Fire Alarm System Through Smoke Detection

Manya Sinha; Shivank Solanki; Sudeep Batra; Dr. Yojna Arora; Abhishek Tewatia

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.

Keywords

Fire Alarm System, Smoke, Fire Safety, Synthetic Materials

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
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
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_Property
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
Wang, Q. H. (2012, june). Intelligent Building Hazard Detection Using Wireless Sensor. Retrieved from researchgate: https://www.researchgate.net/publication/268586834_Intelligent_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

Cites this article as

M. Sinha, S. Solanki, S. Batra, D. Y. Arora, A. Tewatia, "Fire Alarm System Through Smoke Detection", International Journal of Innovative Research in Computer Science and Technology (IJIRCST), Vol-11, no.4, pp.1-4, 2023. Available from: https://doi.org/10.55524/ijircst.2023.11.4.1

Corresponding Author

Manya Sinha

B.Tech Scholar, Department of Computer Science and Engineering, Manav Rachna University, Faridabad, Haryana, India

Download Full Paper

Download PDF

No. of Downloads: 68 | No. of Views: 826

Blockchain Voting System- An NFT-Based Approach

Anshjyot Singh Wadhwa.

September 2024 - Vol 12, Issue 5
Empowering Ecosystems- Unveiling the Interplay of Smart Agriculture and Sustainable Practices .

Mohammad Hashir, Sanskar Mishra, Yojna Arora, Avinash Kumar Sharma.

September 2024 - Vol 12, Issue 5
Enhancing Momentum Trading with Macroeconomic Indicators- A Strategic Approach

Mohit Apte.

July 2024 - Vol 12, Issue 4

IJIRCST

Fire Alarm System Through Smoke Detection

Citations

Download Full Paper PDF

Total View 826

Total Download 68