IoT solutions for companies

What are IoT solutions for companies?

IoT solutions, i.e. solutions based on the Internet of Things, connect physical objects such as machines, vehicles, sensors and systems with digital systems. They collect data from the real world, transmit it in real time and make it usable in business processes. What sounded like a dream of the future a few years ago is now a central component of many companies' digital infrastructure.

IoT solutions for companies encompass far more than simply networking devices. They include the entire chain from sensor technology, data transmission and processing through to visualization, alerting and integration into existing ERP or SAP systems. Only when machine data, position information or environmental parameters flow directly into business processes do IoT solutions unfold their full value.

prodot has been developing individual IoT solutions for SMEs and corporations for years. With our own IoT-X platform and an experienced team of over 80 IT experts, we support projects from the initial requirements analysis through to ongoing operation.

Why IoT solutions are indispensable for companies today

The amount of data that machines, vehicles and systems generate every day is growing exponentially. Companies that do not use this data systematically are wasting enormous potential: for cost reductions, quality improvements and new business models. At the same time, competitive pressure is increasing: those who use IoT data intelligently make better decisions, faster and on a more reliable basis.

Specifically, companies benefit from IoT solutions in several areas:

• Machines and systems are monitored around the clock.

• Deviations from normal operation are automatically detected and reported before they lead to failures.

• Maintenance intervals are no longer planned according to schedule, but according to actual need.

• Vehicles and mobile resources can be localized at any time and their data flows directly into billing and scheduling.

• Energy consumption, capacity utilization and production parameters become transparent, comparable and optimizable.

In short: IoT solutions make the invisible visible and the complex manageable.

The basis of every IoT solution: collecting, transmitting and processing data

Every IoT solution starts with the question of what data is generated where and how it is transmitted securely and reliably. Three layers form the technical basis:

Sensor technology and device connection. Sensors measure temperature, vibration, pressure, fill level, power consumption, position and many other parameters. They are either already installed in machines or are retrofitted. Industrial communication protocols such as OPC-UA, MQTT or REST enable the standardized connection of a wide variety of devices and controllers.

Data transport and connectivity. The recorded data is transmitted via suitable networks: WLAN, LTE, 5G or specialized IoT protocols such as LoRaWAN for energy-efficient transmission over long distances. The choice of the right transmission path depends on the amount of data, latency requirements and the application environment.

Data processing and storage. Incoming data is processed, filtered, normalized and stored in the cloud or at the edge. Cloud platforms such as Microsoft Azure provide the infrastructure for scalable, highly available IoT backends that run stably even with thousands of devices and millions of events per day.

Condition monitoring: keeping a constant eye on machine status

Condition monitoring is one of the most important applications of IoT solutions in industry. It refers to the continuous monitoring of the condition of machines and systems based on sensor data. The aim is to detect wear, malfunctions and impending failures at an early stage before they lead to unplanned downtime.

Typical parameters that are monitored in condition monitoring are vibration and oscillation on rotating components, temperatures on bearings, motors and gearboxes, current consumption of electric drives, pressure curves in hydraulic and pneumatic systems and acoustic emissions that indicate mechanical wear.

The measured values are continuously compared with defined reference values and limit values. If a parameter deviates, the system automatically triggers an alarm: via app, email or directly in the maintenance team's ticket system. This gradually turns a reactive maintenance organization into a proactive one.

prodot develops condition monitoring solutions that integrate seamlessly into existing machinery and IT systems. Whether retrofitting older systems with modern sensor technology or connecting new machines via OPC-UA: we ensure that your system speaks and your team listens.

Predictive maintenance: maintenance based on data instead of schedules

Predictive maintenance goes a decisive step further than condition monitoring. While condition monitoring monitors the current status of a machine, predictive maintenance uses machine learning algorithms to predict when a component will fail based on historical and current sensor data.

The result is the so-called Remaining Useful Life (RUL): the calculated remaining useful life of a component. Based on this prediction, maintenance measures can be planned exactly when they are actually necessary. Not too early, which causes unnecessary costs, and not too late, which leads to breakdowns.

The economic benefits of predictive maintenance are considerable. Unplanned downtimes can be reduced by up to 40 percent. Maintenance costs are reduced because scheduled maintenance is replaced by needs-based maintenance. Spare parts inventories are reduced because orders are placed on the basis of predictions rather than suspicion.

At prodot, we develop predictive maintenance solutions based on our IoT-X platform. We train machine learning models on your specific equipment and failure patterns, integrate the results into SAP PM or other CMMS systems and ensure that your maintenance team receives the right information at the right time.

IoT solutions and AI: the interaction that makes the difference

IoT solutions and artificial intelligence are not separate fields of technology. They complement each other in a way that holds enormous potential for companies: IoT provides the data, AI turns it into actionable insights.

AI models analyze continuous data streams from sensors and machines and recognize patterns that would be invisible to the human eye. Particularly relevant applications in the IoT context are

• Real-time anomaly detection: deviations from normal operation are identified and reported immediately.
• Predictive analytics: AI predicts when components will fail or process parameters will be out of specification.
• Automatic classification: events, alarms and error messages are assigned to the correct categories and responsible parties without manual effort.
• Optimization models: Optimal operating parameters for machines and systems are determined on the basis of real-time and historical data.

prodot develops IoT solutions that are AI-ready right from the start. Our technology stack based on Microsoft Azure includes Azure IoT Hub, Azure Machine Learning and Azure AI Services, so that AI functions are integrated from the ground up rather than being added later.

Modular IoT solutions: Step by step to a digital infrastructure

One of the most common concerns of companies embarking on IoT projects is complexity. Do you really have to rebuild everything at once? The answer is no. Modular IoT solutions enable a step-by-step approach, with each expansion stage delivering added value in its own right while laying the foundation for the next step.

A typical entry point is the connection of a manageable number of machines or vehicles and the visualization of their data in an initial dashboard. This step alone creates transparency that did not exist before. In the next step, automatic alerts are configured, initial evaluations are introduced and integration into ERP systems is prepared. AI models for predictive maintenance, comprehensive reporting functions and expansion to other plants or locations follow later.

This modular approach has several decisive advantages. The investment risk remains manageable because each phase can be evaluated separately. Findings from early phases flow directly into further development. And the company grows into the IoT solution instead of being overwhelmed by a complete system rollout.

IoT solutions in practice: use cases from various industries

IoT solutions are not a technology for a specific industry. They provide added value wherever physical objects generate data that previously remained unused. Some typical use cases:

Construction and road building. Construction machinery is monitored using GPS and an operating hours counter. Machine use is automatically billed in SAP. Fuel consumption and driving behaviour are analyzed and optimized. Geo fences on construction sites precisely record activities and automatically trigger follow-up processes.

Logistics and transportation. Vehicle fleets are monitored in real time. Telematics data from heterogeneous systems from different providers are brought together in a central platform. Hazardous goods transports are fully documented. Dispatching and route planning are optimized on the basis of current vehicle data.

Production and industry. Production facilities are monitored around the clock using condition monitoring. Predictive maintenance models calculate the remaining useful life of critical components. Production parameters are visualized in real time and alarms are automatically triggered in the event of deviations.

Energy supply and utilities. Meters, transformers and line infrastructure are monitored remotely. Consumption data is automatically recorded and evaluated. Faults are detected at an early stage and maintenance work is planned in a targeted manner.

Municipal companies and the public sector. Winter service vehicles are monitored via IoT and their use is documented. Fill levels in bins or waste containers are recorded by sensors and emptying tours are planned according to demand. Public infrastructure is maintained preventively.