An AI-powered tool designed to predict and promote healthy phone usage habits. By analyzing various data streams, the AI model assists the Wellspent health tech startup in creating a more conscious approach to smartphone usage in the era of social media and news sites.
noun /ˈbreɪk.θruː/
Accurate prediction of healthy or unhealthy phone usage using AI analysis of screen unlock data, session length, and motion.
Incorporating ambient sound data, smartphone usage data, and more to enhance the AI training and improve prediction accuracy.
In the era of social media and news sites, phone overuse is becoming a pressing health concern. Wellspent, a health tech startup, aims to address this issue by focusing on how we can consciously use our phones. Collaborating with their team, our goal was to tackle a significant challenge: predict whether a user's phone usage would be healthy or unhealthy based on data like screen unlock frequency, usage session duration, and types of motion (walking, running, cycling, etc.).
minutes of predicted daily phone usage reduction per user
Previous methods using simple statistics for phone usage predictions were insufficient for Wellspent's objectives. To make accurate predictions, our AI-powered tool considered various factors that would be impossible to manually analyze. By utilizing raw data streams such as ambient sound, smartphone usage, and more, the AI model was successfully trained, becoming a critical component of Wellspent's strategy. The algorithm predicts whether a user will engage in healthy or unhealthy phone usage based on historical data, promoting more conscious and healthier habits.
However here are a few common pain points that we often see, which can be solved through our programs and will lead to an AI breakthrough.
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