Audible Order Alerts With Adaptive Speaker Selection
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Solution Overview
Problem
In noisy and complex environments like restaurants, visual alerts on user devices may be ineffective, necessitating the use of audible alerts to ensure timely user responses to trigger events, and existing systems lack efficient methods for selecting and customizing these alerts.
Innovation Solution
A user interface is generated to customize audible alerts, selecting event types, sounds, and preferences, with machine learning models determining when and how to output alerts, prioritizing them, and choosing speakers for optimal delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If visual alerts are used on user devices, then the device complexity is reduced, but the reliability of alert delivery deteriorates in noisy environments
Solution Approach 1:
The patent introduces an environmental assessment intermediary that evaluates noise levels and user context before selecting alert modality. This intermediary layer processes sensor data and determines whether visual or audible alerts should be used, resolving the contradiction by adapting to environmental conditions rather than using a fixed approach
Solution Approach 2:
The system dynamically switches between visual and audible alert modalities based on real-time environmental assessment. The alert delivery mechanism is made adaptive rather than static, allowing the system to optimize reliability for each specific context while managing overall complexity through standardized switching logic
2Reliability
If audible alerts are selected and customized, then the user response effectiveness is improved, but the device complexity increases
Solution Approach 1:
The system performs self-assessment of environmental conditions and automatically selects appropriate alert modalities and characteristics. Rather than requiring manual user configuration, the system autonomously adapts alert delivery based on sensor data and contextual information, improving effectiveness while avoiding the complexity of manual customization interfaces
Solution Approach 2:
The system incorporates feedback loops where user responses to alerts are monitored and used to refine future alert selection. This feedback mechanism allows the system to learn from past interactions and improve user response effectiveness over time without increasing structural complexity, as the learning is handled through software algorithms
3Reliability
If multiple speakers are utilized for alert output, then the coverage and reliability are improved, but the loss of time for speaker selection increases
Solution Approach 1:
The system pre-identifies and ranks available speakers based on environmental assessment and historical performance data before an alert needs to be delivered. This preliminary preparation creates a ready-to-use speaker selection list, allowing rapid deployment of multi-speaker alert output without time-consuming selection delays when alerts are actually needed
Solution Approach 2:
The patent combines multiple speaker outputs simultaneously for critical alerts, merging their capabilities to achieve broader coverage and higher reliability. By pre-coordinating multi-speaker operation and using standardized output protocols, the system achieves enhanced coverage without proportionally increasing selection time
Data Source
AI summary
Techniques described herein are directed to, among other things, determining a status change of a data object representing an order and determining attributes of the order. The systems described herein may then determine to provide an audible alert about the order based at least in part on the status change and the attributes of the order. Predefined audio data associated with the status change of the order may be identified and utilized to cause output, on a speaker of a device associated with the data object, of the audible alert about the order.