Car driving in the rain

Fathym Adopts New Location Based Services from Microsoft to Deliver Enhanced Functionality for Customers

Fathym’s Road and Route Weather Forecasting to be featured at the LA Auto Show and AutoMobility Conference in the Microsoft Booth.

Boulder, CO – November 28, 2017 – Fathym announces it will utilize Microsoft Azure Location Based Services to power its surface weather forecast. Azure Location Based Services is a set of cloud capabilities that provide geographical data to power smart cities and Internet of Things (IoT) solutions natively integrated into the cloud. It’s currently in public preview.

Combining Fathym’s hyper-local, global forecast with Azure Location Based Services, Fathym has improved on its road weather routing and point forecast application. The application gives fleets and autonomous vehicles data for better routing around hazardous weather to improve ETA accuracy, cost savings and driver safety. Fathym is currently testing the new Azure Location Based Services functionality with plans to bring the additional features to customers later this year.

Fathym will highlight its surface weather forecast at AutoMobility LA, a conference focused on the future of transportation. The prototype will be featured at the Microsoft Booth #138 in the Technology Pavilion. Fathym sees better access to road weather data and integrated Internet of Things solutions as being critical technologies for the future of connected and autonomous vehicles.

“Azure Location Based Services is a radical improvement for layering information on top of maps,” said Matthew Smith, CEO of Fathym. “We see it as a modern approach to mapping and data services. What took Fathym hundreds of lines of code on other mapping services, has been reduced to just a few. The integration with the rest of Azure makes it convenient to pair Azure Location Based Services with Azure IoT services. This will be a huge value add to our customers.”

Fathym offers a globally-scaled, hyper-local road weather route and point forecast engine, optimized by a network of road weather sensors. The forecast’s unique risk variables, including crosswind and low visibility, offer further insight to weather-related delays and is already deployed by customers like the Alaska Department of Transportation and Swift Transportation.

“Fathym is showcasing an innovative use of Microsoft Azure Location Based Services, providing critical geospatial data that will bring additional intelligence to Fathym customers,” said Chris Pendleton, Principal Program Manager, Microsoft Azure IoT at Microsoft Corp. “Azure Location Based Services provides customers a platform with large data sets and deep integration with other data graphs that will light up mapping scenarios that don’t yet exist.”

Behind the scenes, the Fathym Framework enables rapid and scalable enterprise IoT solutions by providing the services and platform to ingest device or user-based data, and create the alerts, analytics and systems necessary to turn that data into actionable intelligence that optimizes operations.

Big Data Analysis of routes, speed, direction and operational threats such as high crosswinds, low visibility and slick roads alert drivers prior to an adverse weather event occurring. An intuitive visual interface shows drivers their route and the forecasted weather variables, while truck-ahead alerting can provide real-time observations to other connected vehicles, lowering weather-related accidents.

Introducing the Fathym Forecaster
The Fathym Forecaster is a robust, feature-rich API that offers a powerful suite of weather forecasting and open-source data visualization tools. The Forecaster combines the world’s best weather forecasts with statistics-based, machine-learning techniques to tackle the largest datasets, including road weather.
The Fathym Forecaster offers developers comprehensive weather forecasting capabilities over freely chosen locations and routes across the globe, with any combination of variables. The API delivers a unique suite of highly specialized forecast variables derived through statistically based machine learning models.
Get started exploring the forecaster’s capabilities today for free.

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