Revolutionizing Nutritional Management Through Food Scanning And Object Detection: A New Android Application For Adults
Abstract
The proliferation of mobile technology has led to the development of numerous applications aimed at promoting a healthy lifestyle, such as monitoring food intake and providing suggestions for a healthy diet. However, many of these apps require significant time and effort to manually input food items. To address this issue, we present the development of a new machine learning-based Android application that simplifies food management for adults, especially those in rural environments or with limited technical knowledge. The proposed application uses AWS Rekognition to scan food items and obtain nutritional information, such as the percentage of diabetes, cholesterol, and other key factors affecting health. The app also utilizes image recognition to detect fruits and vegetables, providing their nutritional contents. Additionally, for packed food items, the app scans the ingredients list to predict vital information
regarding the user’s health. The machine learning algorithm in the application helps in improving the accuracy of the scanned information and provides better nutritional recommendations. The application is designed to have a simple and user-friendly
interface, providing a convenient solution for managing food intake.
Keywords:
diet, scan, detection, machine learningPublished
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