PERSONALISED INFORMATION SYSTEM FOR HEALTH EATING AND WEIGHT LOSS

Abstract

The rise in health awareness has driven the need for digital solutions to support personalised dietary management and weight loss. Existing digital health solutions lack personalised dietary and weight management strategies, which limits their effectiveness. This study develops and evaluates a Personalised Information System for Healthy Eating and Weight Loss, incorporating structured health assessments, AI-driven meal planning, and exercise recommendations tailored to user-specific data such as BMI, dietary preferences, and activity levels. Using the Waterfall model, the system was designed and tested through an online survey involving 30 respondents, which assessed five key factors: ease of Use, Usefulness, User Interface Design, User Satisfaction, and System Performance. Results indicate that 78.7% of users found the system highly useful, 86.7% praised its intuitive interface, and 90% expressed overall satisfaction. Correlation analysis reveals a strong positive relationship (r = 0.72) between ease of use and perceived usefulness, underscoring the potential of this relationship to foster long-term engagement. While digital health tools often lack adaptive recommendations, this study addresses this gap by integrating real-time feedback and AI-driven customisation. Future enhancements include integrating wearable devices and expanded meal plan options to optimise the user experience.