Nature is the most valuable aspect of humanity. Many civilizations and
cultures have flourished in the lap of nature. The forest is the most beautiful treasure in
nature. It always fulfills the basic needs of the lives of the earth’s dwellers. Today, the
forests are depleting quickly. The major cause behind this is forest fires or wildfires.
An uncontrollable fire either occurs naturally or due to human interruption or any other
disturbance caused by nature that may or may not be suppressed by artificial control. A
fire broke out in the Amazon rainforest in 2021 and had a significant impact on this
planet. Researchers have measured the impacts of wildfire on the habitats of 14,000
species of plants and animals, finding that 93% to 95% suffered from some
consequences of the fires. In 2020, Australia’s forest fires caught the world’s attention.
Wildfires are a major challenge for humans in today’s time. Early identification of
forest fires is the only way to mitigate the risk of damage.
Researchers are working on various techniques to detect the fire early. Several existing
approaches, like wireless sensor networks, machine learning, and remote sensing, are
used to identify wildfires. Some researchers are using UAVs to identify forest fires. In
most cases, the researchers are focused only on prediction using some environmental
parameters sensed by the sensors or images captured by the satellites. This paper
highlights the various challenges in the prediction of forest fires using the WSN
paradigm.
Keywords: Forest fire, Mobile node, Path generation, Rarefied flow, WSN.
