dor_id: 4110272

506.#.#.a: Público

590.#.#.d: Los artículos enviados a JART se juzgan por medio de un proceso de revisión por pares

510.0.#.a: Consejo Nacional de Ciencia y Tecnología (CONACyT), Sistema Regional de Información en Línea para Revistas Científicas de América Latina, el Caribe, España y Portugal (Latindex), SCOPUS, Directory of Open Access Journals (DOAJ), Periódica, Red de Revistas Científicas de América Latina y el Caribe, España y Portugal (Redalyc), Google Académico

561.#.#.u: https://www.icat.unam.mx/

650.#.4.x: Ingenierías

336.#.#.b: article

336.#.#.3: Artículo de Investigación

336.#.#.a: Artículo

351.#.#.6: http://jart.icat.unam.mx/index.php/jart

351.#.#.b: Journal of Applied Research and Technology

351.#.#.a: Artículos

harvesting_group: RevistasUNAM

270.1.#.p: Revistas UNAM. Dirección General de Publicaciones y Fomento Editorial, UNAM en revistas@unam.mx

590.#.#.c: Open Journal Systems (OJS)

270.#.#.d: MX

270.1.#.d: México

590.#.#.b: Concentrador

883.#.#.u: http://www.revistas.unam.mx/front/

883.#.#.a: Revistas UNAM

590.#.#.a: Coordinación de Difusión Cultural

883.#.#.1: https://www.publicaciones.unam.mx/

883.#.#.q: Dirección General de Publicaciones y Fomento Editorial, UNAM

850.#.#.a: Universidad Nacional Autónoma de México

856.4.0.u: http://jart.icat.unam.mx/index.php/jart/article/view/1351/794

100.1.#.a: Rahimunnisa, K.; M., Atchaiya; Arunachalam, Brindhhiniy; Divyaa, V.

524.#.#.a: Rahimunnisa, K., et al. (2020). AI-based smart and intelligent wheelchair. Journal of Applied Research and Technology; Vol 18 No 6, 2020. Recuperado de https://repositorio.unam.mx/contenidos/4110272

245.1.0.a: AI-based smart and intelligent wheelchair

502.#.#.c: Universidad Nacional Autónoma de México

561.1.#.a: Instituto de Ciencias Aplicadas y Tecnología, UNAM

264.#.0.c: 2020

264.#.1.c: 2020-12-31

506.1.#.a: La titularidad de los derechos patrimoniales de esta obra pertenece a las instituciones editoras. Su uso se rige por una licencia Creative Commons BY 4.0 Internacional, https://creativecommons.org/licenses/by/4.0/legalcode.es, fecha de asignación de la licencia 2020-12-31, para un uso diferente consultar al responsable jurídico del repositorio por medio del correo electrónico revistas@unam.mx

884.#.#.k: http://jart.icat.unam.mx/index.php/jart/article/view/1351

001.#.#.#: oai:ojs2.localhost:article/1351

041.#.7.h: eng

520.3.#.a: The differently abled and/or old-aged people require assistance for their movement. Generally, such assistant providing tool is wheelchair. Normal wheelchairs are manually operated and heavy to move adding burden to the suffered. Hence, automated wheelchairs that are equipped with sensors and a data processing unit constitute a special class of wheeled mobile robots, termed as “smart wheelchairs” in general. In the existing system, the wheelchair movement that is controlled by joystick uses buttons to start and stop the wheel. This is difficult for the differently abled to press the required button with precision. Although there are smart wheelchairs with gesture control, it lacks accuracy in the calculation of the location. The proposed system uses artificial intelligence for its working and proves to be a unique combination of wheelchair and health monitoring system. The wheelchair can be accessed both in manual and automatic modes. In the manual mode, the wheel is controlled using joystick whereas in the automated mode, MPU6050 sensor and accelerometer is used to control the direction by gesture. SPO2 sensor attached to the wheelchair is used to collect the health parameters. Thus, enabling the self-dependency of the person. Further, deep learning analysis of the data from the sensors and the wheelchair usage pattern is compared with the dataset to determine the stress level. The signal from the sensors is monitored and the vitals data is updated in the ThingSpeak website via Bluetooth module serving as a digital health chart.

