Title: Map simulation of dogs' behaviour using population density of probabilistic model
Authors: Jirawat Jiwattanakul; Chawapat Youngjitikornkun; Worapan Kusakunniran; Anuwat Wiratsudakul; Weerapong Thanapongtharm; Kansuda Leelahapongsathon
Addresses: Faculty of Information and Communication Technology, Mahidol University, Salaya, Nakhon Pathom 73170, Thailand ' Faculty of Information and Communication Technology, Mahidol University, Salaya, Nakhon Pathom 73170, Thailand ' Faculty of Information and Communication Technology, Mahidol University, Salaya, Nakhon Pathom 73170, Thailand ' Department of Clinical Sciences and Public Health, Mahidol University, Salaya, Nakhon Pathom 73170, Thailand ' Department of Livestock Development (DLD), 69/1 Phaya Thai Road, Rajathevi, Bangkok 10400, Thailand ' Department of Veterinary Public Health, Kasetsart University, Chatuchak, Bangkok, Thailand
Abstract: This paper proposes a simulator to demonstrate dogs' behaviours considering individual and group habits, which is designed to be purposefully expandable for disease control. The proposed system is developed using Unity and Mapbox SDK. The normal distribution, kernel density method and probabilistic model are applied to simulate the movement behaviour, world interaction and behaviour rates, respectively. The simulation is validated on an area of Saibai, located in the north-western of Torres Strait islands, Australia. This reports a median tie-strength of 0.0106 which is slightly different from the value calculated from the GPS information of 0.0113. It thus contains the relative error of 6.19%. Then, the simulation is applied to three cities in Thailand. They are all reported with higher tie-strengths, when compared to Saibai. This is because of the significantly higher average numbers of dogs and group distances, with the larger connections between dogs and their communities.
Keywords: dog simulation; unity; Mapbox; probabilistic model; kernel density method; dog behaviour.
International Journal of Computer Applications in Technology, 2021 Vol.65 No.1, pp.14 - 24
Received: 05 Apr 2020
Accepted: 10 Jul 2020
Published online: 15 Mar 2021 *