International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

A Survey Paper on Smart Human Activity Detection Using Yolo

Prof. Aparna ThakreProfeesor, Computer Engineering, Siddhant College of Enguneering Technical Campus, Sudumbhare, Pune, IndiaAtharav DeshpandeStudent, Computer Engineering, Siddhant College of Enguneering Technical Campus, Sudumbhare, Pune, IndiaRohan KadamStudent, Computer Engineering, Siddhant College of Enguneering Technical Campus, Sudumbhare, Pune, IndiaAjay UjagareStudent, Computer Engineering, Siddhant College of Enguneering Technical Campus, Sudumbhare, Pune, IndiaAbhishek jadhavStudent, Computer Engineering, Siddhant College of Enguneering Technical Campus, Sudumbhare, Pune, India

Vol 7 No (2023): Volume 7, Special Issue of ICRTET- 2023 | Pages: 236-241

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 16-07-2023

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Abstract

A simple operational model could allow one person to monitor all around us to ensure security and privacy, while maintaining cost and performance of management and getting it right. This inspection with real-time video monitoring function can be sent to hospitals or nursing homes for the sick and elderly, as well as various people working in important area such as airport. In we decided to use the YOLOv4 (You Only One See One) algorithm, which is the newest and fastest of the total algorithms for fast analysis of actions and accurate results when dealing with complex human behaviour. This method uses a bounding box to indicate the action. In these cases, we collected 4,674 different data from different hospitals or different cases, making the most accurate use of one of the largest datasets used in this type of project. When we research, we divide our actions into three different classes: standing, sitting, and walking. Model can control and analyse the activities of many patients or other normal people, and support can monitor the activities of many. After completing three projects, the model achieved an average accuracy of 94.6667.

Keywords

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Citation of this Article

Prof. Aparna Thakre, Atharav Deshpande, Rohan Kadam, Ajay Ujagare, Abhishek jadhav, “A Survey Paper on Smart Human Activity Detection Using Yolo” in proceeding of International Conference of Recent Trends in Engineering & Technology ICRTET - 2023, Organized by SCOE, Sudumbare, Pune, India, Published in IRJIET, Volume 7, Special issue of ICRTET-2023, pp 236-241, June 2023.

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