Gene Wolf
Tdworld 13112 April Theory 1
Tdworld 13112 April Theory 1
Tdworld 13112 April Theory 1
Tdworld 13112 April Theory 1
Tdworld 13112 April Theory 1

Asset Management & IoT

April 25, 2018
One very interesting development taking place with these applications is the linking-up of the system with machine learning

In this month’s feature article, I discussed how my car got me thinking about asset management after it sent me an email. That led me into some pretty wild thoughts about how these systems are beginning to impact utilities and grid operators. Since I have been writing a theory column, I thought this would be an excellent opportunity to look at modern asset management systems. They have become one of the most complex elements in our complicated power delivery industry. They have massive amounts of onboard sensors with sophisticated communications that are connected to powerful computers, which gives them an interconnectivity unparalleled on the grid.

In their simplest form, asset management systems keep track of the assets. They store the huge amounts of data generated by the utility’s smart grid equipment. In more complicated systems, they combine that data with data found in their maintenance and operations records and turn it into actionable information. The advanced applications spot trends and produce valuable info the utility can use to schedule maintenance, predict the health of the asset, and determine when the asset needs to be replaced.

Without going into a lot of detail, the more complex asset management systems use an integrated mix of cloud-based computing and data storage combined with other Internet of Things (IoT). The data deluge is converted into useful information that can be acted upon rather than dumped in a hard drive and forgotten. This is something humans really need help with when you start thinking about the giga-bytes of data generated every day by this equipment.

One very interesting development taking place with these applications is the linking-up of the system with machine learning. Machine learning is also referred to as deep learning and artificial intelligence (AI). AI has the ability to perform real-time cognitive understanding and use it to sort through all the risk measures and mitigation activities identified by these enterprise asset managing platforms. Talk about disruptive technology – this is going to be more than a game changer when fully deployed. It’s going to shake the industry to its core.

Here is a short video that gives a great view of the process. Enjoy!

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