eSmart Systems are proud to be mentioned in Microsofts latest post on their Machine Learning Blog.
Earlier today Microsoft announced the general availability of Azure Machine Learning. In this blog post they use eSmart Systems as an example of a company that apply Azure Machine Learning in interesting business scenarios.
“A traditional smart grid includes multiple data silos, including SCADA networks, building automation systems and substation meters. In this environment, it can be difficult to forecast consumption and prevent bottlenecks or outages. For a utility company, upgrading its entire infrastructure would be costly. Even when upgrades are made, e.g. new smart sensors or meters, data gets collected but is not readily accessible. eSmart Systems uses the Azure cloud platform to integrate and analyze usage data and create forecasts. Azure Machine Learning is the “brains” of the solution, running the data models for predictive analytics. The analytics are used to predict capacity problems and automatically control load in individual buildings”, says the blog post.
Sigurd Seteklev, Chief Strategy Officer of eSmart Systems, says:
“For what we’re doing at eSmart, we needed a cloud solution because of the sheer volume of data being collected; if we were to do it on premise we’d need a lot of storage. We also do a lot of data crunching using Hadoop, which also requires a lot of infrastructure. What we really like about Azure Machine Learning, and Azure in general, is that everything we do is through services available in Azure and we don’t need to monitor virtual machines.”