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Author(s):

Muhamed.J | M SANTHOSH KUMAR | B. AJAY VIGNESH | H. MOHAMED SHAFIQ
Keywords:

IoT, Deep Learning, Fire Detection, Smart Fire Prevention, Smoke Sensor, Temperature Sensor, NodeMCU, Cloud Computing, Smart City
Abstract:
This Paper Presents An IoT And Deep Learning-based Smart Fire Prevention And Suppression System Designed To Improve Fire Safety And Emergency Response Efficiency. Traditional Fire Detection Systems Rely Mainly On Smoke Detectors And Manual Monitoring, Which Often Result In Delayed Detection And Increased Damage. The Proposed System Integrates IoT Sensors, Deep Learning Algorithms, And Cloud Connectivity For Real-time Fire Monitoring And Automated Suppression. Sensors Such As Smoke, Temperature, And Gas Sensors Continuously Monitor Environmental Conditions And Transmit Data To A Cloud Platform Through A NodeMCU Microcontroller. Deep Learning Models Analyze Sensor And Image Data To Accurately Identify Fire Incidents And Reduce False Alarms. When Abnormal Conditions Are Detected, Alerts Are Sent To Users And Suppression Mechanisms Are Activated Automatically. The System Improves Response Time, Enhances Safety, Minimizes Property Damage, And Supports Smart Building And Smart City Applications.