Smart Appliance Status Summaries Using Context-Based Filtering
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Solution Overview
Problem
Managing the statuses of multiple smart appliances becomes complex and computationally resource-intensive, often providing users with unnecessary information that hinders meaningful interaction with automated assistants.
Innovation Solution
Implementing a system that filters and summarizes smart appliance statuses based on user context and past interactions, generating textual or graphical summaries that highlight pertinent information, allowing users to easily control and monitor relevant devices efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If comprehensive recitation of all smart appliance statuses is provided, then information completeness is improved, but user usefulness and interaction efficiency deteriorate
Solution Approach 1:
The patent extracts only the most relevant appliance statuses from the complete set of statuses. The automated assistant identifies and presents only those appliance states that are currently of interest to the user, filtering out irrelevant information. This extraction principle resolves the contradiction by providing useful information without overwhelming the user with comprehensive but unnecessary details.
Solution Approach 2:
The patent applies local quality by adapting the information presentation to the specific user context and needs. Different users receive different subsets of appliance statuses based on their individual preferences, current activities, and historical interaction patterns. This contextual adaptation ensures that each user receives information with locally optimized usefulness rather than uniform comprehensive coverage.
2Loss of information
If comprehensive recitation of all smart appliance statuses is provided, then information completeness is improved, but computational resource consumption increases
Solution Approach 1:
The system extracts only the necessary subset of appliance statuses for presentation to the user, avoiding the computational overhead of processing and transmitting all appliance data. By identifying and extracting only relevant statuses based on user context and preferences, the system reduces computational resource consumption while maintaining information completeness for what matters to the user.
Solution Approach 2:
The patent implements partial action by providing a selective subset of appliance status information rather than complete coverage. This partial presentation is optimized to include only the most relevant statuses, reducing the computational burden of data processing, transmission, and presentation while still satisfying user information needs for currently relevant appliances.
3Loss of information
If comprehensive recitation of all smart appliance statuses is provided, then information completeness is improved, but dialog reengagement capability deteriorates
Solution Approach 1:
The patent extracts and presents only the most relevant appliance statuses in a concise format that leaves room for user follow-up questions. By selectively presenting key information rather than exhaustive details, the system maintains user engagement by inviting further interaction to explore specific appliances of interest, thereby preserving dialog reengagement capability.
Solution Approach 2:
The system uses partial action by providing a curated subset of appliance statuses that serves as an effective conversation starter rather than a complete information dump. This selective presentation maintains user curiosity and engagement by highlighting relevant appliances while leaving opportunities for users to ask follow-up questions about specific devices, thus enhancing dialog reengagement.
Data Source
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AI summary
Implementing methods to provide a shortened textual summary that includes status information that is most pertinent to the user for a plurality of connected smart appliances. The method includes determining a list of current statuses for a plurality of enabled smart appliances and filtering the list to remove statuses that may not be of interest to the user. The filtering of the list is based on a current context of the requesting user and one or more previous contexts of the user. The resulting filtered statuses are then converted to textual snippets, summarized, and provided to the user via one or more output devices.