Location-Triggered Credential Rendering for Low-Latency Access
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Solution Overview
Problem
Users face challenges in accessing locations requiring credentials due to background noise, limited dexterity, and inefficient use of computing device resources when interacting with automated assistants for document retrieval.
Innovation Solution
An automated assistant proactively activates input processing features when a user is near a location requiring credentials, determining the needed credentials through data analysis and rendering them on the device interface, optimizing speech recognition and power usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the user preemptively navigates their device for a credential document, then the credential can be ready when needed, but computing device resources are wasted during unnecessary rendering periods
Solution Approach 1:
The automated assistant proactively determines the user's location and activates input processing features before the user arrives at the location, preparing credential information in advance without requiring the user to manually navigate or preemptively access documents. This reduces retrieval latency while avoiding unnecessary resource consumption by only activating processing when and where needed.
Solution Approach 2:
The system automatically monitors location data and determines when credentials are needed without user intervention. The automated assistant self-manages the activation of input processing features and credential retrieval based on location characteristics, eliminating the need for users to manually prepare or navigate to credential documents.
2Measurement precision
If automatic speech recognition is activated continuously, then speech commands can be recognized accurately, but power consumption increases
Solution Approach 1:
Instead of continuous activation, the automated assistant periodically activates input processing features based on location-triggered events. When the user approaches a location requiring credentials, the system activates speech recognition temporarily to process the security guard's request, then deactivates it when not needed, maintaining accuracy while reducing power consumption.
Solution Approach 2:
The system activates input processing features in advance of when they are actually needed, based on location data indicating the user is approaching a secure location. This preliminary activation ensures speech recognition is ready when the security guard makes a request, while avoiding continuous operation and associated power consumption.
3Use of energy by moving object
If the user waits in line without preparing credentials, then device resources are conserved, but latency increases when credentials are needed
Solution Approach 1:
The automated assistant proactively determines when the user is approaching a location requiring credentials and activates input processing features before the user reaches the security checkpoint. This preliminary action reduces credential presentation delay without requiring the user to manually prepare, and the system only consumes resources when actually approaching a secure location.
4Ease of operation
If the automated assistant processes multiple spoken utterances, then the user can express their needs, but interaction time increases
Solution Approach 1:
The system proactively determines location and activates input processing before the user needs to interact, so when the security guard requests credentials, the information is already prepared or can be quickly retrieved. This reduces the number of utterances needed and total interaction time while maintaining user flexibility in how they communicate their needs.
Data Source
AI summary
Implementations relate to an automated assistant that can proactively detect and respond to a request for credentials. Characteristics of an entity requesting the credentials can be preemptively determined by the automated assistant using data that may be provided by the user or other previous visitors to a location. For example, the automated assistant can determine that the entity may expressly request certain information from a user when the user arrives at the location. Based on this determination, the automated assistant can operate to initialize an interface of a computing device of the user, when the user is determined to be at or near the location. For example, an audio interface of the computing device can be initialized to capture an audible request from a person who views credentials before granting access to a feature of the location.


