Virtual Assistant Engine Context Construction
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Solution Overview
Problem
Existing assistive technologies are limited in their applicability across a broad spectrum of user circumstances, failing to provide contextually relevant assistance as they are often purpose-built and not adaptable to various situations.
Innovation Solution
A virtual assistant system comprising a database of assistant attributes and an engine that analyzes digital representations of objects to construct appropriate virtual assistants, enabling seamless access to relevant assistive technologies based on user context, such as healthcare, finance, or mechanics, through image, audio, or video data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If purpose-built assistive technologies are used for specific tasks, then task-specific functionality is improved, but adaptability to various user circumstances deteriorates
Solution Approach 1:
The virtual assistant system is designed to perform multiple functions across different domains (banking, healthcare, travel, etc.) through a single unified platform. The system uses object type identifiers and assistant attributes to dynamically construct appropriate virtual assistants for various tasks, eliminating the need for multiple purpose-built applications while maintaining task-specific functionality through contextual analysis of user needs and circumstances
2Ease of operation
If manual selection of assistive technologies is required, then user control is improved, but ease of operation deteriorates
Solution Approach 1:
The virtual assistant system automatically analyzes user circumstances, captures images of relevant objects, extracts object type identifiers, and constructs appropriate virtual assistants without requiring manual selection. The system serves itself by autonomously determining which assistive technology is needed based on contextual analysis, thereby eliminating time loss while maintaining user control through the ability to review and accept the automatically selected assistant
3Device complexity
If single-purpose systems are deployed, then system complexity is reduced, but versatility across different applications deteriorates
Solution Approach 1:
The virtual assistant system is segmented into distinct functional modules including image capture, object recognition, object type identifier extraction, assistant attribute compilation, and virtual assistant construction. Each module performs a specific function, maintaining system simplicity through clear separation of concerns while enabling versatility through the coordinated operation of these modular components across different application domains
Data Source
AI summary
A virtual assistant ecosystem is presented. One can instantiate or construct a customized virtual assistant when needed by capturing a digital representation of one or more objects. A virtual assistant engine analyzes the digital representation to determine the nature or type of the objects present. The engine further obtains attributes for a desirable assistant based on the type of objects. Once the attributes are compiled the engine can then create the specific type of assistant required by the circumstances.