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IIoT devices form the foundation of modern industrial architectures, supporting not only process automation but also enabling real-time monitoring, analysis, and optimization. According to data from McKinsey & Company, the adoption of IIoT could generate up to USD 11.1 trillion annually in additional value across industry and services by 2025. In the context of the Fourth Industrial Revolution (Industry 4.0), they serve as a bridge between Operational Technology (OT) and Information Technology (IT) systems, paving the way for the implementation of advanced solutions such as predictive maintenance, digital twins, and edge-level artificial intelligence.
In this article, we will explore what Industrial IoT (IIoT) devices are, the roles they play in industrial environments, the benefits they offer to enterprises, and how industrial IoT development services turn them into working deployments.
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).
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:
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.
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, defined by the Industrial IoT architecture layers and components, 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:
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.
A smart sensor that reports vibration into a closed PLC loop changes nothing. We build the path from device to historian, MES and analytics so the diagnostics reach maintenance and operations.
Connect your sensors to systems that can use the data
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:
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.
A gateway is only useful if the data it forwards lands in a structure the enterprise can query. That is why gateway choice belongs to a wider design decision: the Industry 4.0 data architecture patterns that define how field signals move through edge, platform, and analytics layers before they reach MES or ERP.
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:
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 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:
See also:
Industrial IoT Architecture: Layers and Components
Brownfield IoT: Retrofitting Legacy Industrial Machinery for Predictive Maintenance
Maximizing Efficiency with IoT and Predictive Maintenance
Here's more on the topic of embedded systems in Industry 4.0.
Most plants cannot replace machines to become connected. Ask how we retrofit legacy assets with gateways, digital interfaces and edge processing without stopping production.
See how we roll out IIoT on existing production lines
In a world where data is becoming the new currency, and flexibility and foresight are more important than ever, IIoT devices are opening entirely new horizons for enterprises. They provide access to real-time insights, enable instant fact-based decision-making, and allow organizations to design the future before it even happens.
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.
Not sure where to start? We work with companies at every stage, from early ideas to enterprise-level builds. A 30-minute call can save you months of guesswork.
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.
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.
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.
Industries such as manufacturing, logistics, energy, building automation, precision agriculture, and the chemical industry make extensive use of IIoT solutions.
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.
Adam Szychulec is Deputy CTO at InTechHouse and an electronics and embedded systems engineer with over 13 years of experience in hardware development, FPGA-based systems, embedded software, and technical leadership.
He specializes in electronic system architecture, analog and digital PCB design, FPGA and SoC development, embedded C/C++ software, and managing the complete lifecycle of complex engineering products - from early feasibility studies and technical architecture through development, testing, production introduction, and product modernization.
Adam has extensive experience leading multidisciplinary R&D teams and coordinating electronics, embedded software, mechanical engineering, testing, and project delivery. His responsibilities have included technical decision-making, project planning, risk and change management, budgeting, product testing, new product introduction, and mid-life upgrades of existing electronic systems.
His project experience includes FPGA modules for space applications, electronic systems and payloads for unmanned aerial vehicles, environmental monitoring and multispectral imaging platforms, power electronics, DC-DC converter assessment, and embedded systems developed for demanding industrial and defence-related applications.
Adam works with FPGA and SoC platforms, Xilinx Zynq, VHDL, Vivado, Altium Designer, ARM microcontrollers, embedded C/C++, Linux, digital electronics, and power electronics. He holds bachelor's and master's degrees in Electrical Engineering and is an IPC Certified Interconnect Designer. He writes about FPGA architectures, electronics design, embedded systems, hardware product development, technical risk management, UAV electronics, power electronics, and engineering leadership.
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