Smart Shoe Health & Activity Dataset

A ~5,000-row, open-access CSV compiled from IoT smart shoes that stream multi-sensor health and activity data to the cloud via MQTT. Each record combines demographics (age, sex), lifestyle (fast-food frequency), and computed body metrics (BMI) with shoe-embedded sensor readings: heart rate & SpO₂ (Max30100), body temperature (LM35), foot pressure (FSR), and step count (accelerometer). The dataset was curated for machine-learning experiments (e.g., XGBoost, CatBoost, SVM) to classify health status and support personalized recommendations, making it suitable for supervised learning, feature correlation studies, and real-time monitoring prototypes.