An enhanced real-time forest fire assessment algorithm based on video by using texture analysis

As the human technology moved further, the risk of natural and man induced sudden damage increase exponentially. One of the most dangerous disasters is fire. In addition to its direct danger on human's lives, fire consumes forests where trees that provide humans with oxygen are destroyed. Every year, the large number of wildfires happening all over the world they burn forested lands, causing adverse ecological and social impacts. Early warning and immediate responses are the only ways to avoid such type of disasters. This work describes a naïve method is used to detect flames in forest by using a Spatio Wildfire Prediction and Monitoring System (SWPMS). Basically, the fired information retrieving from regions by using background subtraction and colour analysis. The fire behaviour is modelled by texture analysis using computer vision systems. The Central Server should receives fired regions from the volunteer's smart phone and use fired location coordinates, different angles of smart phone receives fired locations based on Google Earth API. Finally, Kalman filter estimator computes the position vector of a moving object. Antennas or Satellite systems are grasping information from fire regions then GIS will be analyzed those regions and send alert to local peoples of forest regions and NDRF team