Autonomous Lightweight Green Algae Evaluation
Format
SOECS Senior Project Demonstration
Faculty Mentor Name
Rahim Khoie
Faculty Mentor Department
Electrical & Computer Engineering
Additional Faculty Mentor Name
Elizabeth Basha
Additional Faculty Mentor Department
Electrical & Computer Engineering
Abstract/Artist Statement
The growth of algae is a vital issue for watersheds, and monitoring these algal blooms can provide useful data on the health of the local environment. However, most equipment that is used to measure water conditions and algae concentration is bulky and expensive, which is prohibitive to field testing. Additionally, many bodies of water are in remote locations that are difficult to access by car or on foot. Our autonomous algae drone addresses these issues with a low-cost sensor package that can attach to an autonomous drone. The sensor array will measure five key parameters: pH, salinity, depth, temperature, and algae concentration. For the crucial measurement of algae concentration, we intend to use a combination of fluorescence and image processing. Preliminary testing has shown that at least partial submersion will be necessary for our device, and final testing will be completed next semester on the Calaveras River. This project will result in improved methods for autonomous field-testing of water and algae in critical watersheds.
Location
School of Engineering & Computer Science
Start Date
4-5-2019 2:30 PM
End Date
4-5-2019 4:00 PM
Autonomous Lightweight Green Algae Evaluation
School of Engineering & Computer Science
The growth of algae is a vital issue for watersheds, and monitoring these algal blooms can provide useful data on the health of the local environment. However, most equipment that is used to measure water conditions and algae concentration is bulky and expensive, which is prohibitive to field testing. Additionally, many bodies of water are in remote locations that are difficult to access by car or on foot. Our autonomous algae drone addresses these issues with a low-cost sensor package that can attach to an autonomous drone. The sensor array will measure five key parameters: pH, salinity, depth, temperature, and algae concentration. For the crucial measurement of algae concentration, we intend to use a combination of fluorescence and image processing. Preliminary testing has shown that at least partial submersion will be necessary for our device, and final testing will be completed next semester on the Calaveras River. This project will result in improved methods for autonomous field-testing of water and algae in critical watersheds.