IoT Solution for Physical Activity Monitoring with Gamification and Machine Learning
Igor Gabriel D. Rocha, Joao M. Vilas Boas Da Silva, Thales Adriel S. De Araújo, Danilo Cortez Gomes, Andouglas Silva · 2025
In this work, we propose an intelligent system for detecting physical activities, designed to integrate with interactive games that encourage exercise. The system employs wearable IoT sensors, such as the MPU-6050, to capture real-time data from accelerometers and gyroscopes. Advanced preprocessing techniques are applied to normalize and optimize sensor data for activity analysis. An LSTM (Long Short-Term Memory) model is used to classify the movements, enhancing the system’s ability to accurately recognize physical activities. Additionally, a gamified application leverages this system to provide an engaging platform for users to perform and track physical exercises.