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International Journal of Applied Research
  • Multidisciplinary Journal
  • Printed Journal
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ISSN Print: 2394-7500, ISSN Online: 2394-5869, CODEN: IJARPF

IMPACT FACTOR (RJIF): 8.4

Vol. 9, Special Issue 4, Part C (2023)

Human activity recognition using neural networks

Human activity recognition using neural networks

Author(s)
Manisha Gupta
Abstract
This paper presents research made for independent daily life assistance of elderly or persons with disabilities using IoT technologies. The scope is to develop a system that allows living for as long as possible in familiar environment. This will be possible by wider spread of assistive technologies and the internet of things (IoT). With aim to bring together latest achievements in domain of Internet of things and assistive technologies in order to develop a complex assistive system with adaptive capability and learning behavior. We can use IoT technologies to monitor in real time the state of a patient or to get sensitive data in order to be subsequently analyzed for a medical diagnosis. I present the state of my work related to the development of an assistive assembly consisting of a smart and assistive environment, a human activity and health monitoring system, an assistive and telepresence robot, together with the related components and cloud services.
Pages: 78-84  |  219 Views  72 Downloads


International Journal of Applied Research
How to cite this article:
Manisha Gupta. Human activity recognition using neural networks. Int J Appl Res 2023;9(4S):78-84.
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