International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 04 | Apr 2025
p-ISSN: 2395-0072
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Next-Gen Fire Safety: Intelligent Alert Systems and AI-Powered Compliance Verification Nishita Sharma1, Divyanshi Mishra2, Prerna Yadav3, Dr. Hirdesh Sharma4 1 Dept. of CSIT, Dronacharya Group of Institution, Uttar Pradesh, India 2 Dept. of CSIT, Dronacharya Group of Institution, Uttar Pradesh, India
Dept. of CSIT, Dronacharya Group of Institution, Uttar Pradesh, India Assistant Professor, Dept. of CSIT, Dronacharya Group of Institution, Uttar Pradesh, India ---------------------------------------------------------------------***--------------------------------------------------------------------Abstract - Urban infrastructure must comply with fire safety regulations, but the current manual, ineffective, and human error3
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prone inspection and approval procedures are still in place. An AI-powered system that automates real-time emergency alerting, NOC (No Objection Certificate) issuance, and fire safety compliance verification is proposed in this paper. The system incorporates EasyOCR for text extraction from compliance documents, BERT (Bidirectional Encoder Representations from Transformers) for natural language processing to verify regulatory compliance, and YOLO (You Only Look Once) for identifying critical fire safety equipment in uploaded images. Additionally, to improve response efficiency during emergencies, Firebase Cloud Messaging is used to send real-time alerts to fire departments. Delays are reduced, regulatory compliance is guaranteed, and emergency preparedness is enhanced by automating fire safety inspections and compliance verification. By offering an intelligent, data-driven solution that lessens reliance on humans and improves public safety, the suggested system seeks to completely transform fire safety management.
Key Words: Deep Learning , Smart Fire management System, YOLO (You Only Look Once), EasyOCR, BERT, Fire Safety Automation, AI in Emergency Response.
1.INTRODUCTION Ensuring the protection of buildings, infrastructure, and human life depends heavily on fire safety compliance. Strict adherence to fire safety regulations is required by regulatory agencies. This includes having valid compliance paperwork and the necessary fire safety equipment, such as sprinklers, exits, alarms, and fire extinguishers. However, the manual, labor-intensive, and human error-prone nature of traditional fire safety inspection and No Objection Certificate (NOC) issuance processes results in inefficiencies and possible safety hazards. Delays in responding to fire situations can also lead to serious injuries and monetary losses. An AI-driven strategy for fire safety management is required due to the growing complexity of urban growth and the need for quicker and more precise compliance verification. A revolutionary way to automate fire safety compliance, inspections, and real-time alarm production is provided by the quick developments in artificial intelligence (AI), computer vision, natural language processing (NLP), and the Internet of Things. In order to increase the efficiency of emergency response, automate compliance verification, and improve inspection accuracy, this study suggests an intelligent fire safety management system that makes use of several AI technologies. It incorporates: o o o o
YOLO (You Only Look Once) for real-time detection of fire safety equipment in images uploaded by users. This ensures that all required safety measures are in place before issuing an NOC. EasyOCR for extracting textual information from compliance documents, allowing automated verification without manual intervention. BERT (Bidirectional Encoder Representations from Transformers) for analyzing extracted text and matching it against official fire safety regulations, ensuring adherence to government norms. Firebase Cloud Messaging (FCM) for real-time alert generation in case of fire incidents, sending immediate notifications to the fire department with location data and incident images for quicker response.
Traditional fire safety management issues including manual paperwork, phony NOC approvals, inspection delays, and poor emergency response are all addressed by the suggested method. The solution lowers the risk of non-compliance and improves regulatory enforcement by automating fire safety inspections and NOC clearances. Its real-time fire detection and alert system also enhances emergency readiness, allowing fire departments to react quickly and avert possible catastrophes. This research advances the creation of a more effective, scalable, and proactive fire safety system by integrating AI-driven automation into fire safety compliance, thereby enhancing public safety and regulatory transparency.
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