Aim:
Ā Ā Ā Ā Ā Ā Ā Ā Ā To efficient RCNN based system for fire detection in videos captured in uncertain surveillance scenarios
Synopsis:
Ā Ā Ā Ā Ā Ā Ā Ā Ā Vision based fire detection framework has lately picked up popularity when contrasted with customary fireĀ recognition framework dependent on sensors. The need ofĀ video perception at private, Modern, business regions andĀ woods areas has expanded the use of vision based fireĀ acknowledgment system Recently lots of fire related accidentsĀ has occurred due to improper Surveillance or unable to coverĀ those uncertain regions like restricted areas in forest or anyĀ factory buildings. In order to overcome such accidents , weĀ propose a new method using Convolutional neural networks (RCNN).
Proposed System
Ā Ā Ā Ā Ā Ā Ā Ā Ā We propose an efficient RCNN based system for fire detection in videos captured in uncertain surveillance scenarios. Our approach uses light-weight deep neural networks with no dense fully connected layers, making it computationally inexpensive. Once detect a fire the information will pass through the firebase. Firebase is a one type of database. Then the firebase to sendĀ a notification in android smartphone.Ā Ā Ā Ā Ā Ā Ā
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