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Industrial IoT Industry Predictions for 2019

By Ken Briodagh December 27, 2018

As 2018 wraps, everyone in the Industrial IoT is getting focused on the possibilities for the industry coming in 2019. A few folks have sent in their predictions and expectations for trends that will develop or mature in 2019 and we’d like to share them with you below.

Of course, all of you should register now for the upcoming Industrial IoT Event, which will run January 29 to February 1 and will look at many developing IIoT trends in depth.

Marcia E. Walker, Principal Industry Consultant for Manufacturing, SAS
Manufacturing and AI. Many people conjure up images of soulless robots repetitively and anonymously managing a machine when they think of artificial intelligence (AI), but that's an outdated view. AI is not just mechanical in nature; it can also affect the manufacturing industry in more artistic areas like computer vision and natural language processing. For example, a paint manufacturer might use computer vision to help achieve nuances in color that were once a challenge. In natural language processing, a manufacturer can turn to unstructured written data sources like equipment maintenance logs, shipping manifests, and customer call center records to reveal new insights. AI helps manufacturers solve old problems, innovate new products and create new business models.

Chris Penrose, president of IoT solution, AT&T
Manufacturing, healthcare and public safety are expected to be the early benefactors of 5G.

Smart factories will revolutionize the manufacturing process as they connect the entire supply chain. The doctor-patient relationship and the traditional way that we think of healthcare will transform. And first responders will have new technology and lifesaving capabilities to protect citizens like never before.

IoT solutions will be key to helping companies achieve their sustainability objectives by conserving water, reducing energy & fuel use and driving lower carbon emissions.

More and more companies and cities will adopt IoT solutions with a goal of improving the environment and the society for the greater good. Industrial IoT applications such as asset and fleet management solutions will unlock massive efficiencies and help reduce emissions across multiple industries such as manufacturing, transportation and logistics and energy.

Global adoption of low power wide area networks will spur innovation and mass deployment of IoT devices.

Smaller devices, increased battery life, integrated SIMs, spectrum efficiency and lower device costs with carrier-grade security will enable new IoT devices and services as Narrow-Band IoT and LTE-M networks become the fastest growing choice for IoT connectivity in 2019. Look for innovative pricing and service models to emerge as the network technology matures.

Nitesh Bansal, SVP and global head of engineering at Infosys
Technologies like Blockchain will not be an immediate requirement within industrial IoT in 2019 as the systems are still mostly closed loop systems and are trust established. However, Cybersecurity will become mainstream requirement in 2019 for device security, data integrity, device integrity, access control and authorization, over and above data privacy.

Pete Schermerhorn, President and CEO, Triax Technologies
IoT will embed itself across the project lifecycle. 2018 was the year that practical IoT-based applications took hold at the jobsite, and in the new year, contractors will continue to make automatic data collection from resources on site (workers, equipment, tools, etc.) a priority. As existing IoT solutions add new types of sensors to enrich the types and quantity of data collected, organizations will expand their use of data for real-time monitoring and control. IoT will also become more embedded in existing construction processes throughout the jobsite, in areas such as site control and security, to achieve efficiency gains. The widespread adoption of IoT and the groundswell of data will drive greater adoption of visual data analytics tools and dashboards.

Data will become king. The past year represented only the tip of the iceberg when it comes to achieving data-driven insights, and while progress was made, there is still a long way to go. According to research, 90 percent of the world’s data was created in the past year, but only one percent is being used effectively. In 2019, construction firms will further invest in their internal data collection, analytics and decision-making processes (e.g. hiring data specialists, integrating new data sets into their own internal platforms) to act upon data insights in a timely and effective manner. This will advance industry digitization efforts, firmly moving technology from the hypothetical to the practical in the new year.

Point-solution fatigue will spark further integration. In 2019, more contractors and technology providers will work together to build truly integrated systems. Customers do not want to use multiple platforms for similar functionality, and as they become more tech savvy, and more solutions become available, they will increasingly integrate third-party data sets with internal platforms and processes. On the provider side, Application Programming Interfaces (APIs) will become more sophisticated, as enterprise software players develop the functionality to incorporate new data sets and tech start-ups collect more data. This time next year, we expect there will be enhanced cooperation – and meaningful integration – among key technology players in the space.

Tech will augment, not replace, workers. Despite advances in automation, buildings will continue to be built by humans for the foreseeable future. In 2019, the story will not be technology replacing the workforce but technology empowering the workforce to do their jobs better. Contractors will continue to search for solutions that are employee-friendly and unobtrusive, prioritizing features such as battery life, small form factor and worker privacy. With the skilled labor shortage showing no signs of slowing down, companies will turn to technology to do more with fewer resources and will continue to hire and train employees to incorporate technology into their work.

Insurers will further embrace IoT. Construction technology has moved from a competitive advantage to an operational necessity, and in 2019, a growing number of insurance organizations are expected to make IoT technology and data analytics a key part of their risk management and mitigation practices. As early technologies, such as wearable devices, improve injury response and hazard communication, more insurance organizations will embrace innovation to deliver value to their clients and prevent unnecessary losses. In 2019, we expect to see more direct investment and partnership between insurance carriers and tech providers.

Sastry Malladi, CTO of FogHorn
Survival of the smallest. IIoT analytics and ML companies will be heavily measured on how much they can deliver in how little compute.

As IIoT projects pivot away from cloud-centric approaches, the next step in the evolution of artificial intelligence and IIoT will address the need to convert algorithms to work at the edge in a dramatically smaller footprint. According to Gartner, within the next four years, 75% of enterprise-generated data will be processed at the edge (versus the cloud), up from <10% today. The move to the edge will be driven not only by the vast increase in data, but also the need for higher fidelity analysis, lower latency requirements, security issues and huge cost advantages.

