Harness real-time data for smarter cities, buildings, and transportation
Azure Gov Team
This article was co-authored by Christy Szoke, CoFounder/CMO of Fathym, and the Azure Gov Team
Wherever you live, you’re probably all too aware that inclement weather can have a serious impact on citizen safety and city budgets. And until recently, municipalities affected by changing road and weather conditions didn’t have easy access to the data they needed to respond proactively. Now, thanks to recent advances in the Internet of Things (IoT), communities can make faster, more informed decisions based on hyper-local road weather data, improving road safety and operational efficiency.
In Fairbanks, Alaska, the state’s Department of Transportation needed a way to make important decisions such as whether to de-ice the roads as a snowstorm approaches or during the storm. Fairbanks turned to IoT solutions provider Fathym and their WeatherCloud solution, a sophisticated weather tracking product suite that provides a more complete understanding of real-time road weather utilizing Azure IoT Hub.
Fathym is continuing to deliver innovation built on Azure to simplify and accelerate the deployment of IoT solutions, extending their unique expertise in connecting real-time data from disparate sources to help organizations make better decisions. Michael Gearhardt, CTO of Fathym, says “Because Azure IoT Hub is an open and flexible cloud platform that supports open-source SDKs and multiple protocols, we’re able to innovate faster to create new solutions for our customers, in both private and public sectors.”
Because Fathym seamlessly merges data from disparate silos and sensors, it reduces the time to build enterprise-grade IoT solutions and data applications from months to just a few weeks, or even days. Fathym’s tools are designed so operations staff can create and continuously evolve solutions that fit the needs of the organization, freeing up developers for other priorities. Fathym’s Data & Device Framework is built for flexibility and collaboration, enabling users to easily filter and fuse data, pair data streams with visualizations, build any number of dashboards and apps, and re-configure solutions at any time.
Transportation Departments are using Fathym to provide real-time weather data combined with input from IoT sensors to manage everything from repaving roads in the summer season to salting more efficiently in the winter season:
- With real-time data, transportation teams can more easily monitor the temperatures of pavement in different areas, helping them assess when it’s safe to drive.
- Through volumetric assessment of salt and gravel piles using a Lidar device, transportation departments can increase the accuracy of their inventory estimates from within 10-15% to within 2-3%, reports Ryan Sappenfield, Fathym Director of Data Engineering and Analytics.
- Leveraging real-time weather data for decision making can help agencies keep airports and other transportation services operational when big storms sweep the nation. Combining this with other IoT data can help airports forecast the flow of people, traffic, and even janitorial services required when unexpected events occur.
- In addition, Fathym provides supply chain connectivity, leading to more efficient distribution of resources based on the latest weather data.
Fathym is also working with several renewable energy customers, using existing and new sensors to monitor solar and wind, and combining this with WeatherCloud forecast data to provide predictive information about demand and the type of energy source best suited to meet this demand. Using IoT systems that can predict microclimates, energy producers can better predict what energy sources are going to be needed at what time, making the grid more efficient and helping organizations optimize across various energy sources.
Based in Boulder, Colorado, Fathym is an innovation framework for the rapid development and deployment of enterprise Internet of Things solutions. Fathym’s WeatherCloud solution combines proprietary algorithms and machine learning with sensor and atmospheric weather observations to provide the only globally-scaled road and atmospheric weather forecast system in the world.