Case: Hurricane Unwinder
Improve situational awareness with computer vision
This webinar was streamed live and recorded on December 16, 2020. You may watch the recording by clicking to webinar page & filling our the form.
Understanding the current situation is extremely valuable in many environments, ranging from manufacturing, managing operations to planning and executing complex logistics. Weather often plays a key role in forecasting the future outcomes of a planned process, but many other steps can be analyzed with computer vision too.
In our webinar on Computer vision for situational awareness, you’ll learn:
- How AI helps with assessing the situational awareness of both internal and external factors, such as port operations, factory environments, or weather.
- How to improve situational awareness with computer vision: typical pitfalls and how to avoid them.
- How Silo AI together with Hurricane Unwinder evaluated the cyclone intensity with computer vision.
Concrete cases for computer vision
The first part of the webinar will dive into improving situational awareness with computer vision. With concrete reference cases we will demonstrate the value of computer vision in getting insights about how many vehicles are present at a certain location, how many parcels have passed by and are waiting to be treated, as well as how many cargo ships are currently at a certain port.
Case Hurricane Unwinder & scientific deep-dive with a computer vision expert
In the second part, Svante Henriksson from Hurricane Unwinder, a company lead by former Finnish Meteorological Institute researchers, teach how to revolutionize the way tropical cyclones are being tracked. Together with Hurricane Unwinder, we’ve built a computer vision solution that predicts tropical cyclones in the coastal areas of the Atlantic, the Pacific and the Indian Ocean and forecasts the hurricane intensity. The solution won the ESA’s Earth observation award Copernicus Masters in 2018.
– Traditional numerical weather forecasts are not able to forecast the intensity of the storm at the same level of detail as satellite images do. There is no existing computer-vision-based product to predict intensity changes, although scientific research supports the approach. With the help of Silo AI, we’ve been able to create the world’s first forecasting solution with world-class accuracy, says Svante Henriksson, CEO of Hurricane Unwinder.
After Svante’s part, Silo AI’s computer vision expert, Senior AI Scientist Nico Holmberg will explain some of the details in working with satellite images and computer vision.
Dr. Svante Henriksson, CEO at Hurricane Unwinder
Svante Henriksson is the CEO and Founder of Hurricane Unwinder, with a strong climate research background of over 11 years. Svante has researched hurricanes and the reasons behind the formation of very strong winds at the Finnish meteorological institute for over 5 years. Svante also has experience in renewable energy and fusion energy, teaching and economics.
Dr. Niko Vuokko, Lead AI Architect at Silo AI
Niko Vuokko heads Silo AI’s product development and technology. He is actively involved in company strategy and business development and specializes in data-driven B2B. Niko holds an olympic medal in mathematics, PhD in data science, and a broad background in software. Niko is a former Director, Strategy and Business Development at Eniram.
Niko Holmberg, AI Scientist at Silo AI
Nico is an experienced machine learning expert, specialized in building computer vision solutions to improve situational awareness or forecasting, with methods like object recognition and segmentation to video analytics. Nico has a PhD in Computational Quantum Chemistry from Aalto University. In academia, Nico’s research focused on developing new methods to design effective materials for renewable energy applications.
Pauliina Alanen, Communications & Marketing Lead at Silo AI
Pauliina is a communications and marketing professional with a strong background in B2B, technology and startups from both Silicon Valley and the Nordics.