Objective 2: Foster Sustainable Use of Survey Data


Underwater munition detection is largely based on manual processing and visual interpretation of datasets. The efficiency in identifying munition related objects is extremely low. The majority of objects detected during specialized offshore surveys are not related to munition but must be treated the way until confirmed harmless. Artificial intelligence (AI) is better suited to objectively find correlations in ‘Big Data’ than experts can do.


  • Adapt multi-sensor database Amucad for extraction and calculation of the most relevant parameters from raw datasets for quality management and smart data analysis purposes
  • Develop and implement a concept for visualizing uncertainty based on quality metrics and simplified indicators for situation assessment
  • Incorporate new and existing datasets and jointly analyse them by using AI


The target is to provide tested and validated AI methods and streamlined workflows for data use. During the project both will be integrated into a multisensor database, which can be used to identify munition with uncertainty levels.