Human Activity Recognition

• Author(s): Pramodh Yadav M ; Purvika S ; Chatur S
• Paper ID: 1705380
• Page: 277-283
• Published Date: 16-01-2024
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 7 Issue 7 January-2024

Abstract

The Human Activity Recognition (HAR) system is a prominent research area that aims to develop intelligent algorithms and systems capable of automatically identifying and classifying human activities based on sensor data. This project report provides a thorough exploration of the key aspects involved in the design, implementation, and evaluation of a Human Activity Recognition system. The report begins with a comprehensive review of the existing literature, covering the fundamental concepts, methodologies, and recent advancements in HAR. It discusses various sensor modalities commonly used for activity recognition, including accelerometer, gyroscope, and magnetometer data. Special attention is given to machine learning and deep learning techniques employed in the recognition process. The project involves the development of a prototype HAR system using state-of-the-art techniques. The implementation utilizes a dataset representative of diverse human activities to train and test the system. The chosen methodology is presented in detail, highlighting the selection and preprocessing of sensor data, feature extraction, and the training of machine learning or deep learning models.

Citations

IRE Journals:
Pramodh Yadav M , Purvika S , Chatur S "Human Activity Recognition" Iconic Research And Engineering Journals Volume 7 Issue 7 2024 Page 277-283

IEEE:
Pramodh Yadav M , Purvika S , Chatur S "Human Activity Recognition" Iconic Research And Engineering Journals, 7(7)