In the enterprise half of the IoT world, heavy industries like energy, manufacturing, and automotive are the biggest success stories for the new technology, but the prospect of integrating their existing computerized-orchestration and management technology with modern industrial IOT gear can be daunting.\nThe vast majority of IIoT deployments are attempts to layer modern sensors, edge gateways, and communications modules over the top of existing frameworks like SCADA, which means updating legacy sensors and other hardware where possible.\n\nThe good news is that it\u2019s not as big a deal as might be expected from a technical standpoint. There are solutions out there for retrofitting older gear while it\u2019s still operating. New sensor kits or communications modules can sometimes be added to industrial machinery via old RS-232 serial ports, but often that\u2019s not enough. Ethernet connectivity at a minimum is usually what\u2019s required to start metering and then gathering data in meaningful volumes. Hence the need for broader upgrade programs.\nGas pipeline IIoT transition relies on edge networking\nBill Johnson is a vice president and chief transformation officer with DCP Midstream, an energy company mostly devoted to operating natural gas pipelines. It\u2019s got 57,000 miles of pipeline and 61 plants spread across the southern U.S. He said that DCP, like many other companies, is facing the challenge of installing new IIoT equipment without having to take pumps valves and other machinery off-line while they do it. That is such a major concern that the ability to do so has become a selling point for him.\nWhether the IIoT add-ons are flow sensors, pressure monitors or digital thermometers, Johnson said that anything that can simply be strapped, bolted or glued onto the outside of the machinery it\u2019s supposed to be monitoring is more attractive than something that has to be mounted within the equipment itself.\n\n\n\n\n\nFor DCP, the value of IIoT is in getting data from its systems in the field into a centralized repository for analysis. Instrumenting those systems and getting them all to communicate with the analysis layer is enough of a challenge, but DCP also has to cope with the issue of many of its facilities being located in remote areas.\n\u201cMost of the world believes there\u2019s pervasive 4G\/LTE available everywhere, and that\u2019s absolutely not true where we operate,\u201d noted Johnson. \u201cIt\u2019s very hard to convince AT&T or Verizon to give you signal at some of these locations, because they don\u2019t have consumer users [out there.]\u201d\nSo other methods have to be used. One is the use of old-school, point-to-point radio links between sites, as well as satellite communications, but these are expensive and can be unreliable. That prompted a move toward edge computing \u2013 installing local devices to receive and process information from sensors, instead of relying on long-range data links back to a data center, or, in DCP\u2019s case, Microsoft\u2019s Azure cloud, for real-time analytics.\nHonda's IIoT adoption calls for blending disparate technologies\nThose analytics, in fact, are where the real value of IIoT lies for DCP and other companies trying to upgrade their technology. Older industrial automation tech tended not to be designed to share information with a wide range of other machines, particularly those made by different companies.\nIt\u2019s a cross-industry problem, said Pierce Owen a principal analyst at ABI Research. He gave the example of Honda\u2019s light truck plant in Alabama, which, until modernization, was operating a mix of OMRON, Rockwell, and Mitsubishi industrial-monitoring and orchestration equipment, none of which talked to each other, and all of which used proprietary protocols. Settings couldn\u2019t be changed live, and workers had to go to each individual machine and shut it down to make changes. To manage this, Honda developed a complex, in-house system to synthesize data from these various sources, which required extensive coding knowledge to use properly.\n\u201cThe reality is that lots of companies are using software they built in-house, and not only is it difficult to reprogram things, but it requires custom coding to even collect the data in a way that makes sense,\u201d Owen said.\nWhat changed things for the Honda plant, he argued, was the adoption of Telit\u2019s DeviceWise system that can be used by line-of-business personnel who might not have backgrounds in programming, letting the company take data from a disparate range of industrial machines and generally simplify the data exchange.\nUsually, companies updating old industrial control systems to modern IIoT work closely with an industrial automation vendor like Telit or sometimes a smart manufacturing platform provider like PTC or Siemens to manage remote devices and to gather, process and analyze IIoT data. How complex that is depends on where the company\u2019s starting point is because old infrastructure requires a lot more retrofitting than newer hardware.\nIIoT adoption needs clear lines of responsibility\nAn IoT adoption project of any stripe can be organizationally complicated. Does the line-of-business staff, with its familiarity with the actual equipment involved, take the lead or is the task left to the more technically fluent IT department?\n\u00a0\u201cThere just haven\u2019t been enough projects to say, \u2018Oh yeah, in this industry, this group should take the lead.\u2019 There\u2019s definitely still a wide variation,\u201d said Mark Hung, an analyst at Gartner.\nThe example he provided was Microsoft, which undertook a smart buildings initiative a couple years ago at its facilities. Given that Microsoft\u2019s the company in question, it\u2019d be easy to imagine that the IT folks would have been the ones in charge of implementing the new technology, yet the Redmond giant assigned the task to their facilities management people.\u00a0 Conversely, Toyota set up a separate business unit to implement its connected car programs, instead of letting the operational side handle it.\nThere\u2019s no clear right answer, according to Gartner analyst Mark Hung, it\u2019s a matter of what makes the most sense for any given organization \u2013 whether familiarity with the company\u2019s processes and operational equipment outweighs the need for specialized IT-based skill sets.