773.1.#.t: Journal of Applied Research and Technology; Vol 18 No 6 (2020); 362-367

773.1.#.o: http://jart.icat.unam.mx/index.php/jart

046.#.#.j: 2021-04-13 00:00:00.000000

022.#.#.a: ISSN electrónico: 2448-6736; ISSN: 1665-6423

310.#.#.a: Bimestral

300.#.#.a: Páginas 362-367

264.#.1.b: Instituto de Ciencias Aplicadas y Tecnología, UNAM

758.#.#.1: http://jart.icat.unam.mx/index.php/jart

doi: https://doi.org/10.22201/icat.24486736e.2020.18.6.1351

handle: 00cee403da773d16

harvesting_date: 2021-03-08 00:00:00.0

856.#.0.q: application/pdf

file_creation_date: 2020-12-17 23:30:02.0

file_modification_date: 2020-12-17 23:30:02.0

file_creator: Yolanda G.G.

file_name: d39ea09a5a789f4b3156fd9b40ac451f9cb3107753f7edbf8546ea6a4f36d5c8.pdf

file_pages_number: 6

file_format_version: application/pdf; version=1.7

file_size: 559641

last_modified: 2021-04-15 12:10:00.000

license_url: https://creativecommons.org/licenses/by/4.0/legalcode.es

license_type: by

No entro en nada

No entro en nada 2

Artículo

AI-based smart and intelligent wheelchair

Rahimunnisa, K.; M., Atchaiya; Arunachalam, Brindhhiniy; Divyaa, V.

Instituto de Ciencias Aplicadas y Tecnología, UNAM, publicado en Journal of Applied Research and Technology, y cosechado de Revistas UNAM

Licencia de uso

Procedencia del contenido

Cita

Rahimunnisa, K., et al. (2020). AI-based smart and intelligent wheelchair. Journal of Applied Research and Technology; Vol 18 No 6, 2020. Recuperado de https://repositorio.unam.mx/contenidos/4110272

Descripción del recurso

Autor(es)
Rahimunnisa, K.; M., Atchaiya; Arunachalam, Brindhhiniy; Divyaa, V.
Tipo
Artículo de Investigación
Área del conocimiento
Ingenierías
Título
AI-based smart and intelligent wheelchair
Fecha
2020-12-31
Resumen
The differently abled and/or old-aged people require assistance for their movement. Generally, such assistant providing tool is wheelchair. Normal wheelchairs are manually operated and heavy to move adding burden to the suffered. Hence, automated wheelchairs that are equipped with sensors and a data processing unit constitute a special class of wheeled mobile robots, termed as “smart wheelchairs” in general. In the existing system, the wheelchair movement that is controlled by joystick uses buttons to start and stop the wheel. This is difficult for the differently abled to press the required button with precision. Although there are smart wheelchairs with gesture control, it lacks accuracy in the calculation of the location. The proposed system uses artificial intelligence for its working and proves to be a unique combination of wheelchair and health monitoring system. The wheelchair can be accessed both in manual and automatic modes. In the manual mode, the wheel is controlled using joystick whereas in the automated mode, MPU6050 sensor and accelerometer is used to control the direction by gesture. SPO2 sensor attached to the wheelchair is used to collect the health parameters. Thus, enabling the self-dependency of the person. Further, deep learning analysis of the data from the sensors and the wheelchair usage pattern is compared with the dataset to determine the stress level. The signal from the sensors is monitored and the vitals data is updated in the ThingSpeak website via Bluetooth module serving as a digital health chart.
Idioma
eng
ISSN
ISSN electrónico: 2448-6736; ISSN: 1665-6423

Enlaces