Innovations in Fire Detection and Suppression Systems for Oil Refinery Operations

Oil refineries are prone to high fire hazards that involve volatile chemicals combined with extremely high temperatures in confined spaces. These call for advanced fire suppression and emergency response suppression systems. Whereas the traditional sprinkling of water and foam agents have widely been in use, recent studies through the periods of 2020-2024 indicate their inefficiency in effective control within refinery environs on such grounds as water use, environmental impact and adaptability to hydrocarbon-based fires. Those involving automated detection with IoT and AI in predictive fire monitoring, water mist systems for effective flame cooling and control at minimum water consumption and eco-friendly fluorine-free foam agents contribute less to environmental damage. Hybrid suppression technologies, firefighting drones, robots, VR/AR-based emergency training have developed enhanced safety protocols via faster and more focused responses. However, huge gaps exist in scaling these technologies to sustain extreme temperatures and spatial challenges imposed by refineries, apart from all other maintenance issues, cost-effectiveness and regulatory compliance. This review integrates recent progress, confronts such technologies' effectiveness and economic impact, and proposes future research routes focused on sustainability and autonomy while calling for industrial collaboration and adaptive regulations that support even safer and more resilient refinery operations. In all, sensor-fusion systems have been pointed out as the most effective for oil refineries in terms of fire detection. In contrast, firefighting robots and drone delivery systems remain the most reliable for fire suppression. With continuous research, new technology investment and strategic collaboration, the industry will be assured of improved fire safety, contributing to a more sustainable future toward refinery operation globally.

Authors

Institutions

Publication Details

Journal
Path of Science
Published
2024-11-30
DOI
https://doi.org/10.22178/pos.111-7
Citations
2
Primary Topic
Fire Detection and Safety Systems
Type
article
Field-Weighted Citation Impact
0.73
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Innovations in Fire Detection and Suppression Systems for Oil Refinery Operations

Ikechukwu Bismarck Owunna, Onyeka Virginia Ekunke, Temitope Olubanjo Kehinde, Shola Abayomi Ogunkanmi et al.
2 citations
Path of Science
Fire Detection and Safety Systems
0.73
article

Innovations in Fire Detection and Suppression Systems for Oil Refinery Operations

Ikechukwu Bismarck Owunna, Onyeka Virginia Ekunke, Temitope Olubanjo Kehinde, Shola Abayomi Ogunkanmi, Jamiu Olaide Oyetunde, Martin Ngwaldi Dillum, Shina Harry Adegoke
article en
2 citations

Abstract

Oil refineries are prone to high fire hazards that involve volatile chemicals combined with extremely high temperatures in confined spaces. These call for advanced fire suppression and emergency response suppression systems. Whereas the traditional sprinkling of water and foam agents have widely been in use, recent studies through the periods of 2020-2024 indicate their inefficiency in effective control within refinery environs on such grounds as water use, environmental impact and adaptability to hydrocarbon-based fires. Those involving automated detection with IoT and AI in predictive fire monitoring, water mist systems for effective flame cooling and control at minimum water consumption and eco-friendly fluorine-free foam agents contribute less to environmental damage. Hybrid suppression technologies, firefighting drones, robots, VR/AR-based emergency training have developed enhanced safety protocols via faster and more focused responses. However, huge gaps exist in scaling these technologies to sustain extreme temperatures and spatial challenges imposed by refineries, apart from all other maintenance issues, cost-effectiveness and regulatory compliance. This review integrates recent progress, confronts such technologies' effectiveness and economic impact, and proposes future research routes focused on sustainability and autonomy while calling for industrial collaboration and adaptive regulations that support even safer and more resilient refinery operations. In all, sensor-fusion systems have been pointed out as the most effective for oil refineries in terms of fire detection. In contrast, firefighting robots and drone delivery systems remain the most reliable for fire suppression. With continuous research, new technology investment and strategic collaboration, the industry will be assured of improved fire safety, contributing to a more sustainable future toward refinery operation globally.

Path of ScienceVol. 10(11)
University of Southern California (US), Ahmadu Bello University (NG), Hong Kong Polytechnic University (HK), University of Ibadan (NG), California Southern University (US), University of Science and Technology of Benin (BJ), Ladoke Akintola University of Technology (NG)
Openalex Percentile: Top 27%
Fire Detection and Safety Systems
0.73
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.