Industrial Automation Evolution: From DCS to IoT and SoS

Posted on Feb 28, 2026 in Communications Electronic Engineering

Evolution of Industrial Automation

This section explains the evolution of industrial automation from traditional systems (DCS and SCADA) to modern paradigms like IoT and System-of-Systems (SoS), highlighting major limitations and advancements.

1. DCS and SCADA (Earlier Systems)

  • Used for monitoring and controlling machines inside a plant.
  • Worked in a fixed, hierarchical structure.
  • Systems were vendor-specific and tightly connected.
  • Hard to integrate with other systems.
  • Not flexible for frequent changes or expansion.
  • Mostly local systems, not designed for large-scale connectivity.

2. Limitations of DCS and SCADA

  • Poor interoperability between different vendors.
  • Limited scalability for very large systems.
  • Difficult upgrades and modifications.
  • Rigid architecture.
  • Limited support for modern digital services.

3. Evolution to IoT (Internet of Things)

  • Devices become smart and network-connected.
  • Uses IP-based communication.
  • Devices expose data and functions as services.
  • Enables better data sharing and integration.
  • Supports horizontal communication, not only vertical.

4. System-of-Systems (SoS)

  • Multiple independent systems work together.
  • Each system can work on its own but also collaborate.
  • Based on Service-Oriented Architecture (SOA).
  • Systems are loosely coupled.
  • Services can be dynamically discovered and used.

5. Major Advancements with IoT and SoS

  • Service-level interoperability.
  • High scalability.
  • Flexible and reconfigurable systems.
  • Easier integration of new devices and systems.
  • Supports local automation clouds for real-time performance and security.

Need for New Technology in Automation

This discusses the necessity for new technology in societal and industrial automation, mentioning the challenges posed by traditional automation.

1. Growing Complexity of Systems

Modern industries and societies use very large and complex systems that traditional automation cannot manage efficiently.

2. Need for Flexibility and Customization

Customers demand customized products, but traditional automation systems are rigid and difficult to reconfigure.

3. Scalability Issues

Automation systems are becoming large and distributed, while old systems do not scale well across multiple plants or domains.

4. Integration Problems

Traditional automation uses closed and vendor-specific solutions, making system integration difficult.

5. Limited Interoperability

Devices and systems cannot easily communicate or share data. Lack of standard service-based interaction.

6. Security Challenges

Increasing connectivity increases security risks. Traditional systems were not designed with modern cybersecurity needs.

7. Real-Time and Performance Requirements

Industrial automation needs deterministic and real-time behavior, which is hard to achieve with old architectures.

8. Engineering and Maintenance Difficulties

Automation engineering is time-consuming and costly. Changes require significant manual effort and downtime.

9. Societal Automation Demands

Smart cities, energy systems, and transportation need cross-domain cooperation. Traditional automation systems are too isolated for societal-scale use.

Automation System Architecture Comparison

This section draws and explains a general automation system architecture comparing traditional and IoT-based systems.

Traditional Automation System Architecture

Explanation:

  • Hierarchical Layers: Traditional systems are typically structured in a pyramid:
  • Enterprise Level: Business planning and management systems like ERP and MES.
  • Supervisory Level: SCADA systems facilitate monitoring and supervisory control.
  • Control Level: DCS and PLCs manage real-time control of physical processes.
  • Field Devices: Sensors and actuators provide data and execute commands.
  • Communication: Usually proprietary protocols or fieldbuses.

Characteristics:

  • Rigid, hierarchical design.
  • Limited flexibility for integration.
  • Closed, proprietary communication protocols.
  • Focused on local, deterministic control.

IoT-Based Automation System Architecture

Distributed & Connected: Devices are IP-enabled and connected via standard internet protocols.

  • Edge/Local Cloud: Local processing, control, and security measures are implemented close to the devices. Supports real-time requirements for critical operations.
  • Service-Oriented Architecture (SOA): Systems communicate via standardized web services. Functionalities are exposed as services, enabling interoperability and flexibility.
  • Cloud & Enterprise: Data is aggregated, processed, and analyzed in the cloud. Enables big data analytics, machine learning, and visualization across the entire system.

Characteristics:

  • Highly scalable and flexible.
  • Emphasizes open standards, security, and data analytics.

Current Trends in Automation Systems

This explains current trends such as Cyber-Physical Systems, Digital Twins, Edge Computing, and AI-driven Automation.

1. Cyber-Physical Systems (CPS)

  • CPS combines physical processes and computational systems.
  • Sensors, actuators, and software work closely together.
  • Physical systems are monitored and controlled using real-time data.
  • Enables smart factories and smart infrastructure.
  • Forms the foundation for IoT-based automation.

