CaloriQ is an AI-powered smart plate designed to automate and simplify nutritional self-monitoring by combining computer vision and precision weight sensing. The system addresses the limitations of traditional dietary tracking methods, which often rely on manual portion estimation and user input, leading to significant inaccuracies. By automatically recognizing food items, measuring portion sizes, and calculating caloric and macronutrient values in real time, CaloriQ enhances nutritional awareness while minimizing user effort.

The system integrates a segmented smart plate equipped with load cell sensors, an embedded microcontroller, and a mobile application that delivers personalized dietary feedback. Food recognition is performed using machine learning–based image analysis, while weight measurements are acquired through high-precision sensors and synchronized with classification results. The platform provides users with clear visual feedback, meal history tracking, and reference-based nutritional insights aligned with recommended dietary values. It also features a Diabetic Mode for glucose tracking. Designed to be cost-efficient, scalable, and culturally

inclusive, CaloriQ supports healthier eating habits and aligns with global health-related Sustainable Development Goals by promoting informed dietary choices and improved nutrition literacy.