Project: FastSense – Sensors and AI for environmental and hazardous substance monitoring

Innovative sensor technology and AI: A rapid measurement system for environmental and hazardous substance monitoring

Project duration: 11/2025–12/2027

green trees on brown dirt road — The Saxony Forest Condition Survey shows a significant deterioration in both deciduous and coniferous stands.

© Fraunhofer IPMS
Chip developed at Fraunhofer IPMS, with integrated ion filter and ion detector as the basis for an ion mobility spectrometer.

As part of this research project, a portable, fast GC-IMS-based measurement system is currently being developed that will enable precise, real-time emissions assessment for environmental and hazardous substance monitoring. The motivation for the project is the growing need for sensory systems to monitor environmental parameters, especially for detecting damage to forest ecosystems. Current surveys, such as the forest condition survey in Saxony, show significant deterioration in deciduous and coniferous trees. Early detection of damage, for example from pests or tree diseases, is crucial for initiating countermeasures and ensuring the long-term preservation of the forest ecosystem.

The planned system will combine state-of-the-art sensor technology with AI-supported data processing and enable automated evaluation of complex measurement data such as retention time, drift time, and intensity. In addition to applications in environmental monitoring, the potential for other areas is also being investigated, including civil security (e.g., combat and explosive materials, hazardous substances), industrial process monitoring, and medical diagnostics.

The transdisciplinary collaboration between the Center for Applied Research and Technology (ZAFT), the Helmholtz Centre for Environmental Research (UFZ), and Fraunhofer IPMS brings together comprehensive expertise: from the use of AI-based algorithms to the development of field-ready sampling systems and calibrations to the miniaturization of innovative sensor components. The goal is to create a portable, compact demonstrator that will support the early detection of forest damage and serve as the basis for future sensor networks.

The research and development project opens up prospects for fast, reliable, and portable solutions in environmental and hazardous substance monitoring and sets standards for the integration of sensor technology, AI, and miniaturized measurement technology.

Motivation

The Saxony Forest Condition Survey for 2023 shows a significant deterioration in both deciduous and coniferous stands. The protection and preservation of the forest ecosystem is seen as a key task, as it plays a crucial role in securing the basis for life on land in the future.

Against this backdrop, the planned project aims to develop and validate a miniaturized, portable measuring system for real-time monitoring of ecosystem parameters in forest landscapes. This system combines a fast gas chromatograph with an ion mobility-based gas sensor (GC-IMS) and is designed to enable early detection of damage such as pest infestation or tree diseases. Based on the data obtained, targeted countermeasures can be taken in a timely manner.

Critical stressors lead to changes in the composition of the volatile and semi-volatile organic compounds (VOCs) emitted by trees. The UFZ has been active in this field for many years and, through its basic research, has been able to clearly demonstrate the need for portable sensor technology for three-dimensional data collection of VOC emissions in forests. The individual substances are often present in extremely low concentrations and must be recorded on a substance-specific basis despite the large number of background gases. Currently, this can only be done using complex laboratory analysis and is not feasible with existing mobile devices.

The development of a portable, innovative solution that enables fast and uncomplicated emission analysis directly on site is therefore forward-looking. In view of the enormous amounts of data to be expected, new AI-based evaluation algorithms are also required for this purpose.

Other applications include civil security (detection of explosives, combatants, and hazardous substances), industrial process monitoring, and medical diagnostics.

Project partners:

Center for Applied Research and Technology at Dresden University of Applied Sciences (ZAFT)
Helmholtz Centre for Environmental Research (UFZ)
Fraunhofer IPMS