2. Digital Twins

  • A digital representation of a physical system.
  • Uses real-time data from sensors.
  • Helps in monitoring, simulation, and optimization.
  • Supports predictive maintenance.
  • Reduces downtime and improves efficiency.

3. Edge Computing

  • Data is processed close to the devices, not only in the cloud.
  • Reduces latency and network load.
  • Improves real-time performance.
  • Enhances security and reliability.
  • Fits well with the local automation cloud concept.

4. AI-Driven Automation

  • Uses Artificial Intelligence and Machine Learning.
  • Enables self-optimizing and adaptive systems.
  • Helps in fault detection and decision-making.
  • Improves production flexibility and efficiency.
  • Reduces manual intervention.

Future Automation System Requirements and IoT Impact

This describes future automation system requirements and their impact on IoT-based automation.

1. Future Automation System Requirements:

  • High flexibility and reconfigurability: Automation systems must quickly adapt to changing production needs and allow easy addition or replacement of devices and services.
  • Scalability: Systems should support both small local setups and very large, distributed, multi-plant automation systems.
  • Interoperability: Devices and systems from different vendors must work together using standardized, service-based communication.
  • Real-time performance: Automation systems must meet strict timing requirements, especially for control and safety-critical operations.
  • Security: With increased connectivity, systems must ensure strong authentication, authorization, and data protection.
  • Ease of engineering: Automation design, deployment, and maintenance should be simple, reducing engineering effort, cost, and time.
  • System autonomy: Systems should make local decisions and continue operating independently even if other systems fail.

2. Impact on IoT-Based Automation

  • SOA: IoT uses service-based communication, enabling loose coupling and interoperability.
  • Local Automation Clouds: Support real-time performance with better security and manageability.
  • System-of-Systems (SoS): Independent systems work together, providing scalability and distributed intelligence.
  • Security: IoT integrates authentication and authorization mechanisms.

Next-Generation Automation and Digitization

This explains next-generation automation and digitization technology with respect to IoT and SoS integration.

1. Internet of Things (IoT) in Automation

  • IoT connects sensors, actuators, controllers, and systems using IP networks.
  • Devices expose their data and functions as services.
  • Enables real-time data exchange across systems.
  • Supports horizontal and vertical integration.
  • Improves flexibility, interoperability, and scalability.

Impact of IoT

  • Devices are no longer isolated.
  • Forms the base for modern automation architectures.

2. System-of-Systems (SoS)

  • SoS is a collection of independent systems working together.
  • Each system can operate individually.
  • Systems collaborate to achieve higher-level automation goals.
  • Based on Service-Oriented Architecture (SOA).

Key Characteristics

  • Loose coupling between systems.
  • Supports large-scale and distributed automation.

3. Integration of IoT and SoS

  • IoT provides connectivity and services.
  • SoS provides coordination between multiple systems.
  • Integration enables distributed intelligence.
  • Systems cooperate without losing autonomy.
  • Supports local automation clouds and inter-cloud communication.

4. Advantages of Next-Generation Automation

  • High flexibility and reconfigurability.
  • Better scalability for large systems.
  • Improved security management.
  • Reduced engineering effort.
  • Faster deployment and easier maintenance.

Local Automation Cloud (LAC) Definition and Need

This defines a Local Automation Cloud (LAC) and explains its concept and need in real-time IoT automation systems.

A Local Automation Cloud (LAC) is a limited and manageable local environment where automation systems exchange data and services using service-oriented principles. It hosts mandatory core services and application systems to support secure, real-time automation within a defined local scope.

2. Concept of Local Automation Cloud:

  • A LAC groups devices, systems, and services within a local boundary.
  • Systems communicate using services, not direct device connections.
  • Includes core services such as: Service Registry, Orchestration, Authorization.
  • Supports loose coupling between systems.
  • Multiple LACs can interact through inter-cloud communication.

3. Need for LAC in Real-Time IoT Automation Systems

  • Real-time performance: Local communication reduces latency and ensures deterministic control.
  • Security: Limits external exposure and simplifies authentication and authorization.
  • Scalability: Large systems are split into small, independent local clouds.
  • Reliability & autonomy: Systems keep working even if external connections fail.
  • Ease of engineering: Simplifies design, deployment, and maintenance.

4. Role of LAC in IoT and SoS

  • Acts as a building block for System-of-Systems (SoS).
  • Enables interoperability at the service level.
  • Supports secure inter-cloud service exchange.

Properties of Local Automation Clouds

This explains the properties of Local Automation Clouds with suitable examples.

Local Automation Clouds are designed to make automation systems fast, secure, flexible, and easy to manage.

Self-Containment

LACs can work independently without relying on the internet or external clouds, improving reliability.

Real-Time Support

They respond quickly to events, ensuring deterministic behavior for control and safety operations.

