Smoke Detection and Fire Prevention Using Cisco Packet Tracer

Authors

  • V Anusha School of Computer Science and Engineering, REVA University, Bengaluru, India
  • Madhavi S School of Computer Science and Engineering, REVA University, Bengaluru, India
  • Naveen Chandra Gowda School of Computer Science and Engineering, REVA University, Bengaluru, India

DOI:

https://doi.org/10.5281/zenodo.10254199

Keywords:

Packet Tracer, Fire Prevention, Smoke Detection

Abstract

This paper provides an in-depth analysis of the latest developments in smoke detection technologies and fire prevention methodologies, both of which are pivotal components of contemporary fire safety strategies. The review encompasses an exploration of various smoke detection technologies, including ionization, photoelectric, and heat detectors, with a focus on their individual merits and limitations. Additionally, it delves into fire prevention strategies, encompassing the utilization of sprinkler systems, fire-resistant materials, and the formulation of efficient evacuation plans. Regulatory standards pertinent to fire safety are also addressed, and a series of case studies are presented to exemplify successful implementation of these technologies and strategies. The paper concludes by shedding light on emerging trends and the challenges confronting the field, providing valuable insights into potential avenues for future research and innovation within the realms of smoke detection and fire prevention.

References

Ho, C. C., & Kuo, T. H. (2009, July). Real-time video-based fire smoke detection system. In 2009 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (pp. 1845-1850). IEEE.

Lai, C. L., & Yang, J. C. (2008, May). Advanced real time fire detection in video surveillance system. In 2008 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 3542-3545). IEEE.

Razmi, S. M., Saad, N., & Asirvadam, V. S. (2010, December). Vision-based flame detection: motion detection & fire analysis. In 2010 IEEE Student Conference on Research and Development (SCOReD) (pp. 187-191). IEEE.

Ha, C., Jeon, G., & Jeong, J. (2011, November). Vision-based smoke detection algorithm for early fire recognition in digital video recording system. In 2011 Seventh International Conference on Signal Image Technology & Internet-Based Systems (pp. 209-212). IEEE.

Tian, H., Li, W., Wang, L., & Ogunbona, P. (2012, July). A novel video-based smoke detection method using image separation. In 2012 IEEE International Conference on Multimedia and Expo (pp. 532-537). IEEE.

Morerio, P., Marcenaro, L., Regazzoni, C. S., & Gera, G. (2012, September). Early fire and smoke detection based on colour features and motion analysis. In 2012 19th IEEE International Conference on Image Processing (pp. 1041-1044). IEEE.

Ramaiah, N. S., & Ahmed, S. T. (2022). An IoT-Based Treatment Optimization and Priority Assignment Using Machine Learning. ECS Transactions, 107(1), 1487.

Santana, P., Gomes, P., & Barata, J. (2012, October). A vision-based system for early fire detection. In 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (pp. 739-744). IEEE.

Jun-zhe, Z., & Ge, S. Research on the Technology of Fire Detection Based on Image Processing in Unmanned Substation. In 2010 Third International Conference on Intelligent Networks and Intelligent Systems.

Celik, T., & Ma, K. K. (2008, June). Computer vision based fire detection in color images. In 2008 IEEE Conference on Soft Computing in Industrial Applications (pp. 258-263). IEEE.

Jun, C., Yang, D., & Dong, W. (2009, March). An early fire image detection and identification algorithm based on dfbir model. In 2009 WRI World Congress on Computer Science and Information Engineering (Vol. 3, pp. 229-232). IEEE.

Zhu, S., & Zhang, N. (2012, August). Face detection based on skin color model and geometry features. In 2012 International Conference on Industrial Control and Electronics Engineering (pp. 991-994). IEEE.

Kim, D., & Wang, Y. F. (2009, March). Smoke detection in video. In 2009 WRI World Congress on Computer Science and Information Engineering (Vol. 5, pp. 759-763). IEEE.

Bukowski, R. W., Peacock, R. D., Averill, J. D., Cleary, T. G., Bryner, N. P., Walton, W. D., ... & Kuligowski, E. (2008). Performance of home smoke alarms. NIST Technical Note, 1455, 1.

Ahmed, S. T., Basha, S. M., Arumugam, S. R., & Kodabagi, M. M. (2021). Pattern Recognition: An Introduction. MileStone Research Publications.

Smoke Detector in Wikipedia. Retrieved from http://en.wikipedia.org/wiki/smoke on January 10, 2007.

IoT and Sensor Technology in Fire Prevention:* [Internet of Things(IoT)in Fire Safety] (https://www.researchgate.net/publication/322174059_Internet_of_Things_IoT_in_Fire_Safety)

Cybersecurity in Fire Prevention Systems: [Cybersecurity Challenges in Fire Alarm Systems] (https://www.sciencedirect.com/science/article/abs/pii/S1877050915001134)

Cloud Computing and Fire Safety: [Cloud-Based Fire Detection Systems] (https://ieeexplore.ieee.org/document/7510400)

Downloads

Published

2023-12-04

How to Cite

V Anusha, Madhavi S, & Naveen Chandra Gowda. (2023). Smoke Detection and Fire Prevention Using Cisco Packet Tracer. International Journal of Computational Learning & Intelligence, 2(4), 136–142. https://doi.org/10.5281/zenodo.10254199

Issue

Section

RESEARCH ARTICLES