Detecting Human Activities Based on Motion Sensors in IOT Using Deep Learning

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MIRZAEI A.; FARAJI F.

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Paper Information

Journal: NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, B- MUHANDISI -I KAMPYUTAR Year:2022 | Volume:19 | Issue:4 Page(s): 313-324

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Title

Detecting Human Activities Based on Motion Sensors in IOT Using Deep Learning

Author(s)

MIRZAEI A. | FARAJI F. | Issue Writer Certificate

Keywords

Human activity detection

deep learning

machine learning

DNN

IoT

Abstract

Control of areas and locations and motion sensors in the Internet of Things requires continuous control to detect human activities in different situations, which is an important challenge, including manpower and human error. Permanent human control of IoT motion sensors also seems impossible. The IoT is more than just a simple connection between devices and systems. IoT information sensors and systems help companies get a better view of system performance. This study presents a method based on deep learning and a 30-layer DNN neural network for detecting human activity on the Fordham University Activity Diagnostic Data Set. The data set contains more than 1 million lines in six classes to detect IoT activity. The proposed model had almost 90% and an error rate of 0. 22 in the evaluation criteria, which indicates the good performance of deep learning in activity recognition.

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APA: Copy

MIRZAEI, A., & FARAJI, F.. (2022). Detecting Human Activities Based on Motion Sensors in IOT Using Deep Learning. NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, B- MUHANDISI -I KAMPYUTAR, 19(4 ), 313-324. SID. https://sid.ir/paper/955020/en

Vancouver: Copy

MIRZAEI A., FARAJI F.. Detecting Human Activities Based on Motion Sensors in IOT Using Deep Learning. NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, B- MUHANDISI -I KAMPYUTAR[Internet]. 2022;19(4 ):313-324. Available from: https://sid.ir/paper/955020/en

IEEE: Copy

A. MIRZAEI, and F. FARAJI, “Detecting Human Activities Based on Motion Sensors in IOT Using Deep Learning,” NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, B- MUHANDISI -I KAMPYUTAR, vol. 19, no. 4 , pp. 313–324, 2022, [Online]. Available: https://sid.ir/paper/955020/en

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