Phase-Type Distributions of Animal Trajectories with Random Walks

Rodolfo Vera-Amaro (), Mario E. Rivero-Ángeles and Alberto Luviano-Juárez
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Rodolfo Vera-Amaro: Academia de Telemática-UPIITA, Instituto Politécnico Nacional, Av. IPN 2580, Col. Barrio la Laguna Ticomán, Ciudad de Mexico 07740, Mexico
Mario E. Rivero-Ángeles: CIC, Instituto Politécnico Nacional, Av. Juan de Dios Bátiz S/N, Nueva Industrial Vallejo, Gustavo A. Madero, Ciudad de Mexico 07740, Mexico
Alberto Luviano-Juárez: SEPI-UPIITA, Instituto Politécnico Nacional, Av. IPN 2580, Col. Barrio la Laguna Ticomán, Ciudad de Mexico 07740, Mexico

Mathematics, 2023, vol. 11, issue 17, 1-30

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

Keywords: random walk; animal monitoring; animal trajectory generation; phase-type distributions (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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