ALERT Project Team & Contact Persons

The Departments of Self-Powered Radio Systems (EAF) and Machine Intelligence (MI) at the Fraunhofer Institute for Integrated Circuits IIS serve as research partners and lead the ALERT project. The institute is responsible for key technical tasks, in particular:

• Training and optimization of AI models
• Integration of on-device training functionality
• Development of energy-harvesting solutions (especially based on acoustics and vibration)
• Design of integrated power management ICs
• Adaptation of communication properties (QoS) in energy-optimized wireless technologies

Department of Self-Powered Radio Systems (EAF)

The department "Self-powered Radio Systems" at Fraunhofer IIS focuses on energy-efficient, highly reliable, and deterministic radio systems, RFID, and inductive sensors, as well as the necessary power supply. Within this project, the department is working on acoustic and mechanical energy harvesting systems and the required power management electronics. Furthermore, adaptive radio systems are being developed and researched that transmit both broadband raw data for training AI algorithms and energy-efficient anomaly information.

The Machine Intelligence (MI) Department at Fraunhofer IIS develops high-performance AI solutions for the connected world of tomorrow. Its focus areas include energy-efficient AI for future technologies, the earliest possible industrial use of quantum computing, and the localization and identification of radio interference sources. Within the ALERT project, the MI department is responsible for training and optimizing AI models as well as for the development and integration of on-device training functionality – with the goal of enabling powerful yet resource-efficient AI directly on self-powered devices. Applications range from security, robotics, and manufacturing to retail, with growing relevance in fields such as agricultural technology and smart cities.

DALOG Diagnosesysteme GmbH

DALOG Diagnosesysteme GmbH develops solutions and systems for online condition monitoring of machines to enable predictive and proactive maintenance. By combining state-of-the-art technologies with many years of experience, DALOG’s experts gain a precise understanding of the current condition and performance of each individual machine.

Within the ALERT project, DALOG investigates key questions regarding the energy efficiency and intelligence of wireless vibration sensors:

• Can AI-assisted data processing and transmission significantly reduce a sensor’s energy consumption?
• Can sensors powered by energy harvesting operate effectively without batteries?

In addition, DALOG explores which diagnostic functions can be meaningfully implemented directly on the sensor (“at the edge”) using artificial intelligence. The insights gained will contribute to the development of future product generations and help make machine condition monitoring more efficient and sustainable.

HOREICH GmbH

HOREICH GmbH is a spin-off from Friedrich-Alexander University Erlangen-Nuremberg (FAU). The company’s product portfolio includes embedded systems and conventional control systems for various infrastructure and environmental applications, which are developed, manufactured, and distributed in-house. Applications range from environmental parameter monitoring to industrial machinery and bridge structures.

A large portion of Germany’s aging infrastructure consists of bridges, whose condition is often difficult to assess due to their size, remote locations, and structural differences. Within the ALERT project, HOREICH is researching a system that uses energy-efficient sensing technology and local AI-based data processing to optimally monitor wear and fatigue components in bridges.
This enables the assessment of remaining service life, the planning of preventive measures, and the targeted maintenance of existing structures.

NORIS Group GmbH

The Noris Group GmbH is an international family-owned company headquartered in Nuremberg, Germany. Since 1925, the company has been developing and manufacturing customized sensor solutions, as well as automation and control systems for demanding industries. Its portfolio ranges from sensors and display instruments to engine and drive control systems, as well as power and energy management systems for ships, and cloud-based remote access and telemetry solutions. Customers from the shipbuilding, transportation, engine and gearbox manufacturing, and meteorology sectors worldwide rely on Noris products.
With around 250 employees and locations in Europe and Asia, the company stands for reliability, customer focus, innovation, and long-term partnerships.

As part of the ALERT project, Noris aims to expand its product portfolio by developing wireless vibration sensors designed for the early detection of gearbox damage – helping to prevent train failures and track closures.
The sensor will use on-sensor AI-based data processing to detect changes in gearbox vibration behavior, acting as an early warning system. To enable integration into existing train fleets, the sensor’s power supply will rely on an energy harvesting system.

TELIC AG

TELIC AG is one of the leading European providers of telematics and telemetry solutions. For more than 20 years, the company has been developing hardware, embedded software, and platform solutions for the digital connectivity of mobile assets and machinery.
Its modular IoT systems enable rapid market deployment and are manufactured exclusively in Germany according to automotive and industrial standards. In addition to customized solutions, TELIC offers a wide range of ready-to-use products in the fields of telematics, telemetry, and security. More than one million units are successfully in use worldwide.

Within the ALERT research project, TELIC AG contributes its expertise to the requirements analysis, development, and optimization of a flexible system concept, in close collaboration with the consortium partners. The project investigates the potential of edge computing and artificial intelligence (AI) with regard to energy efficiency, motion detection, and dynamic connectivity. This includes comparing AI-based approaches with classical algorithms, implementing a control simulation, and developing a use case using both methods. Furthermore, the project evaluates to what extent AI can be executed effectively in minimalist processor environments.

For further information about the ALERT project, please contact:
Dr.-Ing. Peter Spies, Fraunhofer IIS, Group Leader Integrated Energy Supplies.