Machine Learning based Autonomous Fire Combat Turret

The time lag between the identification and initiation of actuation protocol is more in conventional fire combat system. This turn increases response resulting financial loss as well injuries to human beings. In this paper an efficient method proposed eliminate resource loss. system extinguishes before it reaches its destructive level. It eliminates all flaws extinguishers improves damage limitation by raising alarm. Further applying HAAR cascade classifier machine learning algorithm, accuracy 70-75 % achieved detect fire. also provides minimum latency optimal detecting fires differentiating them from false triggers. observed that 2-4 seconds. automatic mode reliable presence multiple units are deployed same area interest. able cover entire hemispheric 3D volume room per industrial domestic safety standards.