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https://doi.org/10.5194/egusphere-2026-2492
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/egusphere-2026-2492
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Modular Hardware and Software System for Multi-Sensor Environment Perception (MOSEP)
Abstract.
Dynamic environmental processes, from landslides and avalanches to river channel migration and glacier calving, demand innovative monitoring solutions that offer both high spatial and temporal resolution while being robust and cost-effective. Recent advances in robotics and autonomous systems have introduced a new generation of perception sensors, including lidar, radar, and cameras, that have the potential to transform environmental monitoring. While these technologies have long been applied in science, they have traditionally been highly specialized, costly, and designed for narrow use cases. This paper investigates the capabilities of emerging low-cost, lightweight perception sensors for environmental monitoring, including meteorological applications. We introduce the Modular Hardware and Software System for Multi-Sensor Environment Perception (MOSEP), an adaptable and portable hardware platform complemented by a fully open-source software stack that enables time-synchronous collection of multi-sensor data. MOSEP integrates automotive-grade perception sensors with meteorological instruments, offering a temporal resolution of up to 20 Hz and a range of several hundred meters. The system's robustness and flexibility were validated in real-world scenarios, including stationary deployments and mobile data acquisition on land and sea, such as for iceberg mapping in East Greenland. This paper details the design, integration, and capabilities of the MOSEP platform, showcasing its scalability and adaptability. The results underscore the utility of MOSEP as a versatile tool for environmental sensing, with broad applications in geoscience and other fields. By providing a reproducible, open-source platform, this work aims to motivate researchers to adopt these emerging sensor technologies for their own applications.
How to cite. Gaisberger, C., Muckenhuber, S., Schlager, B., Goelles, T., Genser, S., Schratter, M., and Schöner, W.: Modular Hardware and Software System for Multi-Sensor Environment Perception (MOSEP), EGUsphere [preprint], https://doi.org/10.5194/egusphere-2026-2492, 2026.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
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RC1: 'Comment on egusphere-2026-2492', Anonymous Referee #1, 09 Jul 2026
The authors present a flexible and modular platform for various perception and environmental sensors. The components are off-the-shelf products, and the software is distributed under open access, allowing others to use this setup for further studies and analysis.Overall, the paper is well written and should also be understandable to scientists with less background in electronics and software development.As mentioned by the authors, there might be a wide field of applications for the platform in geo- and environmental studies. However, as also mentioned in the Discussions Section, the rather limited range of the sensors right now might also strongly limit the applications. Let's hope for further sensor improvements as briefly discussed by the authors.Major issues:The authors also show some use cases of the platform and mention its suitability for permanent monitoring tasks. However, for this, at least some basic information on the power consumption of the system and handling of power failures should be provided. For sure, it strongly depends on the sensor setup and acquisition parameters (e.g., frequency), but at least for both use cases (iceberg monitoring and the rainfall test), the power statistics would be interesting.Moreover, a more detailed wiring diagram in addition to Fig. 3 and 4 would be very helpful and beneficial for potential users to rebuild the system. Could be provided in the paper or as supplementBesides this issue, there are just a few minor issues (listed below):L22: Frequency…l85: API not introducedl102: Explain IP68 for a wider audiencel121: What does “compare 3” refer to?L385: Unclear. First, you state that these reflections are from below the water surface, and now, that they might be from above. Please rephrase to be clearer.L420: If the range of the lidar or radar were larger, right now, this might be a limiting factor for many applicationsL454: Does FMCW not refer to radar instead of lidar?Citation: https://doi.org/
10.5194/egusphere-2026-2492-RC1 - RC2: 'Comment on egusphere-2026-2492', Anonymous Referee #2, 09 Jul 2026
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Christoph Gaisberger
CORRESPONDING AUTHOR
Department of Geography and Regional Science, University of Graz, 8010 Graz, Austria
Stefan Muckenhuber
Department of Geography and Regional Science, University of Graz, 8010 Graz, Austria
Institute of Industrial Management, FH Joanneum Graz, 8605 Kapfenberg, Austria
Virtual Vehicle Research GmbH, 8010 Graz, Austria
Birgit Schlager
Department of Geography and Regional Science, University of Graz, 8010 Graz, Austria
Virtual Vehicle Research GmbH, 8010 Graz, Austria
Thomas Goelles
Department of Geography and Regional Science, University of Graz, 8010 Graz, Austria
Virtual Vehicle Research GmbH, 8010 Graz, Austria
Simon Genser
Virtual Vehicle Research GmbH, 8010 Graz, Austria
Markus Schratter
Virtual Vehicle Research GmbH, 8010 Graz, Austria
Wolfgang Schöner
Department of Geography and Regional Science, University of Graz, 8010 Graz, Austria
Short summary
To utilize newly emerging perception sensors to track rapid environmental changes, like melting glaciers or rock falls, we developed MOSEP (Multi-Sensor Environment Perception), an affordable, portable monitoring system. We tested it by mapping icebergs in Greenland and in heavy rain, proving it works in harsh conditions. By sharing our open-source design, we hope to make advanced environmental monitoring more accessible, helping more scientists to better understand our changing planet.
To utilize newly emerging perception sensors to track rapid environmental changes, like...