“The fundamental problem in executing Industrial IoT initiatives is that enterprises must now build out entire infrastructures of data scientists, SMEs and developers with skill sets to design IoT applications for solving problems all while being able to manage these robust systems. This infrastructure does not come at an economical rate—data scientists are the most sought-out profession of our generation.”
Welcome to Industry 4.0
The advent of Industry 4.0 has also drawn awareness to the popularity of open-source IoT platforms. Platforms entering the space today are adopting similar approaches to the likes of Amazon AWS and Microsoft Azure, where computing will take place both in the cloud and at the edge. Most of these platforms provide a set of micro-services and libraries of models tailored to meet the needs of your industry applications. I refer to this commonality between platforms as the “plumbing” offered by the major players in this ever-crowded space.
The fundamental problem in executing Industrial IoT initiatives is that enterprises must now build out entire infrastructures of data scientists, SMEs and developers with skillsets to design IoT applications for solving problems all while being able to manage these robust systems. This infrastructure does not come at an economical rate—data scientists are the most sought-out profession of our generation.
For the past 35 years, I have been addressing OT & IT pain points in utilities, manufacturing and transportation markets with automation, MES and SCADA solutions. (SCADA has now been coined as “IoT or IIoT” with more features, expanded data storage capabilities and increased computing power.)
As technology continues to evolve, I imagine a world where the end user managing an OSI PI system can do so from a single command line! Yes, this is a big concept to digest. It’s also a tricky system to manage if that same user is developing thousands (if not millions) of problem-solving models.
Back to the open-source can of worms I opened earlier. It remains a mystery to me how these open-source platforms generate revenue. Sure, the open-source community serves as an integral part of our everyday lives, but this still entails poorly designed, porous code that results in end users being burnt.
The total cost of ownership for open-source platforms will always remain higher for users compared to packaged solutions. I am not trying to downplay open source. As a forward-thinking controls engineer who has interfaced with customers for years, I understand what makes them tick. The last thing they want is to throw time, money and resources at solutions that require endless support. Utilities such as water/waste-water fall victim to this common scenario.
Ideally, open-source technology is best suited for OEMs.
Big data is real and there is no denying that IoT applications will continue to surge exponentially. He who is able to manage these models, systems and applications will capture the biggest piece of the IIoT pie. But to date, very few enterprise IoT platforms can offer under one umbrella:
- IoT management from the edge device
- Data collection that supports all industrial-communication protocols
- Connectors to industry-leading historians such as OSI PI
- Simple, configuration-free predictive- analytics portals with accurate results
- Training platforms for building ML models to deploy those agents to the field
- All while retaining deep domain knowledge in understanding process control and machine data, regardless of the vertical
I look forward to a future where the middlemen (system integrators) of the world can properly bridge the gap between OT and IT silos and deliver complete IoT solutions that prove to be unparalleled economic and operational successes for their customers.
Aldo Ferrante is president & CEO of ITG Technologies.