Visualizing Animal Activity using Intelligent Tags

Abstract: Supervising animals is a significant task in many contexts, for example the keep-ing of cattle and protection of endangered species in sanctuaries, like the blackrhino. Digital solutions exist but can be improved further to ease the workflowof the supervision. This project combines the integration of intelligent tags withinformation visualization and user interviews to develop a dashboard displayinganimal activity. Using positional data from GNSS tags on cows, possibilities wereexplored in terms of modifying and condensing the data to support the detectionof patterns and anomalies in animal behavior. Through a pre-study of interview-ing people with previous knowledge, an effect map and design prototype was cre-ated to determine a scope for the content of the dashboard. The prototype wasthen technically implemented into a dashboard consisting of an information box,a heat map with frequent positions, a graph with hourly distance, a graph withdaily activity compared to previous periods and herd activity and a graph giv-ing information about proximity to other animals. The dashboard was evaluatedthrough four user surveys, with two Kenyan users and two Swedish users. It wasshown that the user had the ability to detect patterns and anomalies from graphsbased only on positional data from GNSS tags. Clustering with the BIRCH algo-rithm was also found to be useful for condensing a large amount of positionaldata. Similarities in the work with animals and possible solutions were foundbetween Sweden and Kenya, such as interest of frequent positions and monitor-ing reproduction. However, improvements can be made in terms of introducingother types of data and notifying users of sudden events. Bluetooth tags provid-ing accelerometer and step count data were investigated briefly but have to bedeveloped further to detect a larger variety of activities.