OHIO team soft launches first sensor in low-altitude weather network

For Ohio State, supporting advanced air mobility research has been a top priority — a priority shared by Chad Mourning, assistant professor at the School of Electrical Engineering and Computer Science, and his collaborators.

In 2021, Mourning received one of the Ohio Federal Research Network awards for a Low Altitude Weather Network (LAWN). His team completed the soft launch of its first unit during the National Advanced Air Mobility Industry Forum on August 22, 2022.

“We have a problem where we go to the weather channel and the satellite tells you the weather at 10,000 feet. There can be a big difference in the weather as we experience it on the ground and the weather at 10,000 feet,” Mourning said.

To mitigate this problem and improve the accuracy of weather forecasts, Mourning’s team, in collaboration with researchers from The Ohio State University and FlightProfilier, was tasked with designing an array of ground sensors to collect data measuring visibility around Springfield-Beckley Airport in Ohio. This network will support the drones with their collected data.

Using machine learning techniques, the team plans to develop a low-cost distributed automated weather observation system (AWOS). Although this project was initiated by the State of Ohio, any progress in developing a cost-effective AWOS would help public and private sector partners improve weather measurement strategies.

“The goal is to deploy 25 of these units at Springfield-Beckley Airport. After the first unit is launched, we still need to improve the machine learning model, so we can label real data with our expected value. to train our model,” Mourning said.

The project has been and continues to be a collaborative effort with external and internal partners. Ohio State University is developing the device case, FlightProfiler receives and visualizes data, and OHIO is working on middleware, including networking, machine learning sensor, and cloud computing.

Within the OHIO team, students Justin Murray, Dylan Wright, Treyce Albin, Hirehalli Ramachandrarajeurs, Sambrama Sathyashreeurs, Lakshmi Kadaru, and Ganesh Sarakadam collectively built prototypes. Using their own skills, the students worked independently on the sensor camera, machine learning program, data visualization, and API.

“These sensors will operate autonomously since they are off-grid and solar powered. If one of them goes down, it’s okay because it’s independent,” Mourning said.

Mourning describes how LAWN will be leveraged in the Internet of Things, a system of things with the processing capability to connect and communicate with other devices in a network. These devices are synonymous with light switches, appliances and thermostats commonly associated with “smart homes”. In this application, however, the network of devices are LAWN’s weather monitoring sensors.

Ultimately, this project has demonstrated the power of collaboration as partners work together to advance advanced air mobility research.

“Once we complete this project, we hope to demonstrate its usefulness to the Federal Aviation Administration, the National Oceanic and Atmospheric Administration, and the State of Ohio,” Mourning said.


Source link