• Medientyp: E-Artikel
  • Titel: AI-Prepared Autonomous Freshwater Monitoring and Sea Ground Detection by an Autonomous Surface Vehicle
  • Beteiligte: Pose, Sebastian; Reitmann, Stefan; Licht, Gero Jörn; Grab, Thomas; Fieback, Tobias
  • Erschienen: MDPI AG, 2023
  • Erschienen in: Remote Sensing
  • Sprache: Englisch
  • DOI: 10.3390/rs15030860
  • ISSN: 2072-4292
  • Entstehung:
  • Anmerkungen:
  • Beschreibung: <jats:p>Climate change poses special and new challenges to inland waters, requiring intensive monitoring. An application based on an autonomous operation swimming vehicle (ASV) is being developed that will provide simulations, spatially and depth-resolved water parameter monitoring, bathymetry detection, and respiration measurement. A clustered load system is integrated with a high-resolution sonar system and compared with underwater photogrammetry objects. Additionally, a holistic 3D survey of the water body above and below the water surface is generated. The collected data are used for a simulation environment to train artificial intelligence (AI) in virtual reality (VR). These algorithms are used to improve the autonomous control of the ASV. In addition, possibilities of augmented reality (AR) can be used to visualize the data of the measurements and to use them for future ASV assistance systems. The results of the investigation into a flooded quarry are explained and discussed. There is a comprehensive, high-potential, simple, and rapid monitoring method for inland waters that is suitable for a wide range of scientific investigations and commercial uses due to climate change, simulation, monitoring, analyses, and work preparation.</jats:p>
  • Zugangsstatus: Freier Zugang