre-call phase, the system reduces the need for additional network requests during the call itself, thereby conserving network bandwidth.
Solution Approach 2:
The pre-call interface performs selective information retrieval based on relevance to the called party and user context. It fetches only the most pertinent information from various sources rather than all available data, optimizing network bandwidth usage by avoiding unnecessary data transfers while still providing sufficient information for the call.
3Reliability
If pre-call content is fetched and presented to users, then user decision quality is improved, but device processing resources are consumed
Solution Approach 1:
The system performs content fetching and analysis in advance during the pre-call phase, when the device has full processing resources available and the user is not engaged in the call. This preliminary processing consolidates resource consumption before the call begins, allowing the device to operate more efficiently during the actual call without dividing processing attention.
Solution Approach 2:
The pre-call interface creates a simplified copy or summary of relevant information from various sources and presents it in an easily consumable format. Instead of requiring the user to access and analyze multiple complex applications during the call, the system provides a curated summary that captures essential information, reducing the processing burden while maintaining decision quality.
4Loss of information
If pre-call content is fetched in advance, then information availability during calls is improved, but device memory resources are consumed
Solution Approach 1:
The system fetches and prepares information in advance during the pre-call phase, making it immediately available when the user needs it. By pre-loading relevant data into memory before the call starts, the system ensures information is accessible during the call without requiring additional memory allocations that would compete with call processing resources.
Solution Approach 2:
The pre-call interface selectively fetches only the most relevant information based on the called party's identity, user context, and predicted call needs. It avoids fetching excessive or irrelevant data, thereby optimizing memory resource usage while still providing sufficient information for the user to make informed decisions about the call.
Data Source
AI summary
Implementations set forth herein relate to generating a pre-call analysis for one or more users that are receiving and/or initializing a call with one or more other users, and/or prioritizing pre-call content according to whether security-related value was gleaned from provisioning certain pre-call content. One or more machine learning models can be employed for determining the pre-call content to be cached and/or presented prior to a user accepting a call from another user. Feedback provided before, during, and/or after the call can be used as a basis from which to prioritize certain content and/or sources of content when generating pre-call content for a subsequent call. Other information, such as contextual data (e.g., calendar entries, available peripheral devices, location, etc.) corresponding to the previous call and/or the subsequent call, can also be used as a basis from which to provide a pre-call analysis.