One can see that a new 30-foot tower on the edge of the OSU Airport has been erected. However, this has nothing to do with air traffic control of the thousands of take offs and landings at the airport each year.
This tower is the center of a new OSU research project that will look into AI connected to a variety of sensors to monitor the environmental conditions as they happen.
The other key part of the project is the machine learning program that can interpret the data as it is collected. It is a way for researchers understand environmental conditions in urban areas, like noise, air pollution and carbon emissions and how they change in real time.
They will be able to collect data and use AI generated models of all the information to get insights into things like the impact of air travel on the local environment.
National Ecological Observatory Network designed and built the tower. NEON is involved in 81 permanent field sites which are operated by Battelle and are funded by the National Science Foundation. NEON sites across the US collect data on changing ecosystems.
OSU is the first to host temporary and mobile field site using a NEON tower.
Scientists have come up with new machine-learning methods that analyze massive amounts of data to find if existing medications could possibly improve diseases the medications are not prescribed for.
The goal is to speed up what professionals call drug repurposing. This is not a new concept. Botox injections are a great example. Originally it was approved to treat crossed eyes. Now it is used as both a cosmetic wrinkle treatment and a migraine medication.
Until the only way to do this was marriage of luck, expense and time spent conducting what amount to randomized clinical trials to ensure that the drug in question is indeed effective for a disorder for which it was not originally intended.
Researchers at OSU have created a framework to streamline the process, this involves massive datasets of patient care information and high-powered computers. The AI (machine-learning) program analyzes the data at a speed that simply isn’t possible in the real world.
Even though researchers had a very specific focus in their drug repurposing—they looked at drugs that prevent heart failure and stroke—the framework is adaptable to most diseases.
Researchers at the Ohio State University have found a unique use for artificial intelligence; they’ve been using AI to look at satellite images of Cambodia looking for unexploded bombs from the Vietnam War era. This new approach has already drastically increased crater decetion by more than 160%.
The model created by AI combined with declassified military records from the U.S. suggest that as many as 44 to 50% of bombs in the area remain unexploded. Most attempts to find and safely remove unexploded ordinance like bombs and landmines has been much less effective than what is needed in Cambodia.
Researchers found that efforts on the part of Cambodia and their national clearance agency have been concentrating on low risk areas and that there are other areas that present a much greater risk that they should be focusing on.
Researchers stated that until efforts to clear mines has been less effective because no one was able to accurately pinpoint the areas that needed demining the most.
Researchers used machine learning to analyze satellite images for evidence of bomb craters. Between the researchers knowing how many bombs were dropped in the area and the general location where they fell and the AI finding the craters researchers are able to determine with how many bombs exploded and where. They can then determine with more accuracy how many bombs are left unexploded and where they might be found.