Sensor-Based Template Development for Personalized Outcome Plans
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Solution Overview
Problem
Existing systems fail to effectively exploit the vast amount of personal data collected through social networking sites, such as blogs and microblogs, to develop personalized plans that help users achieve specific target outcomes, as this data is scattered across multiple platforms and difficult to utilize for achieving desired goals.
Innovation Solution
A computationally implemented method and system that provides reported aspects from source users, originally sensed by sensors, to develop templates that end users can emulate to achieve target outcomes, by identifying relevant aspects and creating schedules or activity plans tailored to individual needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If personal data from social networking sites is collected and utilized, then personalized plans can be developed to help users achieve target outcomes, but the data is scattered across multiple platforms and difficult to utilize
Solution Approach 1:
The patent introduces an intermediary system that acts as a mediator between scattered social networking data sources and the template development process. This intermediary aggregates reported aspects from multiple platforms, processes them through sensor-originated data, and delivers consolidated information to template developers, thereby resolving the complexity of direct multi-platform data collection while enabling personalized plan creation
2Reliability
If sensor data is used to develop templates, then the reliability of achieving target outcomes is improved, but the difficulty of detecting and measuring relevant aspects increases
Solution Approach 1:
The patent implements self-service mechanisms where sensors automatically detect and report aspects without requiring manual intervention. The system autonomously collects sensor-originated reported aspects, processes them through computational methods, and generates templates based on detected patterns, thereby reducing the difficulty of aspect detection while maintaining high reliability in achieving target outcomes
Data Source
AI summary
A computationally implemented method includes, but is not limited to: providing one or more reported aspects associated with one or more source users that were originally reported by one or more sensors; and developing one or more templates designed to facilitate one or more end users to achieve one or more target outcomes when one or more emulatable aspects indicated by the one or more templates are emulated, the development of the one or more templates being based at least on a portion of the one or more reported aspects In addition to the foregoing, other method aspects are described in the claims, drawings, and text forming a part of the present disclosure.