Unlocking the Power of Industrial IoT: How IIoT Transform Industry

Well-designed sensor is not just a data collection device – it is the first decision-making node that filters, evaluates, and transmits data intelligently, in alignment with the overall automation and IT architecture. Modern solutions, such as BOS 21M from Balluff or SMC ISE70/ISE80, are increasingly utilizing sensors with built-in logic that can not only measure but also process data before sending it further. In practice, this means the ability to locally filter measurement noise, determine threshold values, or detect characteristic signal changes such as an increase in vibration amplitude or a drop in pressure beyond a defined tolerance margin. This approach shortens the system’s response time and reduces the volume of transmitted data.

From the perspective of IIoT architecture, the key factor is how the sensor communicates with the rest of the system. Traditional analog signals (e.g., 4–20 mA) are still widely used, but they are increasingly being replaced by digital interfaces that enable not only the transmission of measurement values but also diagnostic data, power status, and error history. As a result, sensors are becoming a source of metadata – crucial in the context of predictive maintenance. Industrial studies show that implementing predictive maintenance (PdM) using smart sensors can reduce unplanned downtime by as much as 30–50% and lower maintenance costs by 10–40%. Moreover, digital sensors allow for remote configuration of operating parameters, which shortens commissioning times.

Another important aspect is the selection of the sensor according to environmental and application conditions. In precision-demanding applications (e.g., quality control on production lines), not only measurement resolution matters, but also temperature stability, response time, and resistance to electromagnetic interference. In industrial environments, mechanical robustness is becoming increasingly important – not only in terms of enclosure protection rating but also, for instance, resistance to vibrations when mounted on dynamic machinery. Additionally, in cases where integration with higher-level systems occurs, the need for standardization arises – both at the physical level (e.g., connector type) and communication level (e.g., unified method of reporting status data).

Industrial IoT actuators on the path to higher productivity

In the context of Industrial IoT, actuators are more than the “executive arm” of automation – they are components that increasingly need to operate in close synchronization with real-time data. Whether we’re talking about a pneumatic actuator opening a valve or an electric linear drive positioning a machine component, their effectiveness now depends not only on mechanical performance but also on the level of integration with the control system.

Modern actuators like Festo CPX-E or SMC LEY series are often equipped with:

Encoders or position sensors that enable precise determination of the actuator’s position,
Force or torque measurement systems that adapt the actuator’s operation to working conditions,
Diagnostic systems that monitor overloads, movement resistance, or mechanical wear,
Communication interfaces that allow for real-time status reporting and remote configuration of operating parameters.

This enables precise dynamic control of force, speed, or position – which is crucial, for example, in precision assembly in the electronics or automotive industries. In IIoT systems, the actuator is no longer a blind executor of commands – it becomes part of the data loop that connects the physical layer with analytics and control decisions. Thanks to growing diagnostic capabilities, it’s possible not only to respond more quickly to failures but also to plan maintenance based on actual working conditions rather than just cycles or time.

Harnessing real-time data in the internet of things: the evolving role of controllers

In industrial environments oriented toward IIoT, the classic approach of treating controllers as centralized units executing predefined logic is gradually giving way to a distributed architecture, where controllers also serve as edge data processing nodes. Modern controllers – whether advanced PLCs, compact modular controllers, or machine-embedded control units – are now expected to do much more than just process input/output signals. Increasingly, they integrate local data buffers, alarm histories, the ability to directly connect with IT systems (via REST APIs, databases, or publish/subscribe protocols), and even basic predictive analytics capabilities at the firmware level.

Functionally, this means the controller can:

Aggregate data locally from sensors and actuators,
Analyze trends – e.g., pressure buildup time or temperature fluctuations over a given period,
React to patterns of dynamic value thresholds, rather than simple “ON/OFF” triggers,
Publish data in real time to higher-level systems, such as the cloud or a local edge server.

Another important aspect is the controller’s ability to operate in environments with unstable connectivity. In a well-designed IIoT architecture like Siemens S7-1500 or Beckhoff CX series, production logic should not be dependent on the availability of external systems. Therefore, the controller must function autonomously in the event of a loss of connection to upper-level systems, and buffer data locally for synchronization once connectivity is restored.

This is precisely what distinguishes an “IIoT-compatible” controller from a traditional PLC – not just control capability, but also system resilience in terms of communication and analytics.

Connectivity solutions for Industry 4.0: how IIoT gateways enable seamless integration

In real-world industrial plants, we rarely encounter a perfectly standardized environment. Typically, modern devices operate alongside machines from the 1990s, each with a different controller, protocol, and communication topology. This is exactly where IIoT gateways (e.g. HMS Anybus, Softing edgeConnector) prove their value – as tools that help bring order to this chaos without the need for costly infrastructure overhauls. Their core function is to connect devices and systems that “don’t speak the same language” – enabling data conversion between standards, variable structure mapping, and even synchronization of data from different sources with different refresh cycles.

In practice, this means a gateway can:

Connect legacy machines that can’t be upgraded with modern data platforms,
Organize addressing structures and unify variable naming conventions across the shop floor,
Reduce network load by filtering out unnecessary data at the source,
Ensure logical separation of communication zones – e.g., between automation and IT networks.

According to a report by ARC Advisory Group, over 65% of manufacturing companies use protocol gateways as a transitional solution between OT and IT systems. It’s thanks to gateways that modernization can be carried out step-by-step, gradually transforming a plant into a smart factory without downtime or costly revolutions.

