IoT integration - Optimize processes - Make informed decisions

The digital transformation is changing the way companies work. By integrating the Internet of Things (IoT) into business processes, data can be intelligently linked, workflows optimized, and costs reduced. The linking of sensors, cyber-physical systems and intelligent analysis tools creates the basis for data-driven process control in real time.

The Internet of Things refers to the networking of intelligent sensors, devices and machines that communicate with each other within an IP network. These systems continuously record environmental and status data that can be used for various applications in logistics, production and infrastructure. The effective use of this data requires powerful interfaces, secure data processing and scalable solutions that can be flexibly integrated into existing IT systems.

• Using real-time data: Process data is recorded, analyzed and processed in real time using sensors and networked systems.
• Automation and increased efficiency: IoT technologies can reduce manual workflows, avoid errors and make processes more efficient.
• Optimized maintenance through predictive maintenance: IoT systems detect deviations in operating data at an early stage so that maintenance measures can be initiated in good time.
• Dynamic adaptation to process requirements: Networking enables flexible control of machines, vehicles and warehouse processes depending on current operating conditions.
• Sustainable use of resources: Intelligent control and forward-looking planning allow material consumption, energy use and transport routes to be optimized.

In order for the Internet of Things to be efficiently integrated into existing processes, several components must work together optimally:

• IoT devices and sensors: These record physical values such as temperature, humidity, position or fill levels and continuously provide data for process optimization.
• Data management and IoT platforms: The volumes of data generated need to be collected, filtered, stored and processed for analysis. This is where powerful platforms and cloud solutions come into play.
• Secure network infrastructure: IoT systems require reliable and secure communication via wired or wireless networks to ensure uninterrupted data transmission.
• IoT edge computing: In many cases, data is processed directly on the device before it is transferred to a central platform. This can shorten response times and reduce network loads.
• Artificial intelligence and machine learning: Smart algorithms help to identify data patterns, optimize processes and create predictive analyses for process control.

A key component of IoT integration is the central control and management of networked systems. This is where the IoT Broker comes into play, networking cyber-physical systems such as intelligent containers or pallets and processing their data for further use.

The following functions can also be implemented via the IoT Broker:

• Management and updating of IoT devices
• Provision and execution of machine learning models (model deployment)
• Adjusting the configuration of sensors and actuators in real time

The IoT Broker thus forms an essential interface between IoT devices, data platforms and analysis tools to enable intelligent, automated control.