RASPBERRY PI-BASED SENSOR NETWORK FOR MULTI-PURPOSE NONLINEAR MOTION DETECTION IN LABORATORIES USING MEMS

Natarajan Shriethar; Narmadha  Chandramohan; Chandramohan Rathinam

doi:10.15446/mo.n65.102641

Published

2022-07-05

RASPBERRY PI-BASED SENSOR NETWORK FOR MULTI-PURPOSE NONLINEAR MOTION DETECTION IN LABORATORIES USING MEMS

RED DE SENSORES MULTIFUNCIONAL BASADA EN RASPBERRY PI PARA LA DETECCIÓN DE MOVIMIENTO NO LINEAL EN LABORATORIOS USANDO MEMS

DOI:

https://doi.org/10.15446/mo.n65.102641

Keywords:

motion sensors, Lagrangean solution, Raspberry Pi, nonlinear measurement system, MEMS (en)
sensores de movimiento, solución Lagrangiana, Raspberry Pi, sistema de medición no lineal, MEMS (es)

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Authors

Natarajan Shriethar Department of Energy Science, Alagappa University, Karaikudi.
Narmadha Chandramohan Vigil Health Solutions. https://orcid.org/0000-0002-6975-7648
Chandramohan Rathinam Vidyaagiri Coleege of Arts and Science, Puduvayal. https://orcid.org/0000-0002-5845-0966

Abstract (en)
Abstract (es)

Detecting and measuring the nonlinear evolution of a classical system is a complex process. In this work, the nonlinear evolution of a lab-level system is measured using the Raspberry Pi-based MEMS sensor network system. The evolution and various results of nonlinear systems were compared theoretical and experimentally.

Detectar y medir la evolución no lineal de un sistema clásico es un proceso complejo. En este trabajo, se mide la evolución no lineal de un sistema a nivel de laboratorio utilizando el sistema de red de sensores MEMS basado en Raspberry Pi. La evolución y varios resultados de sistemas no lineales fueron comparados teórica y experimentalmente.

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How to Cite

APA

Shriethar, N., Chandramohan, N. . and Rathinam, C. (2022). RASPBERRY PI-BASED SENSOR NETWORK FOR MULTI-PURPOSE NONLINEAR MOTION DETECTION IN LABORATORIES USING MEMS. MOMENTO, (65), 52–64. https://doi.org/10.15446/mo.n65.102641

ACM

[1]

Shriethar, N., Chandramohan, N. and Rathinam, C. 2022. RASPBERRY PI-BASED SENSOR NETWORK FOR MULTI-PURPOSE NONLINEAR MOTION DETECTION IN LABORATORIES USING MEMS. MOMENTO. 65 (Jul. 2022), 52–64. DOI:https://doi.org/10.15446/mo.n65.102641.

ACS

(1)

Shriethar, N.; Chandramohan, N. .; Rathinam, C. RASPBERRY PI-BASED SENSOR NETWORK FOR MULTI-PURPOSE NONLINEAR MOTION DETECTION IN LABORATORIES USING MEMS. Momento 2022, 52-64.

ABNT

SHRIETHAR, N.; CHANDRAMOHAN, N. .; RATHINAM, C. RASPBERRY PI-BASED SENSOR NETWORK FOR MULTI-PURPOSE NONLINEAR MOTION DETECTION IN LABORATORIES USING MEMS. MOMENTO, [S. l.], n. 65, p. 52–64, 2022. DOI: 10.15446/mo.n65.102641. Disponível em: https://revistas.unal.edu.co/index.php/momento/article/view/102641. Acesso em: 23 apr. 2025.

Chicago

Shriethar, Natarajan, Narmadha Chandramohan, and Chandramohan Rathinam. 2022. “RASPBERRY PI-BASED SENSOR NETWORK FOR MULTI-PURPOSE NONLINEAR MOTION DETECTION IN LABORATORIES USING MEMS”. MOMENTO, no. 65 (July):52-64. https://doi.org/10.15446/mo.n65.102641.

Harvard

Shriethar, N., Chandramohan, N. . and Rathinam, C. (2022) “RASPBERRY PI-BASED SENSOR NETWORK FOR MULTI-PURPOSE NONLINEAR MOTION DETECTION IN LABORATORIES USING MEMS”, MOMENTO, (65), pp. 52–64. doi: 10.15446/mo.n65.102641.

IEEE

[1]

N. Shriethar, N. . Chandramohan, and C. Rathinam, “RASPBERRY PI-BASED SENSOR NETWORK FOR MULTI-PURPOSE NONLINEAR MOTION DETECTION IN LABORATORIES USING MEMS”, Momento, no. 65, pp. 52–64, Jul. 2022.

MLA

Shriethar, N., N. . Chandramohan, and C. Rathinam. “RASPBERRY PI-BASED SENSOR NETWORK FOR MULTI-PURPOSE NONLINEAR MOTION DETECTION IN LABORATORIES USING MEMS”. MOMENTO, no. 65, July 2022, pp. 52-64, doi:10.15446/mo.n65.102641.

Turabian

Shriethar, Natarajan, Narmadha Chandramohan, and Chandramohan Rathinam. “RASPBERRY PI-BASED SENSOR NETWORK FOR MULTI-PURPOSE NONLINEAR MOTION DETECTION IN LABORATORIES USING MEMS”. MOMENTO, no. 65 (July 5, 2022): 52–64. Accessed April 23, 2025. https://revistas.unal.edu.co/index.php/momento/article/view/102641.

Vancouver

1.

Shriethar N, Chandramohan N, Rathinam C. RASPBERRY PI-BASED SENSOR NETWORK FOR MULTI-PURPOSE NONLINEAR MOTION DETECTION IN LABORATORIES USING MEMS. Momento [Internet]. 2022 Jul. 5 [cited 2025 Apr. 23];(65):52-64. Available from: https://revistas.unal.edu.co/index.php/momento/article/view/102641

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1. Edwin Christian Becerra-Alvarez, Juan Jose Raygoza-Panduro, Jorge Rivera-Dominguez, Susana Ortega-Cisneros, José Luis González-Vidal. (2023). ForEmb: A Forth-Inspired, Real-Time Interpreter for Embedded Systems. 2023 12th International Conference On Software Process Improvement (CIMPS). , p.215. https://doi.org/10.1109/CIMPS61323.2023.10528835.

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