Ubiquitous Event Mining to Enhance Personal Health
This work addresses the challenge of fragmented health monitoring systems for individuals seeking optimized daily health actions, though it appears incremental in combining existing technologies.
The paper tackles the problem of integrating events from various ubiquitous systems to derive actionable causal relationships for personal health guidance, proposing a method that enhances user experience by leveraging these relationships.
Advances in user interfaces, pattern recognition, and ubiquitous computing continue to pave the way for better navigation towards our health goals. Quantitative methods which can guide us towards our personal health goals will help us optimize our daily life actions, and environmental exposures. Ubiquitous computing is essential for monitoring these factors and actuating timely interventions in all relevant circumstances. We need to combine the events recognized by different ubiquitous systems and derive actionable causal relationships from an event ledger. Understanding of user habits and health should be teleported between applications rather than these systems working in silos, allowing systems to find the optimal guidance medium for required interventions. We propose a method through which applications and devices can enhance the user experience by leveraging event relationships, leading the way to more relevant, useful, and, most importantly, pleasurable health guidance experience.