Computer Vision for Wild Life Animal Tracking for Bio-diversity (Inventory)

Develop Raspberry Pi I based camera for computer vision projects for monitoring wildlife at the School of Agriculture and Food Sciences Hidden Vale Teaching & Learning Facility. Design power management solutions for remote deployment and software optimization to extend battery life. Evaluate transmission solutions for WIFI or by using alternative radio technologies for optimal image data transmission. Also evaluate local vs remote computer vision processing.

Location: Gatton campus

Supervisor: Professor Kim Bryceson