Research Article
Learning About Animals and Their Social Behaviors for Smart Livestock Monitoring
@INPROCEEDINGS{10.1007/978-3-319-47075-7_53, author={Jo\"{a}o Ambrosio and Artur Arsenio and Orlando Rem\^{e}dios}, title={Learning About Animals and Their Social Behaviors for Smart Livestock Monitoring}, proceedings={Internet of Things. IoT Infrastructures. Second International Summit, IoT 360° 2015, Rome, Italy, October 27-29, 2015, Revised Selected Papers, Part II}, proceedings_a={IOT360}, year={2017}, month={6}, keywords={Cloud computing Learning Internet of intelligent things Smart livestock management Social behaviors Wireless sensor networks}, doi={10.1007/978-3-319-47075-7_53} }- João Ambrosio
Artur Arsenio
Orlando Remédios
Year: 2017
Learning About Animals and Their Social Behaviors for Smart Livestock Monitoring
IOT360
Springer
DOI: 10.1007/978-3-319-47075-7_53
Abstract
Things are increasingly getting connected. Emerging with the Internet of Things, new applications are requiring more intelligence on these things, for them to be able to learn about their environment or other connected objects. One such domain of application is for livestock monitoring, in which farmers need to learn about animals, such as percentage of time they spend feeding, the occurrence of diseases, or the percentage of fat on their milk. Furthermore, it is also important to learn about group patterns, such as flocking behaviors, and individual deviations to group dynamics. This paper addresses this problem, by collection and processing each animal location and selecting appropriate metrics on the data, so that behaviors can be learned afterwards using machine learning techniques running on the cloud.
