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Many IoT projects fail due to the selection of a scalable technology and solution, as well as uncertainty regarding the provider. We will show you solutions that have proven to work in comparable projects within our network.
These four modules form the technical foundation for many companies in our network for their IoT projects: data acquisition via smart sensors or directly through the control system, secure transmission (wireless or wired), preprocessing of the data via edge devices and modules, and the use of standardized data formats.
Industrial data acquisition starts at the source, directly at machines, systems, sensors or controllers. Smart sensors, controllers and retrofit solutions measure process and condition data such as temperature, pressure, vibration or energy consumption. This acquisition can also be retrofitted to older machines from the 1980s and 1990s. The goal is the precise and continuous recording of all relevant values, regardless of machine type or year of manufacture. Data acquisition ends at the point where the sensor or controller provides the measured value (for example temperature, pressure or power consumption).
The collected raw data is filtered, aggregated and structured directly at the edge, meaning on devices for local data processing close to the machine or system, in order to optimize relevance, data quality and performance before transmission. Real-time critical data remains local, while non time-critical or historical data is sent to central systems or cloud platforms. This reduces latency and CPU load, saves bandwidth and ensures the data is available where it delivers the greatest value.
Collected or preprocessed machine data is securely transmitted to the next stage via IoT connectivity technologies, either wired via Industrial Ethernet, Time-Sensitive Networking (TSN) or through protocols such as OPC UA, MQTT, OPC UA over MQTT, Profinet or other industrial protocols. Alternatively, depending on the use case, transmission can occur wirelessly via 5G, 4G/LTE, NB-IoT, LTE-M, LoRaWAN, mioty, Bluetooth/BLE, Zigbee, Z-Wave, NFC, RFID, Wi-Fi, cellular roaming, local breakout, eSIM, satellite or other radio technologies.
Collected or preprocessed data is converted into standardized formats and data models to ensure cross-system interoperability, meaning seamless collaboration between different systems and manufacturers. Standards exist at all levels, from IO-Link for sensors during data acquisition, to OPC UA over MQTT or LoRaWAN for data transmission, to Docker for device management, NATS or Apache Kafka for IT/OT integration, as well as for product master data. These are developed by industry organizations, alliances and foundations together with their members.
Real insights into how companies install sensor technology, connect systems, and set up secure data paths.
These four modules form the foundation for the IT infrastructure of IoT applications for many companies across industries in our network, with scalable platforms and secure management of connected devices.
IoT platforms are the central nervous system of your digital infrastructure. They collect, store and visualize data, manage connected assets and provide interfaces to third-party systems. There are three types to choose from: industry-ready IoT and service platforms with preconfigured functions for specific applications, custom-developed platforms based on modular components tailored to your processes, and cloud-based modular platforms from hyperscalers on which you can flexibly develop and operate your own applications.
IT/OT integration seamlessly connects the production and business worlds. Production data from machines, systems or sensors is linked with IT systems such as ERP, MES or cloud applications. This creates end-to-end processes without media discontinuities, enabling users to implement specific use cases efficiently. Integration is carried out via standardized interfaces that provide data reliably, securely and in consistent formats. Companies benefit from greater transparency, faster decision-making and the ability to optimally align production and business processes.
Device management ensures that IoT devices are operated efficiently, securely and in compliance throughout their entire lifecycle, from commissioning to updates and decommissioning. Centralized management enables automated OTA updates and patches, secure onboarding, management of digital certificates and role-based access. Device fleets can be monitored, configured and controlled across locations, including in multi-site and critical infrastructure environments. Container management on edge devices ensures that devices are always integrated into the overall architecture. Companies benefit from reduced operating costs, high availability, faster troubleshooting and a scalable foundation for future IoT services.
Protecting industrial data and systems requires holistic security architectures that combine OT and IT requirements. Modern concepts such as defense-in-depth, PKI-based device management and encrypted data flows secure the entire lifecycle from development (security by design) to operation. Intrusion detection, anomaly detection and deep packet inspection detect attacks early, prevent manipulation and protect against downtime. This also enables companies to meet regulatory requirements such as NIS2 or the Cyber Resilience Act, reduce liability risks and ensure the availability of critical processes.
These components form the digital infrastructure for your IoT application and securely connect devices with your IT.
The collected and processed data is displayed in interactive dashboards and real-time graphics so that users can immediately recognize trends, anomalies and key figures and make informed decisions. Visualizations make complex relationships understandable, reduce coordination time and increase productivity. Whether OEE values on the shop floor, energy dashboards in buildings or KPI dashboards for management, our partner solutions connect machines, sensors and IT systems, automatically filter and aggregate data, and present it in a user-friendly way.
Historical and real-time data is systematically analyzed to identify patterns, trends and key performance indicators and to uncover optimization potential. The goal is to enable well-founded business and operational decisions, from fleet management to production optimization. Analytics platforms link data sources such as machines, systems, sensors or entire vehicle fleets, integrate them into central systems and deliver precise, application-specific evaluations. This includes root cause analytics for identifying causes, real-time analytics for immediate responses and event-driven analytics for detecting critical events.
Artificial intelligence is currently being used in pilot projects to automatically detect anomalies from IoT data, create forecasts and derive concrete recommendations for action. AI-supported IoT analytics combines structured machine data with unstructured information from documents, images, videos or large language models (LLMs), as well as other sources such as historical energy data, weather forecasts or procurement and infrastructure data. AI agents can shift operating times into cost-effective and sustainable time windows. Recommendations for action are based on cause-effect analyses, standard operating procedures (SOPs) and relevant contextual information. AIoT platforms process these insights in real time and integrate the results directly into existing systems such as MES, ERP or maintenance applications.
Industry-specific IoT apps offer preconfigured functions to quickly and efficiently solve concrete challenges, with a clear time-to-value. Many of our partners operate their own app stores where numerous proven applications are already available. These apps cover use cases that have already been successfully implemented within our network and can often be used without lengthy development projects. Why start from scratch when ready-to-use web-based applications already exist? Unlike smartphone apps, IoT software applications require a suitable technical foundation. The components shown on this page form the basis for running an app. Many providers now offer product bundles that combine this infrastructure with the right application. Feel free to contact us about this.
The right combination of functional modules is crucial for the success of your IoT implementation. If you are still unsure which building blocks are best suited or if you are looking for a specific solution, we are happy to help.
On our platform, we collaborate with leading companies that implement use cases in practice together with their customers. We review each partner in terms of the practicality of their solutions and their actual use by customers.
Every innovation starts with an idea. Discover proven use cases that support your digital transformation — from predictive maintenance to worker safety.
Real-time monitoring of machine and sensor data to reduce downtime.
Data-driven maintenance to detect failures early and cut costs.
Seamless tracking of assets and material flows in production and logistics.
Automated collection and management of production and operational data.
We know how difficult this decision can sometimes be. With more than 1,700 projects and 80 technology partners, we know the pitfalls and, above all, the best practices.
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