Özkan Arslanoğlu’s Post

An AI dataset carves new paths to tornado detection

An AI dataset carves new paths to tornado detection

An AI dataset carves new paths to tornado detection

Tornadoes, the elusive and deadly storms, may finally be within our grasp. With the release of TorNet, a groundbreaking open-source dataset containing radar images of over 200,000 tornadoes from the past decade, researchers are hopeful that machine learning algorithms can help detect and predict these unpredictable phenomena. The dataset, curated by MIT Lincoln Laboratory, offers a unique opportunity for data scientists and meteorologists to collaborate and potentially save lives through more accurate tornado warnings. But with only a 50% success rate in detecting weaker EF-1 tornadoes, and a high false-alarm rate of over 70%, there are still challenges to overcome in using machine learning for tornado detection. How do you think this dataset could help improve our understanding and prediction of tornadoes? --- Hi, 👋🏼 my name is Doug, I love AI, and I post content to keep you up to date with the latest AI news. Follow and ♻️ repost to share the information! #tornadoes #machinelearning #weatherforecasting

An AI dataset carves new paths to tornado detection | MIT News | Massachusetts Institute of Technology: A new open-source dataset called TorNet, released by MIT Lincoln Laboratory researchers, aims to enable breakthroughs in detecting tornadoes. The dataset contains radar returns from thousands of tornadoes that hit the United States in the past decade and is accompanied by models trained on it. Tornadoes are notoriously difficult to forecast, and the dataset, comprising over 200,000 radar images, seeks to address this challenge. The researchers developed baseline artificial intelligence models, including deep learning, which performed well in classifying tornadoes. The release of the dataset and models is intended to encourage collaboration and innovation in the weather community, potentially leading to improved tornado detection and prediction. The ultimate goal is to enhance public safety by reducing false alarms and providing more accurate warnings.

Here is another great use for AI and Geospatial Data, Detecting Floods a week in advance: https://lnkd.in/gz6ahAhS

Stay Ahead of the Storm with Ubicquia! We’re excited to announce the launch of our Storm Response and Vegetation Encroachment Reporting! Using UbiVu® AI models, utilities can now access real-time insights to accelerate storm recovery and mitigate vegetation risks.     Learn how UbiVu® AI can help you stay storm ready: https://lnkd.in/eNzYPitR #StormResponse #UtilityManagement #VegetationManagement

TorNet, a public artificial intelligence #AI dataset, could help models reveal when and why tornadoes form, improving forecasters' ability to issue warnings. In recent years, researchers have turned to #machinelearning to better detect and #predict #tornadoes. However, raw datasets and models have not always been accessible to the broader community, stifling progress. #TorNet is filling this gap. The #dataset contains more than 200,000 radar images, 13,587 of which depict tornadoes. The rest of the images are non-tornadic, taken from storms in one of two categories: randomly selected severe storms or false-alarm storms. MIT Lincoln Laboratory https://lnkd.in/gYf8_gNg

Exciting Legislative Advancements for Wildfire Technology🔥 In the face of increasing wildfire risks, two significant bills—at both State (Colorado) and Federal levels—are paving the way for enhanced technology deployment in wildfire prevention and mitigation. Colorado’s "Applying Artificial Intelligence to Fight Wildfire" (Bill 1) and Section 303 of the Federal HR8790 Fix Our Forests Act offer exciting new opportunities for using AI, remote sensing, and machine learning to better predict, track, and fight wildfires. Learn more about these legislative efforts here: https://hubs.ly/Q02S2SMg0 With over 39,000 wildfires burning 7.4M acres this year alone, it’s encouraging to see bipartisan efforts at both levels of government driving advancements in wildfire technology. #WildfireTech #GIS #AI #ClimateResilience #FixOurForests #congress #policy

📍New Paths in Tornado Detection with AI📍 TorNet, a new AI dataset developed by the MIT Lincoln Laboratory, could revolutionize the detection and prediction of tornadoes, enhancing meteorologists' ability to issue warnings. It contains radar data from thousands of tornadoes in the USA over the past 10 years, as well as information about storms that did not produce tornadoes. TorNet, available as open-source software, includes over 200,000 radar images, of which 13,587 depict tornadoes. Researchers used AI and developed a deep learning model that outperforms previous algorithms, correctly classifying 50% of weaker EF-1 tornadoes and over 85% of EF-2 or stronger tornadoes, where classical methods generate only 30% of correct tornado alerts. AI can help better understand the processes leading to tornado formation, improving meteorologist training and forecast accuracy. TorNet has the potential to enhance the precision of tornado warnings, reducing the number of false alarms and building public trust. This is all made possible by solutions such as deep learning technology, which is also used in developing AI within PRO.display, our system used to control shelf displays. https://bit.ly/3K8N7QI #TornadoDetection #WeatherTech #Meteorology