Fundamentals 26 min read

What Core Technologies Will Power the Future Industrial Internet?

The article outlines the foundational technologies and strategic components—such as ubiquitous super‑computing terminals, software‑defined machines, knowledge‑work automation, cross‑enterprise standards, system security, robotics, distributed 3D‑printing, brain‑machine interfaces, and virtual worlds—that together shape the emerging Industrial Internet ecosystem.

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What Core Technologies Will Power the Future Industrial Internet?
Industrial Internet was first proposed by GE in 2012, followed by Germany's Industry 4.0 in 2013, reflecting decades of technological accumulation and a new strategic vision that combines industrialization with the Internet.

To achieve sustainable growth in the Industrial Internet, a solid technical foundation is essential. The diagram below (illustrated) structures the emerging and future technology elements, offering a systematic view of the Industrial Internet's technical and system base.

The most basic layer consists of standards and system security. Unlike the mature commercial Internet, Industrial Internet standards are still forming, leading to intense competition among technology camps. Weak system security hampers openness and data exchange, prompting nations, organizations, and research institutes to focus heavily on establishing standards and security consensus.

These foundational, strategic efforts are crucial for Chinese enterprises, which must avoid unrealistic shortcuts and invest in solid groundwork to achieve true industrial connectivity.

Above this base are three critical technology components. The first is the "ubiquitous supercomputing terminal," a combination of sensors, powerful chips, and distributed computing enabled by chip proliferation and IPv6 address expansion.

The second component is "software‑defined machines," where pervasive supercomputing terminals integrate with industrial devices, making software more important than hardware. Software‑defined hardware and machines will become the dominant trend.

The third component is "knowledge‑work automation," encompassing data, models, methodologies, and AI that drive automation in knowledge‑intensive tasks.

Beyond these components, new industrial processes will emerge. Deep robot integration will transform production into a continuous, fatigue‑free workflow, with robots communicating and automating tasks to break human bottlenecks.

In distributed manufacturing, 3D‑printing represents a star technology, turning individuals and organizations into nodes of large‑scale production and redefining traditional mass‑production models.

The uppermost elements envision the fusion of human consciousness with virtual worlds, where machines understand human intent and virtual environments augment physical reality, ultimately merging the industrial and virtual realms.

1. Supercomputing Terminals

Supercomputing terminals include smart devices such as connected cars, wearables, and chip‑embedded apparel. Their core is a powerful chip, with ARM architectures challenging Intel's historic dominance.

These terminals push beyond Moore's Law, benefiting from IPv6's limitless addressing, enabling every smart endpoint to possess strong compute and connectivity capabilities.

Industry giants such as Samsung, Nest, Google, and Apple are forming alliances (e.g., Google’s acquisition of Nest, Apple’s HomeKit) to shape interaction standards, while companies like GE (Predix) and Huawei (LiteOS) are establishing industrial operating system standards.

2. Software‑Defined Machines

Apple’s iPhone demonstrated that software can define hardware functionality, inspiring industrial firms to shift focus from hardware differentiation to software‑driven value, leading to service‑oriented and personalized product models.

This trend is especially evident in automotive and home‑appliance sectors, where software platforms enable remote maintenance, rapid upgrades, and customized services.

3. Knowledge‑Work Automation

First highlighted by McKinsey in 2013, knowledge‑work automation spans information processing, pattern recognition, AI, and machine learning, projected to generate nearly $6 trillion in economic value by 2025 and create over 100 million full‑time‑equivalent jobs.

Artificial intelligence, exemplified by IBM’s cognitive computers and its TrueNorth neuromorphic chip, drives this automation, but progress in industrial AI remains early due to limited algorithm adoption.

4. Cross‑Enterprise Standardization

Global competition over standards is intense; Germany attributes 0.9% of its GDP growth to standards, second only to capital investment. Alliances such as the Industrial Internet Consortium (GE, AT&T, Cisco, IBM, Intel) aim to shape implementation standards, and Chinese firms must actively participate to influence future directions.

5. System Security

Security remains a weak link; incidents like the 2011 Stuxnet‑style attack on Iran’s nuclear SCADA systems highlight the risks. Robust device‑level security, strict network data protection, and comprehensive emergency response plans are essential for widespread Industrial Internet adoption.

6. Robots Transforming Industrial Processes

Robots, first introduced in the 1960s, have become central to production, especially in Japan and increasingly in China, where cost reductions and labor pressures drive adoption despite reliance on foreign high‑end components.

7. Distributed Production and 3D Printing

3D printing enables online design and offline distributed manufacturing, lowering entry barriers and supporting small‑batch, customized production, though material performance remains a key challenge.

8. Human‑Machine Fusion

Brain‑computer interfaces, demonstrated by cross‑continental EEG‑to‑QR‑code experiments, hint at future direct mind‑control of machines and reciprocal machine understanding of human intent, with applications ranging from entertainment to occupational safety.

9. Virtual Worlds

Beyond the physical realm, digital twins and virtual systems will increasingly predict, maintain, and design physical assets, leveraging big data, AI, and simulation to surpass real‑world forecasting accuracy.

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