Industrial IoT devices meet edge computing

Edge devices serve as a buffer between the deterministic world of PLCs and the high-latency, often communication-unstable IT and cloud layers. This is where data from distributed sources is integrated, read cycles are synchronized, preliminary data cleansing is performed, and logical transformations take place before further distribution. Crucially, edge computing not only reduces network traffic but also relieves PLCs of tasks that are not critical to safety or control—such as trend analysis, anomaly detection, or executing predictive models.

At the edge layer, you typically run:

Containers with custom analytics or predictive code (e.g., Python, Node-RED, Docker),
Applications for standardizing data coming from different protocols (e.g., simultaneously polling Modbus RTU, OPC, and REST APIs),
Local time-series databases (TSDBs) for data retention before syncing with higher-level systems,
Routing controllers that dynamically decide which data goes to the cloud and which stays within the closed OT system.

Unlike traditional PLCs, edge devices are not designed to operate in 5–10 ms control cycles. Instead, they follow event-driven architectures and serial processing queues. This makes them more adept at handling parallel requests from multiple sources and dynamically reconfiguring data streams. A key feature is resilience to connectivity loss—local data buffering and context-aware logic allow continued operation in an isolated (offline-first) mode, with synchronization to the central system or cloud taking place only once the connection is restored.

Edge is not a transitional layer – it’s an autonomous decision-making tier. Its value grows proportionally with the number of data sources, the complexity of the infrastructure, and the need to react faster than traditional cloud or SCADA-based architectures allow. According to research by IDC, over 70% of industrial data will be processed at the edge by 2025. As a result, response times to events can be reduced from several seconds to under 200 milliseconds, which is critical in precision processes.

HMI – critical components of today’s IIoT products

HMI is an active component of the control system structure and an interactive layer deeply embedded within the engineering logic. Designing it today requires not only an understanding of process flows but also awareness of data life cycles, permission models, communication redundancy, and operational resilience. A well-designed HMI environment (like e.g. Siemens Comfort Panel, Beijer X2 Pro) goes beyond simply representing variable states—it must serve control, reporting, and diagnostic functions while supporting functional safety, process continuity, and operator ergonomics.

Technically, modern HMIs:

Pull data from multiple sources simultaneously (often from devices using different cycles and protocols),
Implement conditional logic independently from the controller (e.g., screen sequences, interlock logic, visibility based on system variables),
Support internal event-driven queue architectures (event-driven UI),
Are integrated with identity management systems (e.g., synchronizing user roles with Active Directory or a local authorization server),
Operate in redundant environments – as replicated visualizations running in hot standby or active-active mode.

How to start implementing industrial internet of things in your company – step by step

Identify business and operational objectives
Determine where IIoT technology can deliver measurable value—e.g., reducing downtime, optimizing energy consumption, improving quality, or enabling real-time production monitoring.
Conduct an infrastructure audit
Assess the current state of your OT and IT systems. Examine existing machines, sensors, control systems, and networks to evaluate compatibility with planned IIoT solutions.
Choose the appropriate IIoT system architecture
Design a structure that includes edge devices, sensors, data transmission systems, and integration with existing software (such as SCADA, MES, or ERP platforms).
Start with a pilot project (proof of concept)
Deploy IIoT in a limited area (e.g., a single production line) to test the technology, validate assumptions, and gather the first measurable results.
Scale the solution gradually
Based on pilot outcomes, expand the system to other processes, departments, or locations according to a well-defined implementation strategy.
Ensure data and system security
Address cybersecurity from the outset: implement data encryption, access controls, network segmentation, threat monitoring, and regular firmware/software updates.
Integrate IIoT with existing IT systems
Ensure seamless data flow between the operational layer and analytics/management systems to fully leverage the value of collected information.
Prepare your team to work with the new technology
Train technical and IT staff in the use, diagnostics, and development of the IIoT environment. Make sure your organization has the competencies to maintain and evolve the system.
Monitor results and continuously optimize the system
Regularly analyze data collected from IIoT devices, verify business goals, identify new improvement opportunities, and iterate the system for ongoing value creation.

If you are interested in the topic of embedded systems in Industry 4.0, we encourage you to read the following article:
https://intechhouse.com/?post_type=blog&p=18048&preview=true

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If you’re looking for a partner that combines engineering expertise with cutting-edge technologies, InTechHouse is the right choice. We specialize in developing intelligent IoT and IIoT solutions tailored to the real needs of the industry. With the experience of our team and an individual approach to each project, we help companies increase efficiency, reduce costs, and build a strong technological advantage. With InTechHouse, you implement innovations that truly work – with no compromises and no unnecessary risks. Schedule a free consultation today and discover what we can offer you.

FAQ

How do IIoT devices differ from consumer IoT?
IIoT devices are designed specifically for industrial environments – they offer greater resistance to external conditions, comply with industrial standards, and operate in real-time. Consumer IoT (e.g., smart home) is used mainly in domestic environments and has less stringent requirements.

How is IIoT device integration with existing infrastructure handled?
In most cases, IIoT devices can be integrated with existing systems (such as SCADA, MES, or ERP) using standard communication protocols like OPC UA, MQTT, Modbus, or PROFINET.

Do IIoT devices require constant internet access?
Not necessarily. Many IIoT devices operate within local networks, and cloud connectivity is optional, depending on the use case. What’s essential is that they have access to the industrial network that enables data exchange.

Which industries most commonly use IIoT devices?
Industries such as manufacturing, logistics, energy, building automation, precision agriculture, and the chemical industry make extensive use of IIoT solutions.

How much does it cost to implement IIoT devices?
The costs vary – they depend on the number of devices, the level of integration, the type of network, and analytical requirements. However, it’s worth noting that IIoT investments often pay for themselves quickly through cost savings and improved efficiency.