Industrial IoT is the integration and networking of intelligent, wireless sensors and actuators into industrial plants and processes in order to optimize them and equip them with new functionality.
Service-portfolio in detail:
We support our customers with our many years of know-how in the field of “Industrial Internet of Things” through research and development activities in the following service portfolio:
A frequent challenge for mobile sensors and IIoT nodes in industrial environments is the absence of a wired power supply. By using “Energy Harvesting” wireless sensors and actuators can be operated independently. Energy available in the environment such as ambient light or vibration is converted to electric energy, with which energy-saving (low power) sensor systems can be supplied.
Wireless communication between intelligent sensors and actuators must be protected against disturbances and external attacks by means of cryptographic algorithms. “Secure Sensors” ensure confidentiality, availability and integrity of sensor data.
Edge computing is the decentralized processing of (sensor-) data in a network of sensors and actuators. With embedded systems, data is preprocessed specifically to reduce the volume of communication. These smaller amounts of data can be “transferred” to make artificial intelligence learning faster and more efficient.
Locating network participants in real time is essential in the Industrial Internet of Things, so that products can interact with equipment, machines with tools and vehicles with warehousing. Only through the spatial allocation commodity flows can be optimized, transport routes planned, ergonomics and efficiency improved, and new application scenarios created. For a long time, this has been working “outdoors” in the form of GPS-based localization and navigation systems. Since recently, “indoor” localization systems via application-optimized localization networks with IIoT devices as nodes are being developed and deployed.
Integrated vision systems in the industry range from assistance systems that support assembly or machine operation, to fully automated production lines of digital factories, loading and unloading of transport systems or automatic navigation of automated guided vehicle systems (AGVS).
Since the beginning of digitization in industry, the available data volume via states and processes has been rising sharply. To process the vast amounts of data and to draw meaningful conclusions is the logical consequence. Targeted analysis methods make it possible to identify relationships between seemingly independent data streams. Production errors can thus be detected more accurately and preventive maintenance techniques can be developed. The system becomes more efficient, produces less waste, and maintenance times can be accurately planned.
State-of-the-art microelectronic devices and systems are prerequisites for intact industrial networking, as they are the core of every cyber-physical system (CPS) and the link between the real (physical) world and the virtual (cyber) image – they convert measurable quantities to sensor data. Microelectronic devices control flexible production processes and announce necessary maintenance work in industrial plants.
Data acquisition systems are becoming more flexible, less expensive, and capable of delivering larger volumes of data at shorter intervals. This poses great challenges to storage and transmission systems. When signals can no longer be completely recorded, output data must be reconstructed. Compressed sensing methods solve this problem by collecting just enough data to restore the original information, either to the exact extent or to a degree that is appropriate for the application.