Smart In-Cabin Air Monitoring System using IoT Technologies

Authors

  • Falah Y H Ahmed Faculty of Computing and Information Technology, Sohar University, Sohar 311, Oman.
  • Jabar H. Yousif Faculty of Computing and Information Technology, Sohar University, Sohar 311, Oman.
  • Marwan Alshar’e Faculty of Computing and Information Technology, Sohar University, Sohar 311, Oman.
  • Maram El Sheikh Faculty of Computing and Information Technology, Sohar University, Sohar 311, Oman.
  • Ehsan Al-Ajmi Faculty of Computing and Information Technology, Sohar University, Sohar 311, Oman.
  • Mahmood Al-Bahri Faculty of Computing and Information Technology, Sohar University, Sohar 311, Oman.

DOI:

https://doi.org/10.58429/qaj.v4n1a275

Abstract

This research develops a monitoring system that improves the safety of people in the car. Continuous monitoring of in-cabin air quality is an important step in achieving a safer environment inside the cabin. Using oxygen, carbon dioxide, and temperature sensors to monitor those variables at all times, combining them with an Arduino to process those variables. In the event of approaching danger levels, a message is generated and sent to the owner of the car alerting them of the changes in the variables. This step allows the owner to resolve the situation without compromising the security of the vehicle. If the readings continue to depreciate, the Arduino will roll down the windows slightly allowing fresh air into the cabin, message the driver again to inform them of the action taken and alert the authorities to act immediately in case medical assistance is required. Cars have become the most common means of transportation in the world. While car crashes are looked at as the source of deaths related to vehicles, lack of oxygen and cabin overheating-related deaths have been rising. Many scenarios can lead to deaths in a stationary car such as children being left inside a car alone, parents unintentionally leaving their children in the back seats while rushing to work in the morning, and napping or sleeping in the car. Those scenarios are dangerous because of the effect of low oxygen, high carbon dioxide, and high temperature on humans. Oxygen deprivation and high carbon dioxide intake negatively affect the human brain.

Downloads

Download data is not yet available.

References

Almohsen, M. K., Alanazi, T. H., & BinSaif, S. N. (2021, April). Smart car seat belt: Accident detection and emergency services in smart city environment. In 2021 1st International Conference on Artificial Intelligence and Data Analytics (CAIDA) (pp. 109-114). IEEE.

Vimalkumar, S., (2018). A review on smart IOT car for accident prevention. Asian J Appl Sci Technol, 2(1), 287-292.

Mohammed, M. A., Lakhan, A., Abdulkareem, K. H., et al. (2023). Homomorphic federated learning schemes enabled pedestrian and vehicle detection system. Internet of Things, 23, 100903.

Mohammed, M. A., Lakhan, A., et al. (2024). Securing healthcare data in industrial cyber-physical systems using combining deep learning and blockchain technology. Engineering Applications of Artificial Intelligence, 129, 107612.

Verberne, F. M., Ham, J., & Midden, C. J. (2012). Trust in smart systems: Sharing driving goals and giving information to increase trustworthiness and acceptability of smart systems in cars. Human factors, 54(5), 799-810.

Wani, N.A., Najar, S.A. and Masoodi, Z.S., The Impact of Automation on Human Behavior-A Review.

Mohammed, M. A., Lakhan, A., Abdulkareem, K. H., et al. (2023). Energy-efficient distributed federated learning offloading and scheduling healthcare system in blockchain based networks. Internet of Things, 22, 100815.

Szczurek, A., and Maciejewska, M. (2016). Categorisation for air quality assessment in car cabin. Transportation Research Part D: Transport and Environment, 48, 161-170.

Morallo, N. T. (2021). Vehicle tracker system design based on GSM and GPS interface using arduino as platform. Indonesian Journal of Electrical Engineering and Computer Science, 23(1), 258-264.

Sugiharto, A. F., Firdausi, R. A., and Safitry, O. (2018, August). The effects of declined oxygen levels on hypoxia symptoms and blood gases: An experimental study. In Journal of Physics: Conference Series (Vol. 1073, No. 4, p. 042023). IOP Publishing.

Ramya, V., & Palaniappan, B. (2012). Embedded Technology for vehicle cabin safety Monitoring and Alerting System. International Journal of Computer Science, Engineering and Applications, 2(2), 83.

