The Industrial Internet of Things: A Short History of Its Evolution and Impact

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The Internet of Things (IoT) is widely regarded as the next industrial revolution. Over the past decade, it has moved from niche concept to mainstream technology, with leading analyst firms such as Gartner, IDC, and Statista forecasting that continued IoT development will generate global revenue of more than $2‑3 trillion in the next ten years. Industry experts agree that the industrial sector stands to gain the most, and that the Industrial Internet of Things (IIoT) will account for the lion’s share of this growth.

To understand where IIoT is headed, we must trace its roots back to the late 1960s. The path to today’s connected factories was paved by early innovations in automation and machine‑to‑machine (M2M) communication.

Humble Beginnings

On January 1, 1968, engineer Richard (Dick) Morley drafted a memo that would lead to the invention of the programmable logic controller (PLC). His Modicon PLC dramatically improved General Motors’ manufacturing capabilities and set the stage for modern automation.

That same year, Theodore G. Paraskevakos was developing the world’s first M2M device, aiming to create an “apparatus for generating and transmitting digital information.” Both Morley’s PLC and Paraskevakos’s M2M device were foundational steps toward the IIoT.

Laying the Foundation for Connectivity

In the 1980s, two milestones accelerated industrial connectivity. In 1983, Ethernet was standardized, enabling machines from different manufacturers to communicate over a common physical layer. Six years later, Tim Berners‑Lee invented the World Wide Web at CERN, providing a global, automated information‑sharing platform that would later influence industrial data exchange.

Industrial leaders recognized the need for interoperable plant‑floor connectivity. A group of vendors—Fisher‑Rosemount, Intellution, Rockwell Software, and others—convened to address the “Device Driver Problem.” This meeting marked the birth of what is now the OPC Foundation.

Connectivity, Collaboration, and Cooperation

Early human‑machine interface (HMI) and supervisory control and data acquisition (SCADA) systems relied on proprietary protocols or vendor‑specific drivers. As operators integrated solutions from multiple vendors, the necessity for cross‑platform communication grew. Some vendors responded by creating their own APIs, but these fragmented the market. The OPC Foundation’s collaborative approach eventually standardized communication, benefiting end users.

In 1995, the rise of Microsoft Windows on the plant floor intensified the push for interoperability. Windows 95, the first commercially available off‑the‑shelf OS with plug‑and‑play support, enabled easier integration with industrial hardware. By the late 1990s, wireless M2M technologies emerged, and Ethernet became the universal connectivity standard in industrial settings. Industry‑specific interface standards such as DNP, IEC 61850 (power), BACnet (building automation), Profibus, CC‑Link, and HART began to form dedicated consortiums, steering the sector toward the IIoT.

Taking IIoT to the Masses

With a ubiquitous OS and Ethernet backbone in place, more devices connected. In 1999, Kevin Ashton coined the term “Internet of Things” to describe a network where the Internet links to the physical world via sensors. The concept also allowed legacy equipment—often long‑term investments—to become connected.

A pivotal moment arrived in the early 2000s with the widespread adoption of cloud technologies. Amazon Web Services launched in 2002, making cloud computing accessible to enterprises and reshaping industrial architectures. Fourteen years later, the cloud and virtual machines continue to unlock new IIoT opportunities.

Meanwhile, the consumer market’s smartphone boom prompted the industrial sector to develop smaller, smarter PLCs, DCSs, hybrid controllers, and programmable automation controllers (PACs). Improved battery and solar power made distributed sensing practical across expansive infrastructures, such as oil pipelines. This convergence of power and connectivity brought meaningful context to industrial data.

Data Transforms into Information

Contextualized data became actionable information, prompting the OPC Foundation to release OPC UA in 2006. The new protocol decoupled the API from the physical layer and was designed for field devices, control‑layer applications, MES, and ERP systems. Its generic information model supports primitive data types, binary structures, and XML documents, providing seamless data access from the shop floor to enterprise executives.

By 2010, machine and operational data were delivering tangible value, and organizations sought to store and analyze data longitudinally. The data historian market surged, and sensor costs dropped dramatically, enabling many legacy (“brownfield”) architectures to embrace IIoT. Advances in edge computing and personal devices—endorsed by leaders such as Citrix and Intel—further empowered on‑the‑go data access and analysis.

IIoT Today, Tomorrow, and Beyond

In the past six years, the convergence of robust connectivity, advanced analytics, condition‑based monitoring, predictive maintenance, machine learning, and augmented reality has crystallized a clear vision for the IIoT’s future. Technology giants—including GE, IBM, and PTC—have heavily invested in IIoT platforms, and recent acquisitions have refined these solutions.

From Morley’s early PLC to today’s ubiquitous sensors, the journey has been long, but the momentum is undeniable. A recent business‑intelligence report projects nearly $6 trillion will be spent on IoT solutions over the next five years, with enterprises as the primary adopters.

These investments signal major shifts: IT and operations technology divisions are increasingly collaborating—or merging—while traditional IT standards such as MQTT, WAMP, and XMPP gain traction in industrial contexts. As integrated data becomes ubiquitous, data scientists are stepping into executive decision‑making roles.

While predicting the exact trajectory of IIoT remains challenging, the current tipping point suggests that as more devices connect and generate data, the possibilities for analytics and artificial intelligence will expand without bound.