Abstract:
Heedless deforestation together with industrialization has led the world towards global warming from the north pole to the south pole, since the early 1990s. As per the Scientists, this can lead to disaster if this continues like that. (Irfan et al, 2019). Thus year 2019 has been able to strike the highest number of forest fires worldwide since 2010 highlighting the necessity to address this overarching theme. Considering this world’s upcoming issue, current study has been focused towards inventing an automotive, self-charging robot who can identify the disaster sites and alarm the necessary authorities. Therefore, the current study was designed with the general objective of overcoming the drawbacks within the existing research projects, related to the difficulties that faces during, distribution of the sensors in complex outdoor environments, battery charge, battery life and come up with an accurate cost effective forest fire detection methodology using image processing. The project Automatic Forest Fire Detection Robot introduces a novel approach to forest fire detection systems. The system proposed in this project primarily addressed on developing an automotive forest fire detection robot which can navigate through obstacle, and aid to detect foci of forest fire at an early stance. Moreover, this project showcases that image processing technique together with the CNN can be used to achieve a higher accuracy rate, that s nearly 96.98 % and that has been the highest accuracy marked within the current context.
