Development of Health Story Web Application Using Artificial Intelligence for Food Label Analysis and Eating Behavior Prediction to Recommend Personalized Exercise
Keywords:
Web Application, Artificial Intelligence (AI), Food Label Analysis, Eating Behavior, Exercise RecommendationAbstract
This paper presents the development of the Health Story web application, an innovative platform designed to promote personalized health management through the integration of artificial intelligence (AI) and behavioral psychology. Addressing the challenges in tracking dietary intake and personalizing exercise recommendations, the application features an OCR-powered food nutrition label scanning system for real-time food analysis and an AI-driven module for predicting eating behaviors and recommending personalized exercise patterns. It further incorporates an interactive, blog-based system to foster self-tracking and leverage narrative psychology for enhanced user engagement and motivation in achieving individual health goals. Developed with Next.js, Tailwind CSS, and a Directus/PostgreSQL backend, the system integrates advanced AI for weight loss outcome prediction. Comprehensive evaluation with 30 users across five key areas—user capability, system capability, system quality and efficiency, design, and security—demonstrated strong performance, achieving an average satisfaction score of 4.79±0.41. These results confirm that the Health Story application effectively meets its objectives, offering a sustainable and innovative solution for personalized digital health.
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