07 April 2015
Tim Taberner, global product manager – Advanced IoT Gateways for B+B SmartWorx says it is time to rethink our approach to the Internet of Things.
The case being made for the adoption of IoT solutions in the industrial space is well understood and widely accepted, so why aren’t end users investing in volume? The obvious answer is that business models haven’t changed!
The value proposition for many IoT use cases is that by interconnecting systems and eliminating ‘islands of automation’ we can optimise not just individual processes, but entire ecosystems, be it a smart city or an entire sourcing, manufacturing and distribution operation spread across multiple sites and regions. However, it is almost impossible to price the anticipated efficiency savings or the revenues from new business streams based on data ownership. This is compounded as often benefits accrue to individuals or organisations which are not paying for the system. Put simply, the investment is too risky.
It is time that IoT suppliers, tackled the problem head on – offering solutions that make commercial sense in their own right when addressing a point in time problem, offering the flexible data connectivity needed to build IoT architectures as an added benefit, not an end in itself. Critical to this is the elephant in the room that is often overlooked in the ROI argument – that of edge flexibility and scalability.
Specifying a legacy M2M system edge was easy – take the process input and output totals, add a few spares for good measure and size the edge accordingly. This doesn’t work for IoT systems where edges need flexibility to grow and adapt as new business requirements and sensing technologies emerge. The problem when specifying such a system is that we don’t know what we don’t know, so how can we specify an edge device that won’t need replacing in two years time?
Often, the focus of the evaluation process is in the enterprise system capability; what can be done with the data, how it can be visualised and analysed. Users often go on to simply accept the corresponding edge device technology without question. Crucially, they overlook that the majority of the cost of implementing an industrial asset monitoring system is not in the equipment, enterprise software and services, but instead in the cost of deployment; of wiring sensors into edge devices; of managing remote device populations; and importantly for lifetime ROI, what happens when the capacity of the deployed edge devices is exceeded.
By leveraging innovative wireless technologies installation can often be reduced to simply mounting a node next to a group of sensors, connecting them and moving on. Contrast this to the cost of installing hundreds of meters of cable – especially if this involves specialist cables, asbestos removal or trenching. We estimate reductions in the initial cost of purchasing and deploying a medium sized asset monitoring system of 30-40% are achievable.
Return-on-investment is enhanced by the emerging SWARM Intelligence edge collaborative device paradigm. This breaks the relationship between an edge and a single physical device, allowing interfaces and processing capability to be distributed throughout an asset and expanded throughout the system lifetime as the need arises. Installation costs are again reduced, and future expansion and adaptation becomes a process of incremental addition, not ‘rip out and replace’, with potential savings across the lifetime of a system
Both systems provide the decoupling of data producers and consumers fundamental to an IoT architecture. Northbound data is enriched prior to transmission allowing it to be easily consumed by upstream applications without needing detailed knowledge of the sensors, devices or legacy systems producing the base measurements. At the same time, SWARM Intelligence opens the door for much more collaborative local intelligence and control.
Machines, sensors and actuators can all be accessed under the control of a single local intelligence, distributed throughout the swarm, paving the way for architectures where autonomous manufacturing processes are the norm, with the enterprise IoT providing supervisory overview and analytics based scheduling.
For the IoT vision to transform into a reality, suppliers need to rethink their approach to the marketplace, offering systems which justify themselves on single point in time use cases, not the promise of ‘jam tomorrow’. The adoption of emerging technologies for the edge solution can dramatically reduce the initial investment needed to implement such systems, and protect this investment over the lifetime of the installation, significantly improving ROI. The correct choice of edge technology in a system is therefore a major contributor to the success of any project, and deserves careful consideration.
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