Home daily living activity monitoring for elderly

Abstract

This project aims to develop a comprehensive system for monitoring the daily activities of elderly individuals using Artificial Intelligence (AI) technology. The system utilizes Internet of Things (IoT) devices, sensors, and data analytics to provide valuable insights on the well-being and safety of seniors within their homes, enabling effective real-time monitoring. The project utilizes the ESP32 microcontroller. MPU6050 sensors are employed to provide motion sensing, orientation, acceleration measurement, and angular velocity. We utilized machine learning algorithms, specifically the 1D Convolutional Neural Network (CNN) model, to process, analyze, and classify the monitored individual's daily activities.