ISSN2320-2882
Impact Factor9.17
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ESTD2013
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Paper Title
Real-Time Motion Classification Using Edge AI and TinyML with IMU Sensors
Authors
Namit Solanki , Pritesh Kamdi , Saidatta Sabale , Dr. Amrapali Chavan , Suraj Pinjare
Keywords
AI, ML, IMU
Abstract
Getting a microcontroller to classify human movement
without any cloud dependency was the core challenge we
wanted to tackle. The common assumption is that useful
motion recognition requires a server somewhere in the loop
-- our project was built around questioning that. The system
we developed reads raw IMU output, feeds it into a quantized
neural network running on the same chip, and produces a
motion label in under 12 ms with no network involvement at
all.
We evaluated across five gesture categories (idle, wrist
rotation, arm raise, horizontal swipe, vertical punch), drawing
training data from eight participants across multiple recording
sessions. Quantizing to INT8 brought us to 94.3% top-1
accuracy on the held-out test set -- only 1.5 percentage points
behind the full-precision model. The complete firmware on the
Arduino Nano 33 BLE Sense came in at 62.7 KB, comfortably
within the 256 KB available.
One thing that genuinely surprised us during development
was how unaffected inference was when we cut wireless
connectivity entirely. Disabling the radio had no measurable
impact on latency or accuracy. Everything we built -- includ-
ing the parts that did not work out as planned -- is documented
below.
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How To Cite
Choose the style your journal or department asks for, then copy it. Every version below is generated from this paper's own record.
IJCRT — journal style
"Real-Time Motion Classification Using Edge AI and TinyML with IMU Sensors", IJCRT - International Journal of Creative Research Thoughts (www.ijcrt.org), ISSN:2320-2882, Vol.14, Issue 4, page no.l174-l179, April 2026, Available :https://ijcrt.org/papers/IJCRT26A4299.pdf
APA — 7th edition
Solanki, N., Kamdi, P., Sabale, S., Chavan, A., & Pinjare, S. (2026). Real-Time Motion Classification Using Edge AI and TinyML with IMU Sensors. International Journal of Creative Research Thoughts, 14(4), l174-l179. https://ijcrt.org/viewpaperforall.php?paper=IJCRT26A4299
MLA — 9th edition
Solanki, Namit, et al. "Real-Time Motion Classification Using Edge AI and TinyML with IMU Sensors." International Journal of Creative Research Thoughts, vol. 14, no. 4, 2026, pp. l174-l179, https://ijcrt.org/viewpaperforall.php?paper=IJCRT26A4299.
Chicago — 17th, bibliography
Solanki, Namit, et al. "Real-Time Motion Classification Using Edge AI and TinyML with IMU Sensors." International Journal of Creative Research Thoughts 14, no. 4 (2026): l174-l179. https://ijcrt.org/viewpaperforall.php?paper=IJCRT26A4299.
Harvard — author–date
Solanki, N. et al. (2026) 'Real-Time Motion Classification Using Edge AI and TinyML with IMU Sensors', International Journal of Creative Research Thoughts, 14(4), pp. l174-l179. Available at: https://ijcrt.org/viewpaperforall.php?paper=IJCRT26A4299
IEEE — numbered reference
N. Solanki, P. Kamdi, S. Sabale, A. Chavan and S. Pinjare, "Real-Time Motion Classification Using Edge AI and TinyML with IMU Sensors," IJCRT, vol. 14, no. 4, pp. l174-l179, Apr. 2026.
Vancouver — biomedical
Solanki N, Kamdi P, Sabale S, Chavan A, Pinjare S. Real-Time Motion Classification Using Edge AI and TinyML with IMU Sensors. IJCRT. 2026 Apr;14(4):l174-l179.
AMA — 11th edition
Solanki N, Kamdi P, Sabale S, Chavan A, Pinjare S. Real-Time Motion Classification Using Edge AI and TinyML with IMU Sensors. IJCRT. 2026;14(4):l174-l179. Accessed at https://ijcrt.org/viewpaperforall.php?paper=IJCRT26A4299
BibTeX — Zotero, Mendeley, LaTeX
@article{IJCRT26A4299,
author = {Namit Solanki and Pritesh Kamdi and Saidatta Sabale and Amrapali Chavan and Suraj Pinjare},
title = {Real-Time Motion Classification Using Edge AI and TinyML with IMU Sensors},
journal = {International Journal of Creative Research Thoughts},
volume = {14},
number = {4},
pages = {l174-l179},
year = {2026},
month = {April},
issn = {2320-2882},
url = {https://ijcrt.org/viewpaperforall.php?paper=IJCRT26A4299}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - Solanki, Namit
AU - Kamdi, Pritesh
AU - Sabale, Saidatta
AU - Chavan, Amrapali
AU - Pinjare, Suraj
TI - Real-Time Motion Classification Using Edge AI and TinyML with IMU Sensors
T2 - International Journal of Creative Research Thoughts
JA - IJCRT
VL - 14
IS - 4
PY - 2026
SN - 2320-2882
UR - https://ijcrt.org/viewpaperforall.php?paper=IJCRT26A4299
SP - l174-l179
ER -
Issue
Volume 14 Issue 4,
April-2026
Pages : l174-l179
Article Information
- Pages
- l174-l179
- Published
- April 2026
- Registration ID
- IJCRT_307418
- Published Paper ID
- IJCRT26A4299
- Research Area
- Science and Technology
- Author Type
- Indian Author
- Location
- Pune, Maharashtra, India
- Peer Review
- Request Peer Review Report
- Licence
- CC BY 4.0 · Open Access
- ISSN & Impact Factor
- 2320-2882 · IF 9.17
- Downloads
- 159
- Permanent Link
- https://ijcrt.org/viewpaperforall.php?paper=IJCRT26A4299
- Published Paper PDF
- https://ijcrt.org/papers/IJCRT26A4299.pdf
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International Journal of Creative Research Thoughts
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2320-2882
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No external funding was received for this study.
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Acknowledgements
The authors would like to thank the reviewers and the editorial board of International Journal of Creative Research Thoughts for their careful reading and constructive comments, and all colleagues who supported the preparation of this manuscript.
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