Fire Alarm System Through Smoke Detection

Authors

  • Manya Sinha B.Tech Scholar, Department of Computer Science and Engineering, Manav Rachna University, Faridabad, Haryana, India Author
  • Shivank Solanki B.Tech Scholar, Department of Computer Science and Engineering, Manav Rachna University, Faridabad, Haryana, India Author
  • Sudeep Batra B.Tech Scholar, Department of Computer Science and Engineering, Manav Rachna University, Faridabad, Haryana, India Author
  • Yojna Arora Associate Professor, Department of Computer Science and Engineering, Manav Rachna University, Faridabad, Haryana, India Author
  • Abhishek Tewatia B.Tech Scholar, Department of Computer Science and Engineering, Manav Rachna University, Faridabad, Haryana, India Author

DOI:

https://doi.org/10.55524/ijircst.2023.11.4.1

Keywords:

Fire Alarm System, Smoke, Fire Safety, Synthetic Materials

Abstract

A reliable fire alarm system (FAS) is crucial for timely reporting and responding to fires. While existing techniques can predict undesirable outcomes, they lack guidance on when and how workers should intervene to minimize the associated costs. Recent advancements in sensors, microelectronics, and information technology have significantly improved fire detection technologies.
However, the prevalence of synthetic materials in modern homes has increased the danger of fire-related injuries and deaths due to the release of toxic fumes and gases, including carbon monoxide. This highlights the need for ongoing analysis and development of fire detection techniques to ensure the safety of occupants.

Downloads

Download data is not yet available.

References

Hu, Z. W. (2019, September 20). Research on two stage flame detection algorithm based on fire. Retrieved from ACM Digital Library: https://dl.acm.org/doi/10.1145/3366194.3366296

Kaiser, A. S. (2018). A Hybrid Approach for Alarm Verification using Stream. Retrieved from openproceedings.org:

https://openproceedings.org/2018/conf/edbt/paper-246.pdf [3] Lamine Salhi Thomas Silverston, T. Y. (2019). Early Detection System for Gas Leakage and Fire in. Retrieved from IEEE Xplore: https://ieeexplore.ieee.org/document/8661990

Mogren, J. M. (2022, july 19). A Novel Method for Smart Fire Detection. Retrieved from springer: https://link.springer.com/article/10.1007/s10694-022-01307- 1

Putrada, G. S. (2019). Comparison of Classification Algorithms to Improve. Retrieved from IEEE Xplore: https://ieeexplore.ieee.org/abstract/document/8935885

Sivaraman, R. A. (2021, December). Machine Learning Based Fire Alarming System Using. Retrieved from Researchgate:

researchgate.net/publication/357159137_Machine_Learning _Based_Fire_Alarming_System_Using_Internet_of_Things [7] Surya, L. (2017, March 1). Risk Analysis Model That Uses Machine Learning. Retrieved from IJCT: https://www.researchgate.net/publication/349310241_Risk_ Analysis_Model_That_Uses_Machine_Learning_to_Predict _the_Likelihood_of_a_Fire_Occurring_at_A_Given_Propert y

Udaya Dampage *, L. B. (2022, January 7). Forest fre detection system. Retrieved from nature.com/scientificreports:

https://www.nature.com/articles/s41598-021-03882-9 [9] Wang, Q. H. (2012, june). Intelligent Building Hazard Detection Using Wireless Sensor. Retrieved from researchgate:

https://www.researchgate.net/publication/268586834_Intelli gent_Building_Hazard_Detection_Using_Wireless_Sensor_ Network_and_Machine_Learning_Techniques

YUN, K. S. (2017, February). An Improved Feature Extraction and. Retrieved from space.snu.ac: https://s space.snu.ac.kr/bitstream/10371/122863/1/000000142478.pdf

Downloads

Published

2023-07-30

Issue

Vol. 11 No. 4 (2023): International Journal of Innovative Research in Computer Science and Technology(JUL) 2023

Section

Articles

How to Cite

Fire Alarm System Through Smoke Detection. (2023). International Journal of Innovative Research in Computer Science & Technology, 11(4), 1–4. https://doi.org/10.55524/ijircst.2023.11.4.1
Crossref
Scopus
Google Scholar
Europe PMC