Heterogeneous and Self-Adaptive Acoustic Monitoring Network – RESSACH

Oceans are the heart of the development of intense economical and industrial activity, supports by current developments of marine renewable sites. The maritime spaces are facing huge competition among professionals of the sea. These economical activities also impact marine ecosystems. Such impacts have to be considered in the planification of the maritime spaces.

Several regulations have appeared in order to ensure the safety for whole users. As an example, the Automatic Identification System (AIS) which equips all ship with 300 or more gross tonnage. However, it does not equip all ships yet, and can be easily turned down in order to hide the navigation and activities in specific areas. Additional systems (Radar, Satellite images) can be considered, without guarantee of detection all the suspicious activities.

Ocean is a relevant medium for propagation of acoustics, sound can propagate over large distance depending on the frequency, the source levels and the properties of the environment, whether they are static (bathymetry, seabed nature) or dynamic (hydrologic conditions). Acoustic monitoring is a relevant alternative to other approaches. Underwater acoustic networks are already used for the environmental purpose on tracking marine populations, as well as detecting target in operational theatres.

Performance of such acoustic network depends on its intrinsic characteristics and the properties of the marine environment. The RESSACH project considers to consider the physical environment and its associated uncertainties to guarantee the performance level of detecting acoustic signature. The project will rely on the integration of acoustic, seismic and hydrologic sensors in the network. Performance will be optimized on the basis of realistic simulation, and by considering additional underwater vehicle with acoustic sensors. Artificial intelligence provides a relevant framework to support the optimization process, and to develop a tool merging detection algorithm.

The project covers both military and civilian purpose. It will provide tools for optimizing the monitoring strategy according to the environmental knowledge, as well as support to decision maker in warfare context. In particular, it has strong relevancy to the use of underwater drone.