Farming and shipping industries powering IIoT revolution
At the annual Mobile World Congress (MWC) in Barcelona, Spain, it can be often hard for business-led technologies to stand out from the crowd. That was especially true at the 2016 show where everything from virtual reality (VR) headsets and driverless cars to new Android smartphones and robotics leveraging artificial intelligence was on display.
Enterprise technology is, in that context, a much harder sell.
Nonetheless, the Industrial Internet of Things (IIoT) was a very topical theme at this year’s show, with announcements showing how telecoms operators and other technology firms see the potential of connecting cars, cities, buildings, and businesses together for better business insights and customer relations.
One interesting discussion was a session that focused on recent cases involving the IIoT as well as difficulties around standards, protocols, and legacy systems.
In the session, which was moderated by ABI Research’s Dan Shey, ABB group VP of service and R&D Christopher Ganz, and John Deere’s director of on-board applications Ronald Zink talked through their respective IIoT roll-outs, while executives from Microsoft and analyst firm Etisalat Group also chipped in with market insight.
ABB, John Deere and the IIoT
ABB has been using IIoT solutions to inform ship managers at German-based cruise operator AIDA when to replace parts on the ship in order to keep it running. The firm collects data from each ship’s internal control system and electrical systems, pushing this data to the cloud for data analysis.
Power consumption can also be monitored to see how the diesel engines run in order to optimize energy consumption and environmental footprint, while also saving the cruise-liner money.
Meanwhile, John Deere has been using the Internet of Things (IoT) to become more efficient, with Zink detailing the main challenge facing the farmers of today.
"The world has a challenge and that challenge is tackling about how we add 2.5 billion people over the next few years, while having land that won’t appreciably grow. We think technology is a lot of the solution, and maybe the majority of the solution."
Using the IIoT and analytics tools has allowed John Deere to automate its production steps much like a factory. This makes it easier to prepare land and protect it by giving it the right nutrients and harvesting it at the right time. Key components in this real-time monitoring of their crops are cloud computing, data analytics, hardware sensors, and Apple’s iPad, which combine to give a precise live location of equipment in the field, even down to the farm knowing where seed is planted within just 2.5cm. This, says Zink, results in "Better yield, saves costs, and lets plants grow to their optimum potential."
The sensors are installed on John Deere’s machinery, some of which can be so big they have up to 500 sensors on them. And such is their sophistication that Zink says that John Deere is developing guidance systems for these vehicles so that they can essentially drive themselves using coordinates from GPS.
The firm started connecting machines, including its large tractors, in 2011 and now claims to have 100,000 connected machines in 50 countries. Telematics data reports back on the machine’s activity and progress on certain jobs.
With its SeedStar Mobile iPad app, the firm has been able to see precisely what areas have been covered in the field. This mobility means the results can be monitored anywhere in the world in real-time, with data being pooled by a cloud operations center and open for which third-parties may develop applications.
The future of the IIoT
Mats Myrberg, senior director of business development for the IIoT and research at Microsoft, added: "If you think about IIoT for consumer perspective, it’s about making lives easier and computing more personal, whereas in industrial perspective, a lot of it is about business model. The technology is also interesting, but it is a huge opportunity from a business standpoint for companies in the industrial space."
Myrberg added that this was being driven by data, while pointing to Microsoft’s own efforts with Azure and solutions for data and analytics. He went on to detail how Microsoft worked with German elevator firm ThysseenKrupp to improve their efficiency by using IoT algorithms to predict when parts break down. "I think machine learning is super important in this area," he said.
Myrberg admitted however that there are concerns over legacy systems, adding that some firms also have issues about data being managed in the cloud. Driving insight from such data is another challenge entirely.
"Once you have this data in cloud, what do you do with it, how do you drive insight?" he asked. "That’s a super exciting area where I think machine learning is going to drive new learning."
Doug Drinkwater is editor at Internet of Business, which is hosting the Internet of Manufacturing Conference November 1-2, 2016, in Chicago. This article originally appeared here. Internet of Business is a CFE Media content partner. Edited by Chris Vavra, production editor, CFE Media, firstname.lastname@example.org.
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