AI AND ANDROID APP BASED VEGETABLES NUTRITION PREDICTION SYSTEM

AI AND ANDROID APP BASED VEGETABLES NUTRITION PREDICTION SYSTEM

1 SHRUTI M T , 2 SUMANTH B M
1,Assistant Professor Department of MCA, BIET, Davangere

2,Student, Department of MCA, BIET, Davangere

ABSTRACT
The increasing awareness of health and nutrition has led to a significant demand for tools that provide accurate nutritional information about food items. This paper presents the design and development of an AI and Android app-based Vegetables Nutrition Prediction System (VNPS). The VNPS leverages advanced machine learning algorithms and an extensive vegetable nutrition database to offer users precise nutritional information about a wide variety of vegetables. The system comprises a user- friendly Android application that utilizes AI to predict and display the nutritional content of vegetables based on user inputs such as the type, quantity, and preparation method. Key features of the VNPS include real-time nutritional analysis, customizable user profiles, and integration with health and fitness trackers. The AI component of the system employs machine learning techniques to continuously improve the accuracy of nutritional predictions by learning from user feedback and new data entries. A comprehensive evaluation of the VNPS demonstrates its effectiveness in providing reliable nutritional information, which can aid users in making informed dietary choices. The evaluation includes a comparison with existing nutrition prediction tools, highlighting the VNPS's superior accuracy and user satisfaction. Additionally, the app's intuitive interface and seamless user experience make it accessible to a broad audience, including individuals with limited technical expertise.

Keywords: AI, Android app, nutrition prediction, vegetables, machine learning, health informatics, dietary choices, public health.