LifeLens combines a wearable device with a mobile app and cloud-based analytics platform.

The wearable continuously records various health metrics such as activity levels, sleep patterns, and environmental exposure (e.g., UV, air quality).

Users input lifestyle data like diet and stress levels manually or via integration with third-party apps.

The cloud platform uses artificial intelligence to process long-term data, analyzing patterns and identifying correlations between past behavior and current health conditions.

It provides users with detailed reports and actionable insights, enabling tailored health advice and either corrective or preventative interventions guided by historical data comparison.

LifeLens offers a unique ability to analyze and understand the long-term health impacts of past lifestyle and environmental factors.

By providing a holistic view of personal health history, it enables precise interventions, enhancing personal health literacy and reducing healthcare costs associated with unexplained health issues.

The concept leverages existing wearable technology and cloud-based analytics while advancing them through AI-driven retrospective analysis.

Technical challenges center around data interoperability and ensuring robust historical data accuracy.

Costs include hardware development, data infrastructure, and potential regulatory approvals related to health data privacy.