Generation of synthetic trajectory data

 Suggested by: Thomas Schneidergruber, Johannes Scholz 

Keywords: Synthetic Data, Trajectory Generation, Generative AI, Landscape-Aware Simulation, Elevation Data, Cow Movement, Spatial Modeling, AI in Agriculture 

 

Objective: Develop a generative AI model capable of producing realistic synthetic cow trajectories based on specified geographic locations, incorporating landscape and elevation data to enhance realism. 

 

Short Description: This thesis explores the use of generative AI techniques to synthesize cow movement trajectories in a given geographical area. By integrating landscape and elevation data, the model aims to generate realistic movement patterns that mimic natural behavior. The research will focus on data-driven trajectory modeling, spatial constraints, and validation against real-world movement data. 

 

Start: 

As soon as possible 

 

Prerequisites/qualification: 

• Interest/knowledge in Machine Learning 

• Programming (Python) 

• Knowledge in GIS and spatial data processing