• Lokesh Lodha
• Ms. Shilpi Kulshrestha
• Ms. Nikita Gautam
• Ms. Nishi Sharma

In this paper, our goal was to minimize the process of Human Activity Recognition in terms of the methodology as well as the physical equipment used for the same. The research was carried out using some tri-axis accelerometers and use of adaptive learning approaches like deep neural networks. The observed output and the response were better than the previously carried out experiments both in terms of accuracy and time.

accelerometer, deep neural network, style, styling, insert.

"HUMAN ACTIVITY RECOGNITION USING DEEP NEURAL NETWORKS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.o15-o21, April-2024, Available :http://www.jetir.org/papers/JETIR2404F03.pdf

"HUMAN ACTIVITY RECOGNITION USING DEEP NEURAL NETWORKS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppo15-o21, April-2024, Available at : http://www.jetir.org/papers/JETIR2404F03.pdf