Niall Sullivan, VP Marketing, Senseye looks at the pivotal role of cloud in allowing IoT to go mainstream.
The Internet of Things, or IoT, refers to the billions of physical devices around the world that are now connected to the internet, all collecting and sharing data. Thanks to the widespread availability of cheap computer chips, and wireless networks, anything, from a cup to a cruise ship, can become part of the IoT.
What is Cloud IoT?
These internet connected objects can then communicate real-time IoT data without involving a human being, merging the physical and digital to create a means of living our lives, whether it’s through smart homes or smart cities, in a smarter and more responsive way.
The use of cloud computing is not new; it is widely used for data-heavy applications, including software (CRM solutions, social media), corporate email and document storage. Its attraction is its data storage capacity, scalability, access on the go, and of course cost. It is a proven tool and has brought high technology to the masses rather than preserving it for the benefit of only the largest organizations.
Technology analyst company IDC predicts that in total there will be 41.6 billion connected IoT devices by 2025, with Worldwide spending on the IoT forecast to pass the $1 trillion mark this year (2022).
Unsurprisingly, asset intensive industries such as manufacturing ($197), transportation ($71 billion) and utilities ($61 billion), are set to dominate this spending.
This is largely because IoT as a concept promises enterprises access to more data about their own assets, products and internal systems, and a greater ability to make changes as a result.
However, it’s really important to note that this promise can’t be delivered by IoT alone. In fact, IoT strategy relies upon three core components to be successful:
- IoT, the source of data, typically via sensors and connected devices
- Big Data, to analyse and contextualise IoT data
- Cloud computing, to facilitate scale, storage and allow speed of access
With many organisations openly admitting that they are data rich, but insight poor, embracing these converged capabilities in the form of Cloud IoT is crucial in unlocking untapped potential and driving the best performance.
For asset-centric companies Cloud IoT represents a capability which goes beyond monitoring and maintenance, to automatically predict when equipment needs attention. In turn, this averts potential problems and minimises downtime, while minimising unnecessary maintenance and optimizing performance.
Cloud IoT solutions which are designed for predictive maintenance really amplify both precision and productivity, when compared with on-premise enterprise asset management (EAM) platforms.
Whereas a typical on-premise EAM solution will extract data and trends from within the organisation’s own asset portfolio to maximise availability and reliability, Cloud IoT applications, such as Senseye PdM, provide scale through leveraging data from across a dedicated network consisting of a multitude of organisations and asset registers globally.
Capturing data on this scale helps to distil learning, establish patterns and optimise accuracy. And by applying machine learning and AI to pinpoint key issues with a certain type of asset, and point to the most appropriate remedial action, the most informed decisions can be made to minimise costs and downtime, reduce risk and maximise asset performance.
Through delivering predictive maintenance in this way, real-world learning can take place and be applied, rather than relying on more limited insights from within just one organisation.
Is Industry 4.0 a security risk?
As a foundation of Industry 4.0’s interconnected universe and in today’s world of headline-grabbing hackers, the cloud has been placed under increased scrutiny for its security. Has it stood up to the scrutiny? In terms of Industry 4.0, arguably, yes it has; as these new networks are created, security is built in from the outset. Is the scrutiny a fair reflection of risk? Perhaps, perhaps not.
Many organizations sensibly choose to separate cloud-connected networks from operations networks and keep sensitive equipment ‘airgapped’ from the cloud – but often the biggest risk is not in the cloud, but in internal networks and leaks in the airgap. Often the biggest security threats such as the Meltdown and Spectre calamities are internal.
Ensuring staff are mindful of security, updating passwords, ensuring antivirus software is up to date, encrypting data, keeping on top of permissions, maintaining a firewall; these are some of the areas which are critical in maintaining a secure network. However, any addition to a network carries additional risk and needs to be properly assessed.
A catalyst for innovation
Accelerated by IoT and Cloud computing, analysts forecast that the predictive maintenance market will continue to grow at a rapid pace, and is set to be worth $28.2 billion by 2026.
My prediction is that IoT will become synonymous, and even interchangeable with Cloud IoT as this growth continues, and the framework will facilitate vital insights from which modern business are run on. These insights from which action can be taken and performance enhanced, will become the lifeblood of operations and planning, and without a means of harnessing them, organizations may find themselves drowning in big data which has no value.
In an economy where the only certainty is uncertainty, few organizations can afford the luxury of ignoring the potential which Cloud IoT promises. Those who embrace it stand to build competitive advantage, and become the market leaders of tomorrow.
Cloud technology is a core enabler of Predictive Maintenance, whether collecting, analyzing, transferring or responding to machine data to keep machinery running; as such, the role of the IT team has never been more critical.
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