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Ai-Enabled Droplet Detection And Tracking For Agricultural Spraying Systems, Praneel Acharya, Travis A. Burgers, Doang Nguyen
Ai-Enabled Droplet Detection And Tracking For Agricultural Spraying Systems, Praneel Acharya, Travis A. Burgers, Doang Nguyen
Mechanical Engineering Faculty Publications
his work leverages recent advancements in com- puter vision and deep learning to detect and track the motion of droplets captured by a camera. While classical computer vision techniques have been employed for detection and tracking, those approaches have limitations and are not trivially extended to droplets. We approach the problems of droplet detection and tracking through a data-driven framework, in which an annotated database of droplet images is built and object detection and tracking models are trained on this database. The accuracy of the model is evaluated and the whole process is discussed. At this point, droplet geometric properties …
Vision And Radar Steering Reduces Agricultural Sprayer Operator Stress Without Compromising Steering Performance, Travis A. Burgers, Kelly J. Vanderwerff
Vision And Radar Steering Reduces Agricultural Sprayer Operator Stress Without Compromising Steering Performance, Travis A. Burgers, Kelly J. Vanderwerff
Mechanical Engineering Faculty Publications
Self-propelled agricultural sprayer operators work an average of 15 h d-1 in peak season, and steering is the task that causes the operator the most stress because of the large number of stimuli involved. Automatic guidance systems help reduce stress and fatigue for operators by allowing them to focus on tasks other than steering. Physiological signals like skin conductance (electrodermal activity, EDA) change with stress and can be used to identify stressful events. The objective of this study was to determine if using a commercially available vision and radar guidance system (VSN®, Raven Industries) reduces agricultural sprayer operators’ stress …