Mousel, T., Larsen, P., and Lorenz, H. (2017). Unattended children in cars-Radiofrequency-based detection to reduce heat stroke fatalities. In 25th International Technical Conference on the Enhanced Safety of Vehicles (ESV): Innovations in Vehicle Safety: Opportunities and Challenges.

Jawarneh, M., Alshar'e, M., Dewi, D. A., Al Nasar, M., Almajed, R., & Ibrahim, A. (2023). The impact of virtual reality technology on Jordan’s learning environment and medical informatics among physicians. International Journal of Computer Games Technology, 2023.

Alshar’e, M., Albadi, A., Mustafa, M., Tahir, N., and Al Amri, M. (2022). A framework of the training module for untrained observers in usability evaluation motivated by COVID-19: enhancing the validity of usability evaluation for children’s educational games. Advances in Human-Computer Interaction, 2022, 1-11.

Alshar'e, M., Al Nasar, M. R., Kumar, R., Sharma, M., and Tripathi, V. (2022). A face recognition method in machine learning (ml) for enhancing security in smart home. In 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) (pp. 1081-1086). IEEE.

Nolich, M., Spoladore, D., Carciotti, S., Buqi, R., & Sacco, M. (2019). Cabin as a home: a novel comfort optimization framework for IoT equipped smart environments and applications on cruise ships. Sensors, 19(5), 1060.

Sini, J., Pugliese, L., Groppo, S., Guagnano, M., & Violante, M. (2023). Towards In-Cabin Monitoring: A Preliminary Study on Sensors Data Collection and Analysis. arXiv preprint arXiv:2309.11890.

Kazem, H.A., Chaichan, M.T., Al-Waeli, A.H., Yousif, J.H. and Al-Waeli, K.H., 2017. Wind Resource Assessment for nine locations in Oman using weather data. International Journal of Computation and Applied Sciences, 3(1), pp.185-191.

Yousif, J.H. and Abdalgader, K., 2022. Experimental and mathematical models for real-time monitoring and auto watering using IoT architecture. Computers, 11(1), p.7.

Goh, C. C., Kamarudin, L. M., Zakaria, A., et al. (2021). Real-time in-vehicle air quality monitoring system using machine learning prediction algorithm. Sensors, 21(15), 4956.

Ahmed, F. Y., Hazlan, E. B., and Abdulla, M. I. (2021). Enhancement of Mobile-Based Application for Vehicle Rental. In 2021 IEEE 11th IEEE Symposium on Computer Applications & Industrial Electronics (ISCAIE) (pp. 163-168). IEEE.

Mahmood, O. A., Yousif, A. S., and Shamsuddin, F. Y. A. (2020, April). A new approach to solving Transportation Model Based on the Standard Deviation. In 2020 IEEE 10th Symposium on Computer Applications & Industrial Electronics (ISCAIE) (pp. 1-5). IEEE.

Mohammed, M. A., Lakhan, A., et al. (2023). Adaptive secure malware efficient machine learning algorithm for healthcare data. CAAI Transactions on Intelligence Technology.

Fong, S. L., Chin, D. W. Y., Abbas, R. A., Jamal, A., & Ahmed, F. Y. (2019). Smart city bus application with QR code: a review. In 2019 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) (pp. 34-39). IEEE.

Ramos-Sorroche, E., Rubio-Aparicio, J., Santa, J., Guardiola, C., & Egea-Lopez, E. (2024). In-cabin and outdoor environmental monitoring in vehicular scenarios with distributed computing. Internet of Things, 25, 101009.

Nugraha, D., and Ahmed, F. Y. (2019). MEAN stack to enhance the advancement of parking application: A narrative review. In Journal of Physics: Conference Series (Vol. 1167, No. 1, p. 012075). IOP Publishing.

Published

2024-01-29

How to Cite

Y H Ahmed , F. ., H. Yousif , J. ., Alshar’e , M. ., El Sheikh, M. ., Al-Ajmi , E., & Al-Bahri , M. . (2024). Smart In-Cabin Air Monitoring System using IoT Technologies . Qubahan Academic Journal, 4(1), 78–90. https://doi.org/10.58429/qaj.v4n1a275

Issue

Section

Articles