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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: April 2026
Volume 11 | Issue 4
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 119
Article Submitted : 23355
Article Published : 9033
Total Authors : 23952
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| Paper Title: | A Hybrid YOLOv11–EfficientNet Approach for Real-Time Fire and Smoke Detection |
| Authors Name: | VISHAL NISHAD , Komendra Kumar Dhruvey , Tarun Kumar Sahu , Shiv Kumar Sao , Liza Patel |
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IJRTI_211614
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| Published Paper Id: | IJRTI2604173 |
| Published In: | Volume 11 Issue 4, April-2026 |
| DOI: | |
| Abstract: | In this paper, we introduce a real-time, AI-powered system for detecting fire and smoke through security cameras, specifically designed to drastically reduce false alarms. Traditional smoke detectors are often slow and only cover small areas, while standard camera-based systems easily get tricked by bright lights or reflections. To solve this, our system combines two models: YOLOv11 to quickly spot potential danger zones, and EfficientNet-B4 to carefully classify those areas as fire, smoke, or just normal lighting. The system evaluates both the specific hot spots and the overall scene to make a confident decision, then double-checks its results across multiple video frames to ignore quick camera glitches. We trained our models on about 35,000 images so they can reliably handle real-world situations. In our tests, the system hit 92.8 percent accuracy and slashed false alarms from 12.8 percent down to just 2.4 percent. Plus, it runs smoothly in real time at 20 to 25 frames per second. Overall, it is a practical, ready-to-use solution built to keep people safe and scale up as needed. |
| Keywords: | Fire and Smoke Detection, Real-Time Object Detection, Hybrid Deep Learning, False Positive Reduction, YOLO-Based Detection, and Real-Time Video Surveillance |
| Cite Article: | "A Hybrid YOLOv11–EfficientNet Approach for Real-Time Fire and Smoke Detection", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 4, page no.b267-b274, April-2026, Available :http://www.ijrti.org/papers/IJRTI2604173.pdf |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2604173
Registration ID:211614
Published In: Volume 11 Issue 4, April-2026
DOI (Digital Object Identifier):
Page No: b267-b274 Country: Raigarh, Chattisgarh, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2604173 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2604173 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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