Silo AI and Vaisala collaborate to offer hyperlocal weather insights in Xweather with deep learning-based data fusion

Silo AI has partnered with Vaisala, a global measurement technology company specializing in developing products and services for environmental and industrial measurement. Silo AI's deep learning experts work closely with the Vaisala Xweather team to improve the detection, characterization, and forecasting of local atmospheric events. Vaisala Xweather is a suite of services that offers real-time and hyperlocal weather and environmental insights. By incorporating hyperlocal weather data, companies can maximize the utilization of their assets, improve risk and hazard awareness, and make their operations more efficient.

Vaisala Xweather is a leading suite of services providing weather and environmental insights that combines software and intelligent sensors by utilizing advanced AI and machine learning technologies. Silo AI has joined forces with Vaisala to further enhance Vaisala Xweather by complementing their measurement technology and domain understanding with Silo AI's deep learning expertise. Together the two are developing solutions that improve the ability to detect, characterize and forecast local atmospheric events. The primary goals of this joint development initiative have been to enhance characterization accuracy and to build new analytics capabilities that use sensors as input data, offering end customers unprecedented amounts of environmental data to support decision-making.

The joint development initiative has revolved around deep learning solutions that fuse data from weather sensors, remote sensing instruments, and other environmental data sources. As a result, Xweather can now, for example, improve road safety by providing more precise information about road conditions along a vehicle's planned route, such as coverage of water, snow, or ice. Additionally, Xweather offers hyperlocal air quality insights that empower city authorities to identify areas of poor air quality, plan mitigation campaigns like smart traffic management, and assess the impact of such activities on street-level air quality.

‍Samuli Hänninen, Head of Xweather at Vaisala comments: 

“Until now, the lack of real-time, local data has been a major source of error in weather and environment forecasting. With Xweather, businesses and developers can utilize data about the environment in real time from a hyperlocal location that is relevant to them. Silo AI’s close cooperation with Vaisala’s domain experts has been extremely valuable. Their strong deep learning capabilities have been crucial in introducing new forecasting capabilities that optimally combine our advanced physical modeling techniques and pioneering sensors with machine learning for unprecedented accuracy.”

‍Peter Sarlin, CEO & Co-founder of Silo AI, says: 

"We are happy to collaborate with Vaisala and bring the latest AI technology to Xweather, helping companies and city authorities to make informed decisions based on hyperlocal weather and environmental data. Ultimately this will help solve environment-related challenges by turning intelligence into climate actions, which is directly aligned with Silo AI's vision of enabling people to have a positive impact with the help of AI."

Read more about Vaisala Xweather here: xweather.com