Internet of Things-based device for the early detection and prevention of vehicle accidents

Authors

DOI:

https://doi.org/10.58594/rtest.v6i3.234

Keywords:

Internet of Things, vehicle safety, fire detection, sensors, accident prevention

Abstract

Traffic accidents, vehicle fires, and toxic gas accumulation inside cabins represent growing risks to road safety. Nearly 1.2 million people are affected annually by traffic incidents worldwide, a figure that exceeds 5,000 cases in Ecuador, including 564 accidents recorded in Quevedo during 2023 alone. This paper presents the development of an Internet of Things (IoT) device for the early detection and prevention of accidents in light vehicles, integrating gas (MQ-135), temperature/humidity (DHT11), and motion (PIR HC-SR501) sensors controlled via an Arduino UNO and an ESP8266 module for wireless transmission. A mobile application was also developed in Android Studio to display environmental variables and issue real-time alerts. Evaluation using the Technology Acceptance Model (TAM) with 20 users showed high perceived usefulness and ease of use, validating the prototype's feasibility as a low-cost preventive solution.

Downloads

Download data is not yet available.

References

Barrios Andrés, M. (2021). Internet de las cosas. Editorial Reus.

Bucsuházy, K., Matuchová, E., Zůvala, R., Moravcová, P., Kostíková, M., & Mikulec, R. (2020). Human factors contributing to the road traffic accident occurrence. Transportation Research Procedia, 45, 555–561. https://doi.org/10.1016/j.trpro.2020.03.057 DOI: https://doi.org/10.1016/j.trpro.2020.03.057

Caballero Hernández, H., Ramos Corchado, M. A., & Muñoz Jiménez, V. (2023). Sistema de identificación de incendios en espacios interiores. ReCIBE: Revista Electrónica de Computación, Informática, Biomédica y Electrónica, 12(1), 1–18. https://doi.org/10.32870/recibe.v12i1.256 DOI: https://doi.org/10.32870/recibe.v12i1.256

Csápaiová, N. (2021). The impact of vehicle fires on road safety. Transportation Research Procedia, 55, 1704–1711. https://doi.org/10.1016/j.trpro.2021.07.162 DOI: https://doi.org/10.1016/j.trpro.2021.07.162

Ecuador. Instituto Nacional de Estadística y Censos. (2023). Anuario de Estadísticas de Transporte, 2023. INEC. https://www.ecuadorencifras.gob.ec/documentos/web-inec/Estadisticas_Economicas/Estadistica%20de%20Transporte/ESTRA/2023/2023_ESTRA_PPT.pdf

Hidalgo, G., & Borja, J. (2023). Nota técnica: Siniestros de tránsito. I trimestre, 2023. Instituto Nacional de Estadística y Censos. https://www.ecuadorencifras.gob.ec/documentos/web-inec/Estadisticas_Economicas/Estadistica%20de%20Transporte/2023/2023_SINIESTROS_ITRIMESTRE.pdf

Hidalgo-Solórzano, E., Pérez-Núñez, R., Mojarro, F. R., Vera-López, J. D., & Híjar, M. (2020). Accidentes no fatales en población mexicana, prevalencia y factores asociados. Ensanut 2018-19. Salud Pública de México, 62(6), 829–839. https://doi.org/10.21149/11563 DOI: https://doi.org/10.21149/11563

Liao, S., Tu, Z., Yu, F., Zhu, M., Sun, K., Sha, Q., Yang, X., & Zheng, J. (2024). Emissions of gaseous nitrous acid (HONO) from diesel trucks: Insights from real-driving emission experiments. Science of the Total Environment, 954, 176425. https://doi.org/10.1016/j.scitotenv.2024.176425 DOI: https://doi.org/10.1016/j.scitotenv.2024.176425

Organización Panamericana de la Salud. (2023). 7.ª Semana Mundial de la ONU para la Seguridad Vial 2023. OPS. https://www.paho.org/es/campanas/7a-semana-mundial-onu-para-seguridad-vial-2023

Periyanayagi, S., Manikandan, A., Muthukrishnan, M., & Ramakrishnan, M. (2021). BDoor App: Blood donation application using Android Studio. Journal of Physics: Conference Series, 1917(1), 012018. https://doi.org/10.1088/1742-6596/1917/1/012018 DOI: https://doi.org/10.1088/1742-6596/1917/1/012018

Xie, J., Teng, J., Fan, Y., Xie, R., & Shen, A. (2019). The short-term effects of air pollutants on hospitalizations for respiratory disease in Hefei, China. International Journal of Biometeorology, 63(3), 315–326. https://doi.org/10.1007/s00484-018-01665-y DOI: https://doi.org/10.1007/s00484-018-01665-y

Yu, L., Xu, Z., Cheng, M., Lin, W., Qiu, W., & Xiao, X. (2023). MSEDDI: Multi-scale embedding for predicting drug–drug interaction events. International Journal of Molecular Sciences, 24(5), 4500. https://doi.org/10.3390/ijms24054500 DOI: https://doi.org/10.3390/ijms24054500

Downloads

Published

2026-09-01

How to Cite

Morán-Cabezas, J. L., Morán-Cabezas, A. L., Balarezo-Valarezo, F. J., & Delgado-Soto, J. F. (2026). Internet of Things-based device for the early detection and prevention of vehicle accidents. Revista Transdiciplinaria De Estudios Sociales Y Tecnológicos, 6(3), 77–85. https://doi.org/10.58594/rtest.v6i3.234

Issue

Vol. 6 No. 3 (2026): Ciencia y sociedad ante los desafíos humanos, tecnológicos y ambientales del presente (Septiembre-diciembre)

Section

Artículos

License

Copyright (c) 2026 Jefferson Leandro Morán-Cabezas, Anthony Limber Morán-Cabezas, Fabricio Javier Balarezo-Valarezo, José Fernando Delgado-Soto

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Authors who publish in Revista Transdisciplinaria de Estudios Sociales y Tecnológicos (RTEST), agree to the following terms:

1. Copyright

Authors retain unrestricted copyright to their work. Authors grant the journal the right of first publication. To this end, they assign the journal non-exclusive exploitation rights (reproduction, distribution, public communication, and transformation). Authors may enter into additional agreements for the non-exclusive distribution of the version of the work published in the journal, provided that acknowledgment of its initial publication in this journal is given.

© The authors.

2. License

The articles are published in the journal under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0). The terms can be found at: https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en

This license allows:

  • Sharing: Copying and redistributing the material in any medium or format.
  • Adapting: Remixing, transforming, and building upon the material.

Under the following terms:

  • Attribution: You must give appropriate credit, provide a link to the license, and indicate if any changes were made. You may do this in any reasonable manner, but not in any way that suggests the licensor endorses or sponsors your use.
  • NonCommercial: You may not use the material for commercial purposes.
  • ShareAlike: If you remix, transform, or build upon the material, you must distribute your creation under the same license as the original work.

There are no additional restrictions. You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.