Drone technology will enable monitoring of algal blooms by policy makers, public stakeholders, and other research groups.
A team of University of Windsor students is proposing a more reliable and cost-effective way to monitor contamination in Lake Erie.
Comprised of engineering and law students, the group has entered its idea in Erie Hack— a competition created by the Cleveland Water Alliance and the Creativity and Innovation Team at NASA Glenn Research Center in hopes of accelerating technology solutions to the lake’s most pressing problems.
One of these problems is hazardous algal blooms primarily caused by agricultural runoff. These blooms release harmful toxins, which result in loss of plant and fish life and increase water treatment costs. Monitoring these blooms is a critical part of the mitigation process, says environmental engineering PhD student Mohammad Madani.
“Current methods include satellite imaging, which often falls short as the data is low resolution, inflexible in sampling frequency and often affected by cloud and fog cover, restricting data availability for much of the year,” Madani says.
The UwinTeam is proposing the use of drone technology coupled with spectral imaging hardware and hydrodynamic modeling to provide high-resolution water quality intelligence. The results generated by machine learning algorithms can be analyzed by water quality professionals and used by policy makers, public stakeholders, and other research groups.
“Our method generates higher resolution photos, more frequent sampling and more flexible data collection for a fraction of the cost of traditional methods,” says Saranya Jeyalakshmi, a doctoral student in civil engineering. “Data collected can be coupled with current hydro dynamic and water quality models, increasing understanding of these water systems and allowing for breakthroughs in mitigation and management techniques.”
The team’s law student will examine aviation law, land use planning, environmental law, and international policy to ensure the process is feasible as a real-world solution.