Morgan Gebhardt, Vice President, IPsoft
While the Internet of Things (IoT) still flies beneath the broad public consciousness, it’s already transforming modern life. Beyond fitness trackers and predictive car maintenance, the devices around us are becoming ever more connected and “intelligent.” If you’re in construction, concrete can sense and alert to weakness. In medicine, doctors can remotely check your heart. Or if you manage an office of freelancers, workstations can recognize and adapt to an employee’s presence.
But what does this mean for the average person or business? Are IoT technologies merely the nice-to-have “apps” of the physical world? Can’t your business leave them to the smart watch crowd?
In short, no. If you are an executive decision-maker, you might be wary of hype around IoT…but by 2020, predictions state we’ll have between 20 to 50B IoT devices in operation worldwide accounting for a market worth nearly US $2 trillion.
And even if your business does not seem ready-made for the Internet of Things, IoT will integrate with your work in some way, just as the Internet became indispensable for even the smallest start-up. So it’s very likely a matter of when, not if, you will need consider a management strategy for IoT devices.
When you do embrace IoT, however, there are new risks that need to be managed given the role of this myriad of devices. Imagine a customer’s front door being remotely unlocked by thieves or, less dramatically, consider the disruption caused by faulty inventory tracking. Just as outdated software versioning and insecure networks can create data vulnerability on our laptops, broken communication or missed update cycles can deactivate IoT devices–or worse, make them vulnerable to misuse. Immature (or worse, absent) IoT management can miss problems we may not have yet even considered.
Even more than traditional IT infrastructure, the IoT universe requires technology that’s up to managing the interdependence between this massive ecosystem of intelligent “devices.” Three key capabilities will provide the foundation for a robust system:
It’s simply impossible to manage billions of hyperactive, hyper-connected devices manually. Intelligent technology able to absorb the required scale, complexity and machine speeds required will be essential. With the inter-relationships between devices constantly changing, autonomic technology that can recognize a problem, learn from experience, and act to resolve it is becoming a base requirement.
In concert with autonomics, an intelligent server in the cloud will receive inputs from various smart devices, analyze the data to see what action to take, then instruct the smart devices to act accordingly. The inherently elastic nature of modern cloud architectures is likewise a necessity to meet the scaling demands of a continuously expanding ecosystem of connected devices.
Big Data Analytics
To make sense of all this complexity, the smart, cloud-based, autonomically orchestrated IoT ecosystem must be driven by deep analytics, powered by cognitive machine intelligence.
Most of all, we will need transparency that unifies a view of how data is flowing through this vastly increased number of devices. Point solutions that manage one set of IoT devices for a single purpose will be unaware of faults in other related networks of devices. CTOs have a challenging task ahead in managing their extended IoT infrastructure and are under pressure now to create blueprints that will stand up to the test.