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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
Call For Paper - Volume 14 | Issue 3 | Month- March 2026
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Published Paper Details:
Paper Title
Enhancing Human Activity Recognition with Different AI Models Using Mobile Sensor Data
Authors
RAHUL KUMAR GOUR, Dr DIVYARTH RAI
Keywords
Human Activity Recognition, HAR, Mobile Sensors, Logistic Regression, Artificial Neural Networks, Long Short-Term Memory, GRU, Deep Learning.
Abstract
Human Activity Recognition (HAR) plays a crucial role in health monitoring, smart environments, and human-computer interaction. This study investigates four machine learning models Logistic Regression, Artificial Neural Networks (ANN), Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRU) for activity identification using mobile sensor data. The dataset comprises gyroscope and accelerometer readings from smartphones. Preprocessing techniques such as feature extraction, noise reduction, and normalization are applied to enhance model performance. The results indicate that while Logistic Regression provides a reliable baseline, ANN, LSTM, and GRU models outperform it, particularly in capturing temporal dependencies. Among the evaluated models, The GRU model delivers the best performance, achieving an accuracy of 97.2% and a loss of 0.28%.
IJCRT's Publication Details
Unique Identification Number - IJCRT2412714
Paper ID - 274501
Page Number(s) - g504-g510
Pubished in - Volume 12 | Issue 12 | December 2024
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
RAHUL KUMAR GOUR, Dr DIVYARTH RAI, "Enhancing Human Activity Recognition with Different AI Models Using Mobile Sensor Data", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 12, pp.g504-g510, December 2024, Available at :http://www.ijcrt.org/papers/IJCRT2412714.pdf
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Submit Manuscript Online Impact Factor: 7.97 Review Results : Within 02-03 Days Paper Publication : Within 02-03 Days
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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