  Wildfires are a disastrous phenomenon which cause damage to land, loss of
property, air pollution, and even loss of human life. Due to the warmer and
drier conditions created by climate change, more severe and uncontrollable
wildfires are expected to occur in the coming years. This could lead to a
global wildfire crisis and have dire consequences on our planet. Hence, it has
become imperative to use technology to help prevent the spread of wildfires.
One way to prevent the spread of wildfires before they become too large is to
perform early detection i.e, detecting the smoke before the actual fire starts.
In this paper, we present our Wildfire Detection and Alert System which use
machine learning to detect wildfire smoke with a high degree of accuracy and
can send immediate alerts to users. Our technology is currently being used in
the USA to monitor data coming in from hundreds of cameras daily. We show that
our system has a high true detection rate and a low false detection rate. Our
performance evaluation study also shows that on an average our system detects
wildfire smoke faster than an actual person.
