A Sensor System to Track Individual and Social Animal Behavior in the Wild
thesisposted on 06.08.2019 by Riccardo Pressiani
In order to distinguish essays and pre-prints from academic theses, we have a separate category. These are often much longer text based documents than a paper.
Nowadays, biologists and social scientists are interested in understanding fundamental evolutionary, ecological, and population processes, such as decision making and activity recognition in a group of individuals. Collective behavior of animals like fish or birds is governed by local mathematical rules. However, discovering the rules and the dynamics in more complex societies requires a different approach. In this thesis research work, I developed a sensor system to remotely extract data from social wild animals. The system is currently designed for Olive baboons, which have been our target species for this stage of the project. The system is composed of a main sensor unit which is located in a collar for and at least one secondary unit that we designed as a bracelet. The main unit is composed of a GPS, a 9 axis IMU and a microphone. It provides Wi-Fi and Bluetooth connectivity to allow the primary and secondary units to communicate, as well as to extract the data from the system remotely. We exploit the Bluetooth Low Energy to implement a proximity sensor. The secondary unit is equipped with a 6 axis IMU. The expected outcome of this project is a long-term deployment of the designed units on a troop of wild baboons in an uninstrumented environment. For this reason, the specifications for the device to be developed raised a set of new challenges to be addressed. Among them, the whole system will need to be tolerant of possible hardware faults while the energy consumption needs to be monitored and reduced as much as possible. The proposed work will allow scientists to have a deeper and more granular understanding of animal behavior on a long-term basis. The benefits of this setting will be empowering the scientific community with useful data and information to address animal conservation issues. Moreover, this technology could be adapted to other environments rather than the wild one, such as the possibility to study animals in agricultural, domestic, and habituated settings (such as zoos). This will make an impact on the productivity and efficiency of farms, veterinary health, and well-being of domesticated animals.