While the cloud is a good place to store data and train machine learning models, it cannot deliver high fidelity real-time streaming data analysis. In contrast, edge technology can analyze all raw data and deliver the highest-fidelity analytics, and increase the likelihood of detecting anomalies, enabling immediate reaction. A test of success will be the amount of “power” or compute capability that can be achieved in the smallest footprint possible.

The market understands "real" versus "fake" edge solutions.

As with all hot new technologies, the market has run away with the term “edge computing” without clear boundaries around what it constitutes in IIoT deployments. “Fake” edge solutions claim they can process data at the edge, but really rely on sending data back to the cloud for batch or micro batch processing. When reading about edge computing, the fakes are recognized as those without a complex event processor (CEP), which means latency is higher and the data remains “dirty,” making analytics much less accurate and machine learning (ML) models are significantly compromised.

“Real” edge intelligence starts with a hyper-efficient CEP that cleanses, normalizes, filters, contextualizes and aligns “dirty” or raw streaming industrial data as it’s produced. In addition, a “real” edge solution includes integrated ML and AI capabilities, all embedded into the smallest (and largest) compute footprints. The CEP function should enable real-time, actionable analytics onsite at the industrial edge, with a user experience optimized for fast remediation by operational technology (OT) personnel. It also prepares the data for optimal ML/AI performance, generating the highest quality predictive insights to drive asset performance and process improvements.

Real edge intelligence can yield enormous cost savings, as well as improved efficiencies and data insights for industrial organizations looking to embark on a true path toward digital transformation.

ML/AI models get skinny with edgification.

Moving machine learning (ML) to the edge is not simply a matter of changing where the processing happens. The majority of ML models in use today were designed with the assumption of cloud computing capacity, run time and compute. Since these assumptions do not hold true at the edge, ML models must be adapted for the new environment. In other words, they need to be “edge-ified”. In 2019, “real edge” solutions will enable relocating the data pre- and post-processing from the ML models to a complex event processor, shrinking them by up to 80% and enabling the models to be pushed much closer to the data source. This process is called edgification, which will drive adoption of more powerful edge computing and IIoT applications overall.

Closed-loop edge to cloud machine learning will become a true operational solution

As machine learning (ML) and AI algorithms become “edgified” for use close to sensors or within IoT gateways or other industrial compute options, new best practices will emerge on how to train and further iterate on these models. What industrial organizations will find is that edge devices generating analytics on live streaming data (including audio and video) should regularly send insights back to the cloud, but only those that represent anomalous activity warranting a shift in the core algorithms. These edge insights enhance the model, significantly improving its predictive capabilities. The tuned models are then pushed back to the end in a constant closed loop, reacting quickly to changing conditions and specifications, and generating much higher quality predictive insights to improve asset performance and process improvements.

Production IIoT applications will go into implementation only with edge computing solutions supporting multi- and hybrid-cloud deployments.

Hybrid- and multi-cloud solutions will dominate the industrial IIoT deployments – a recent report found that the hybrid-cloud market will reach $97.64B USD by 2023. As industrial organizations look to bring multi-cloud environments together to provide a more cost-effective approaches and flexibility, it will be important for edge solutions to be cloud agnostic. Vendor-exclusive solutions will likely begin to fall by the wayside as companies look for more flexibility and freedom of choice when building their edge-to-cloud environments. Google, AWS, Microsoft, C3IoT, Uptake and other leading cloud providers will establish more collaborative partnerships with edge computing companies to help businesses as they continue to improve and expand their offerings.

IoT video and audio sensors take off, driving the need for deep learning at the edge.

There is industry-wide excitement about the capabilities that audio and video sensors can bring to the IIoT. Edge computing technology can play an important role in the further deployment of audio and video data in commercial and industrial IoT systems. The fusing of asset data with audio and video analytics will allow for faster and more accurate device and machine maintenance (including updates on systems health and more), and a whole host of new innovative applications. One such example of the video analytics is the use of flare monitoring at oil and gas operations to track environmental compliance and flare state remotely for large volumes of flare stack towers.

Predictive maintenance gives way to prescriptive maintenance.

One of the big promises IIoT edge solutions deliver is predictive maintenance, offering insight into what is likely to happen to a connected asset (like manufacturing equipment or an oil rig) in the future. While many organizations still lag in implementing predictive maintenance as a first step, even more advanced technology will be available to early adopters in 2019.

Prescriptive maintenance is a step forward to enable businesses to not only predict problems, but also produce outcome-focused recommendations for operations and maintenance using data analytics.

For example, elevator manufacturers want to put an end to routine problems, such as friction in elevator doors. As part of this effort, they partner with Foghorn to create a predictive maintenance solution. By analyzing sensor data at the source, they can now determine maintenance needs well in advance, without the cost, latency, security and other issues associated with transfer of large amounts of data outside of the building. Thus, it can schedule service before anomalies impact performance in a highly efficient manner. As prescriptive maintenance becomes available, before the manufacturers roll a truck to provide maintenance on an elevator, they will have data available to suggest areas most likely to need repairs and have verified the repair staff person the expertise, tools and parts available for the repair.


The IoT Evolution Expo, and collocated events, IoT Evolution Health, LPWAN Expo, The Smart City Event, and IIoT Conference, will take place Jan. 29 to Feb 1 in Ft. Lauderdale, Florida. Visit IoTEvolutionExpo.com to register now.

Editorial Director

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