Chronic Wasting Disease (CWD) Prediction, Modeling and Mapping
Project utilizing Python tools to process and inspect images provided by volunteer land owners and hunters. Compare images of confirmed CDW positive deer harvested and inspected at Fish and Game inspections stations, when leveraged with all other available data to help predict where CWD will either appear or increase to allow Fish and Game and how to better manage and reduce the impact of the disease. (Sustainable Agriculture, Big Data, Machine Learning, NoSQL)
Data Acquisition Utilizing Drone Technology with Swarm Methodologies
Creating autonomous inspection and data collection tools for remote data gathering. Several applications under development, including crop and health and vigor data. The use of swarms of commodity priced drones improves data collection and efficiency while keeping costs low. This project involves Big Data and NoSQL solutions to store and process the large amounts of images captured.
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