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He says : “ You don ’ t need to keep feeding back data about that piece of equipment . The only data you want to capture is if something changes – for example , if the thermostat fails .
“ IIoT devices are creating data 24 / 7 , so the idea is you discard most of it and look for the exception - the piece of data that shows a machine is overheating , or out of calibration . With data , less is usually more .”
Hancock says businesses who are harnessing IIoT tech should treat their networks in the same way the world treated modems , back when the Internet was in its infancy .
“ Think back to the days of dial-up modems ,” he says , “ where everyone minimised the amount of data transmitted , because if you didn ’ t then the whole thing just hung ”.
ACCORDING TO THE LATEST AVAILABLE DATA , THERE ARE APPROXIMATELY
15 billion
CONNECTED IOT DEVICES
As well as focusing in on data exceptions , Hancock says IIoT operations benefit hugely from edge computing , which is a distributed computing model that brings computation closer to the sources of data – a warehouse full of inventory , say , or components in a vitally important production plant .
“ If you have local processing power it can be invaluable ,” Hancock says . “ For instance , if a machine is going out of tolerance at a paper mill and there was a delay in sending this data to the cloud and back , then you could have lost a hundred metres of product by the time the machine is switched off . “ So the idea is that local machine-learning tech understands that the machine is out of tolerance , and recalibrates it without any human action needed .”
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