DESIGN AND IMPLEMENTATION OF A PERSUASIVE MOBILE APPLICATION FOR PROMOTING THE CONSUMPTION OF FIBER AND YEAST MEALS

This study examines the promotion of the consumption of fiber and yeast meals through a persuasive application with the use of machine learning to provide Image Recognition. While studies have established the remarkable health effects of meals rich in fiber and yeast, there is a lack of evaluation of the influence of interventions delivered via digital media on dietary behavior. This study evaluates the potential of Mobile applications in promoting wholesome eating behaviors using such persuasive tools as reminders and tracking of progress.To determine user behavior and attitudes towards mobile diet programs, a survey involving 103 respondents was carried out. Descriptive statistics were used to analyze the data, indicating that most respondents ate fiber-rich meals regularly or weekly but lacked awareness and motivation to eat continuously. The results showed that the combination of persuasive technologies with machine learning was likely to improve healthy eating adherence greatly. Following the system analysis procedure, a mobile application was developed and designed with React.js and Tailwind as the frontend, Node.JS as the backend and Firebase Firestore as the real-time data storage and best user tracking database. The app comes equipped with image detection for meal identification, and machine learning-based progress tracking. Authentication and data encryption security capabilities were included to protect user data. There was a post-design evaluation, measuring the usability, security, and efficacy of the app. Statistical tests and T-tests set up a better capacity to track fiber and yeast intake, awareness, and dietary modification, all significantly different. The research suggests that there is potential for a well-designed, interactive mobile app to facilitate long-term healthy eating and offer scalable, ;flexible solutions to broader public health interventions.