Uncovering the Internet of Things

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The next few posts in this blog will focus on the Internet of Things. Often abbreviated as IoT, the Internet of Things is a term for the massively interconnected webs of sensors and actuators increasingly embedded in almost every personal, commercial and industrial device, appliance, tool, sub-component,  etc. These sensors can be used in applications as diverse as:

  • Detecting fractures in railcar wheels
  • Monitoring and reporting the temperature in poultry barns
  • Observing patients’ vital signs
  • Recording and transmitting security camera feeds

While remote monitoring – a.k.a. telemetry – is not new, the Internet of Things is distinguished by scale and pervasiveness, and the use of Big Data techniques to analyze the resulting flood of information. IoT promises a more dynamic and adaptive digital ecosystem, as everyday devices become accessible, and therefore “smart.”

The potential upside to an Internet of “Things” is vast, and is likely to provide an inflection point that will change the direction of human culture (similar to the earlier inflection points of the Internet, mobility and social media; IoT is equally disruptive, but on a much bigger scale).

Companies are looking to IoT to improve the customer experience, boost insight into operations and supply chains, enhance security and control of key assets, provide warnings and alerts of infrastructure malfunction or other risk events, and much more. IoT also promises to blur further the lines between traditional “IT” concerns and broader operational issues – what’s been called the convergence of “IT” (information technology) and “OT” (operational technology).

For example, a server or a router in a data center is usually understood to be an “IT” concern. How does that relate, however, to a massive bulldozer, or even just a railroad engine wheel, that is now an Internet end-point? A truck, one of many in a fleet? Who manages the information associated with a vast range of what had previously been “dumb” devices? Responsibility for the physical node (e.g. a railcar wheel) will probably remain with its associated operational group, but it will be more and more dependent on IT services for base networking and very possibly data aggregation and analytics platforms associated with the specific end-point.

Service dispatch and response may be managed through IT-based ticketing systems, as they often have the highest maturity in a given organization. All of this is already happening; for example, a major refinery operator automatically enters a help desk ticket when a sensor on one of its pipelines indicates an unexpected decrease in pressure flow. Not your traditional IT service request, but it works, and works well. Because of this type of expanded monitoring and reporting capability, the traditional boundaries between functional silos are already starting to disappear.

While IoT applications will increase the need for networking infrastructure and services, the voluminous nature of the data will also challenge business processes, which must accept increased uncertainty and error. When an “error” in an IoT feed might indicate a security risk, the best approach will be challenging to define. High quality and well-engineered data quality analytics, such as Blazent provides, will be an essential part of the new operating model.

The data center itself will continue to increase its automation and sensing. Racks, power distribution units and data center environmental controls will all continue to increase their level of sensing and automation. Automatic location of physical assets has long been sought in large data centers, and technology is now making this possible. Reconciling such ongoing data back to the supply chain processes by which assets are acquired will also continue to mature.

Software licensing may also be affected. If an IoT solution involves enterprise software providers, there may be significant ramifications. Previous posts have mentioned that virtualization has resulted in unexpected costs when licensing is poorly understood. Will the likes of SAP or Oracle start to charge for their core, mission-critical software on the basis of how many IoT nodes a company is managing? Given their previous history, it seems prudent to assume that these companies will seek to maximize any such opportunity for revenues. If your enterprise could be targeted for this revenue increase (and chances are it is), best to be prepared, especially knowing that unmanaged IoT nodes are also a security risk.

The convergence of IT and OT will further complicate a topic presented previously in this blog: the relationship between IT asset management and corporate fixed asset management. Systems, data and process will all be affected. A common IoT use case might appear similar to well-known ITSM practices, including:

  • Connecting to a new asset (e.g. an industrial robot)
  • Defining the data flow from it, including establishing baselines for “normal”
  • Predicting faults and failures
  • Dispatching response
  • Enabling incident resolution and problem root cause

Improving fault or incident management is a key goal of IoT initiatives. The lowest maturity is to respond and restore service. Higher maturity prevents specific outages, and the highest maturity predicts scenarios that might lead to outages.

Future posts in this blog series will cover:

  • Instrumentation and IoT in the data center
  • IoT for improved asset and configuration management
  • Software licensing and the Internet of Things
  • The convergence of information technology with operational technology
  • Securing the Internet of Things