Author Login IJIRT Partner Network (IPN) Login

FIRE HAZARD DETECTION VIA VISION BASED MACHINE LEARNING SYSTEMS

  • Unique Paper ID: 174555
  • Volume: 11
  • Issue: 11
  • PageNo: 4-8
  • Abstract:
  • The objective of this project is to develop a real-time fire hazard detection system using YOLOv5, a state-of-the-art object detection algorithm. This system aims to enhance fire safety by providing timely alerts and accurate detection of fire hazards. Key features of the system include: Early detection of fire hazards, allowing for prompt action. Real-time alerts for users, ensuring immediate awareness of potential threats. High accuracy with minimal false positives, reducing unnecessary alarms. Robust performance in diverse environments, adapting to various conditions. The anticipated outcome is a reliable system for fire detection that can be effectively utilized in industrial, residential, and forest environments, ultimately contributing to enhanced safety and risk management
Download article email to a friend

Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 11
  • PageNo: 4-8

FIRE HAZARD DETECTION VIA VISION BASED MACHINE LEARNING SYSTEMS

Related Articles

Impact Factor
8.01 (Year 2024)
UGC Approved
Journal no 47859

Join Our IPN

IJIRT Partner Network

Submit your research paper and those of your network (friends, colleagues, or peers) through your IPN account, and receive 800 INR for each paper that gets published.

Join Now

Latest Publication

Archive

View More

Recent Conferences

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024 Last Date: 15th March 2024

Submit inquiry