Design of a Web-Based Platform for Gamified Behavioral Data Collection with AI-Assisted Data Extraction

Abstract

Sedentary behavior and fragmented health monitoring remain key challenges in modern digital environments, particularly among university students and working professionals. Existing mobile health (mHealth) systems often provide incomplete behavioral coverage and suffer from low long-term user engagement. This paper presents the design of a web-based platform for gamified behavioral data collection with AI-assisted data extraction. The system integrates structured daily check-ins, gamification mechanisms, and an AI-based pipeline for extracting health metrics from screenshots of third-party applications. The platform combines objective sensor-derived data and subjective self-reports into a unified longitudinal dataset. A pilot deployment across eight countries involving 38 participants demonstrates the system’s ability to collect diverse health metrics, including physical activity, sleep, hydration, and screen time, while maintaining user engagement through gamification mechanisms such as points, streaks, badges, and leaderboards. The resulting dataset is intended for further machine learning-based analysis and predictive modeling of health-related outcomes.