About this research

Animal movement patterns are indicators of many factors. The grazing capacity of the landscape, and the animal grazing habits can be determined by the time spent in an area. Change in local weather, and ecological conditions cause a change in these habits, and human presence causes uncommon change in this behaviour. Since a few decades, many organizations, zoos and individuals have tagged animals to collect geo-locations data for biodiversity research as well as for management purpose. In conservation particularly, location datasets are used to map species’ home ranges, and, when used in near real-time, to enhance law enforcement, mitigate human-wildlife conflicts. While our literature review has found no previous research that combines local biotope condition, real-time or near-real-time poaching indicators with location timeseries to evaluate the change in animal behaviour, we used Garamba’s African Elephants data to implement an Animal Movement Patterns analyser using Bayesian Networks. Local biotope data comprises climate, landcover and topography, as well as infrastructures (road, villages, rangers’ installations…). Animal behaviour will be calculated based on variables considered from our literature review. A Bayesian Network AI will be implemented to alert of any Outstanding patterns.