Smart Appliance Status Summaries Using Context-Based Filtering
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Managing smart appliances becomes complex as the number of connected devices increases, leading to inefficient use of computational resources and providing users with unnecessary information, making it difficult for users to engage in meaningful interactions with automated assistants.
Innovation Solution
A method to generate and provide summary information about smart appliance statuses, filtering out less relevant information based on user context, past commands, and device types, organizing statuses into groupings to present only pertinent data in a computationally efficient manner.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If comprehensive recitation of all smart appliance statuses is provided, then complete information is delivered to the user, but the information becomes lengthy and less useful
Solution Approach 1:
The patent extracts only the most relevant appliance status information based on user context, location, and device type. The system selectively presents status data by filtering out irrelevant information, such as excluding smart lights in the user's current room or alarm systems that are already disengaged, thereby maintaining information completeness while improving usefulness.
Solution Approach 2:
The patent applies different levels of detail to different appliances based on their relevance to the user's current context. High-priority appliances receive detailed status reporting while low-priority appliances receive summarized or omitted status information, creating a localized quality of information delivery that matches user needs.
2Loss of information
If statuses of numerous appliances are verified and conveyed, then complete status information is provided, but computational resources are inefficiently used
Solution Approach 1:
The system extracts and processes only the necessary subset of appliance status data required for meaningful user interaction. By filtering out redundant status checks and focusing computational resources on high-priority appliances, the system maintains complete status verification for relevant devices while reducing overall computational energy consumption.
Solution Approach 2:
The patent implements partial action by verifying and conveying status information for only the most relevant appliances rather than all connected devices. This selective approach performs sufficient status verification to maintain system awareness while avoiding excessive computational resource allocation to low-priority devices.
3Loss of information
If detailed recitation of appliance statuses is provided, then comprehensive information is available, but user engagement in meaningful dialog is reduced
Solution Approach 1:
The system extracts and presents only the most actionable and relevant status information that enables meaningful user engagement. By filtering out excessive detail about appliances that are either visible to the user or already in expected states, the system maintains sufficient information detail while preserving the user's ability to continue meaningful dialog and issue commands.
Solution Approach 2:
The patent applies partial action by providing detailed status information only for appliances that require user attention or action. This selective detail level maintains enough information for meaningful engagement while avoiding information overload that would prevent continued user interaction.
Data Source
Figure 1
Figure 2
Figure 3
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.