Hunting the hunters: Wildlife Monitoring System

During the last decades, there has been a dramatic rise in number of illegal animal poaching incidents. Wildlife Monitoring Systems (WMSs) are emerging as a solution to help reduce poaching incidents by monitoring the activities of wild animals. The technological advances in low-power wireless networks have paved the way to exploit their potential for utilizing in wireless based WMS. One of the fundamental difficulties for utilizing existing wireless based WMS is the lack of full network connectivity provision due to the sparsely con-specific mobility behaviour of wild animals. Unlike static network applications, where the proximity among sensor nodes is fixed, wild animals often show signs of movement which alters the spatial proximity between neighbouring sensor nodes.

To address this challenge, this thesis deals with leveraging short-rage radio and lowpower wide area networks to provide a communication network architecture that is energy-efficient, reliable, and has a low latency. We present a single-hop, multi-hop,
and opportunistic multi-hop hybrid tree network architecture for WMS.

Moreover, in wildlife monitoring applications, WMS often has to deal with frequent herd mobility. We address this issue by applying a herd-movement adaptive scheme. The particular focus of this technique is to have a strategy to adapt to the movement pattern of animals to make the communication network more efficient. We developed a mobility state driven data advertising control scheme based on an unsupervised learning algorithm. In addition, we implement a managed data dissemination scheme with controlling and prioritizing data replication function. In contrast to existing forwarding algorithms, it optimally makes data forwarding decisions by utilizing locally accessible information. Hence, the proposed algorithm adapts to dynamic network topology caused by the inherent sporadic connectivity among mobile herd of animals.

Finally, the application of WMS communication network is demonstrated for inferring movement of an animal from the received signal information. This is introduced by using short-range radio for proximity and relative ranging as an alternative approach for the current use of GPS to examine the mobility interaction between wild animals. The developed animal movement analysis framework helps to infer how animal population density changes due to certain natural disturbances and how the animals interact to one another.