In this day and age, the majority of herding work is performed manually; herds of livestock such as cattle are handled in-person by ranchers, who could be using this time for other work. Our project consists of an end-to-end system for automating the task of herding livestock. The automation is done by placing GPS-enabled, low-power smart collars onto each animal, and using these collars to track the animals’ locations. In the event that an animal leaves the grazing area it has been allotted, the smart collars will emit a noise or electrical shock, directing the animal to return to its previous location. Data from the smart collars is collected over a long range LoRaWAN network into a centralized gateway server, which also allows users to remotely configure and view collars in the field. The collar exposes this functionality to an Android application through a JSON REST API, enabling ranchers to perform common tasks on the collars through their mobile phone or tablet. LoRaWAN’s ability to reliably send data to large numbers of devices over kilometers of distance allows our system to work even with large farms with many animals. Client: Dr. Bechir Hamdaoui, School of Electrical Engineering and Computer Science, Oregon State University Ryan Alder (alderr@oregonstate.edu) Danila Fedorin (fedorind@oregonstate.edu) (https://danilafe.com/) Matthew Sessions (sessionm@oregonstate.edu)