Buying into IoT comes with a wealth of benefits, but adopting heavy use of the internet of things means more than plugging in devices and waiting for the data to pour in; it means modifying network infrastructure to accommodate them.
This is not a trivial consideration. If the network doesn’t adequately support all aspects of IoT, a company may be unable to take advantage of all that data and will fail to realize the return on investment it was hoping for.
The Internet of Things (or IoT) sounds like one of those futuristic buzzwords that’s still just a little too far off to think much about. But the IoT — where once-unconnected things like watches, cars, healthcare equipment, etc. will be connected to the Internet — is already here, and it’s changing our health, how we build things, and how we get around, and creating billions of dollars in value across multiple sectors.
Industrial Internet of Things (IIoT) is already revolutionizing domains such as manufacturing, automobiles and healthcare. But the real value of IIoT will be realized only when Machine Learning (ML) is applied to the sensor data. This article attempts to highlight how ML augments IIoT solutions by bringing intelligent insights.
The Internet of Things (IoT) has been called the next Industrial Revolution, and it will have a profound effect on how marketers will need to understand, market and track consumers in the years ahead.
In fact, BI Intelligence, in a 2015 report, estimated that more than 34 billion devices will be connected to the internet globally by 2020, up from 10 billion in 2015. This includes a mix of standalone devices that can be monitored and/or controlled from a remote location, as well as remote-enabled devices (such as smartphones, connected/smart TVs, smart home and smart assistants like Amazon’s Echo).