Phase-Type Distributions of Animal Trajectories with Random Walks

Animal monitoring systems often rely on expensive and challenging GPS-based to obtain accurate trajectories. However, an alternative approach is generate synthetic trajectories that exhibit similar statistical properties real These can be used effectively in the design of surveillance such as wireless sensor networks drone-based techniques, which aid data collection delineation areas for animal conservation reintroduction efforts. In this study, we propose a generation method utilizes simple phase-type distributions produce By employing probability distribution functions based exponential distribution, achieve highly approximations movement patterns four distinct species. This significantly reduces processing time complexity. The research primarily focuses generating endangered species, comprising two terrestrial flying order demonstrate efficacy proposed method.