A smart tableware-based meal information collection system using machine learning

In recent years, due to lifestyle-related diseases, people have paid more and more attention to the management of healthy meals. Some meal management systems are entering people's lives gradually. Existing studies have found that the proper meal habits, such as a correct meal sequence, can help prevent disease to a certain extent. In this paper, we introduce the smart tableware consisting of an acceleration sensor and a pressure sensor to obtain meal information such as meal sequence and meal content automatically. Moreover, feature extraction is performed on the meal information captured by sensors, and the machine learning algorithms are used to analyse and process the information. Finally, the meal content and meal sequence are fed back to the user to help people prevent diseases affected by lifestyle habits such as obesity and diabetes. In the experiment, we compare a variety of different machine learning algorithms and analyse the experimental results.