Security and Safety

Only authorized devices and users can access services, reducing the risk of cyberattacks.

Scalability and Interoperability

LACs can easily grow and support devices from different vendors using standard communication.

Ease of Engineering and Deployment

System setup, updates, and maintenance are simple, reducing time, cost, and manual effort.

Multi-Stakeholder and Multi-Cloud Support

Different local clouds can share data and cooperate for large-scale automation.

Low Latency and High Performance

Local communication minimizes delay, ensuring stable and smooth system operation.

Architecture of a Local Automation Cloud

This section draws and explains the architecture of a Local Automation Cloud.

1. Devices and Systems (Bottom Layer)

  • Includes sensors, actuators, controllers, and machines.
  • These devices produce or consume services.
  • They do not communicate directly with each other.
  • Example: Temperature sensor, PLC, motor controller.

2. Core Systems (Middle Layer – Mandatory)

These are essential for a Local Automation Cloud:

  • Service Registry: Stores information about available services. Helps systems discover services.
  • Orchestration: Decides which service talks to which system. Enables dynamic connections.
  • Authorization: Controls who can access which service. Ensures security inside the cloud.

3. Application Systems (Top Layer)

  • Perform automation logic and control.
  • Use services provided by devices.
  • Examples: Control applications, monitoring dashboards.

4. Local Boundary (Key Concept)

  • All components are inside a local, secure boundary.
  • Ensures low latency, real-time performance, and security.
  • External communication is done via inter-cloud links.

Why this Architecture is Important

  • ✔ Supports real-time control
  • ✔ Improves security
  • ✔ Enables loose coupling
  • ✔ Easy to scale and maintain
  • ✔ Ideal for IoT-based automation

Local Cloud Establishment Process

This explains the process of Local Cloud Establishment and the engineering steps involved.

Local Cloud establishment is the process of creating a secure Local Automation Cloud (LAC) where automation systems, devices, and services can interact efficiently within a defined boundary. The detailed engineering steps can be summarized as follows:

  1. Service Registration: Devices and systems register the services they provide in the Service Registry after successful authentication.
  2. Service Discovery: Registered services become discoverable. Application systems query the registry to locate required services.
  3. Authentication and Authorization: Before registering or accessing services, systems must prove their identity and get permission. This ensures security inside the cloud.
  4. Service Orchestration: The Orchestration System decides how services are connected and used in automation processes.
  5. Creation of Control Loops: Services are linked to form closed control loops such as sensor → controller → actuator for real-time automation.
  6. Security Enforcement: Secure communication, encryption, and access control protect services and data from unauthorized use.
  7. Deployment and Operation: The configured local cloud is deployed, monitored, and maintained. Devices can be added or updated without disturbing operations.

Conclusion: These steps ensure a secure, real-time, and scalable IoT-based automation system.

Latency and Security Challenges in LACs

This analyzes latency and security challenges in Local Automation Clouds and provides mitigation techniques.

Latency Challenges

  • Real-time control loops require very low delay.
  • Network congestion and service orchestration can increase latency.
  • Inter-cloud communication adds extra delay.

Mitigation Techniques (Latency)

  • Keep time-critical control loops inside the local cloud.
  • Use local processing and edge computing.
  • Optimize service orchestration and bindings.
  • Limit inter-cloud communication for real-time tasks.

Security Challenges

  • Unauthorized devices may attempt to register or access services.
  • Increased connectivity raises the risk of cyberattacks.
  • Inter-cloud communication can open security vulnerabilities.

Mitigation Techniques (Security)

  • Use strong authentication for devices and systems.
  • Apply authorization rules for service access.
  • Encrypt communication using TLS/DTLS.
  • Use secure bootstrapping and controlled inter-cloud access.

SoS Scalability in IoT Automation

This discusses SoS scalability in IoT automation systems, explaining challenges and architectural solutions.

System-of-Systems (SoS) scalability in IoT automation refers to the ability to expand and integrate multiple independent systems while maintaining performance, security, and autonomy.

Challenges

  • Heterogeneity: Different devices, vendors, and platforms.
  • Interoperability: Incompatible protocols and data formats.
  • Latency: Delays increase as systems scale.
  • Security: Larger attack surface with more connected systems.
  • Engineering complexity: Difficult configuration and maintenance.

Architectural Solutions

  • Service-Oriented Architecture (SOA): Enables loose coupling through services.
  • Local Automation Clouds (LACs): Divide systems into manageable, real-time local clouds.
  • Inter-cloud communication: Secure cooperation between local clouds.
  • Standardized interfaces: Improve interoperability.
  • Distributed security: Local authentication and authorization.

Conclusion: SOA and Local Automation Clouds enable scalable, secure SoS integration in IoT automation.