BM Bergmann Marine GmbH works for or together with companies, research institutes, governments and other organisations world wide.
Here a selection of some of those partners and clients:
BM Bergmann Marine is partner in various projects.
Here a few of the currently active projects:
Project Description:
The aim of LEAS is to research an Al-based decision support system for the onshore monitoring and control of mixed traffic. LEAS is geared towards the design, implementation and demonstration of land-based support services for conventional to autonomously navigating and possibly even unmanned ships. This deals with a still completely unknown maritime traffic scenario for which - apart from a few simulation studies - there is no practical experience with the operational requirements and processes. Due to the increasing complexity of traffic situations and the effects ofwrong decisions, the advisory components and modules developed should be based on elements that work with artificial intelligence and implemented in an innovative human machine interface (HMI}. This should explicitly show the human operator the intention of the automated system, i.e. the goals that the system pursues and the means that it uses for this (transparency of artificial intelligence decisions). The acceptance of the developed solutions is of central importance and should be covered by the accompanying research.
LEAS
Landseitige Entscheidungsempfehlung für Verkehrslagen mit hochautomatisierten bzw. autonomen Schiffen
(Land side decision recommendation for traffic situations with highly automated or autonomous ships)
Project Homepage:
Project Duration:
January 2022 to December 2024
Project Partners:
Project Description:
The purpose ofthe PASSport (Operational Platform managing a fleet of semi autonomous drones exploiting GNSS high Accuracy and Authentication to improve Security & Safety in port areas) is to engineer and qualify a solution extending situational awareness based on aerial fixed/ rotary wing and underwater drones to improve safety and security in port areas. The need stems from the directive 2005/65/CE asking to complement surveillance systems for the whole port area, in order to significantly improve security and safety for daily operations implanted in port area. This result also in saving citizen lives ensuring a high and equal level of safety and security for all European ports. Around one thousand European ports fall within the scope of the directive. As a consequence, PASSport responds to the needs expressed by port authorities, harbour master and border control authorities which are active parties in the consortium and will be directly involved in the definition of the proposed solutions. The proposed solution is intended to complement already operational platforms by extending the surveillance perimeter using a fleet of drones to provide innovation and operational support to the recognition, management and analysis of safety and security aspects of daily operations with particular attention to:
- Pollution monitoring (safety)
- Support to e-navigation (safety)
- Critical buildings/ lnfrastructures protection (security)
- Protection against non-cooperative small craft approaching the port areas (security)
- Underwater threats monitoring (security)
The project is expected to activate commercialisation channels based on the novelty represented by the usage of a fleet of semi-automated drones integrating Galileo services (and other sensors) for a safe and efficient guidance, navigation and control (GNC) even in a challenging environment in presence of obstacles - including buildings and other ground assets - and potentially unfavourable weather conditions.
PASSport
(Operational Platform managing a Fleet of semi-autonomous drones exploiting GNSS high Accuracy and Authentication to improve Security & Safety in port areas)
Project Homepage:
Project Duration:
November 2020 to November 2023
Project Partners:
MAREMIS
Maritime traffic modelling and verification for reducing maritime traffic emission based on spatia/-tempora/ big data
Project Description:
The consortium is developing Big Data and machine learning-based models and a demonstrator to measure, track, and validate emissions-related aspects of maritime transport to reduce emissions (exhaust, no ballast water or waste) from ships and improve local air quality. Validation is required because the basis for the project is data from the Automatie ldentification System. These may be partially erroneous or the ship may have disabled its AIS. lt is tobe investigated here whether, on the basis of the trajectories as a string of position signals in relation to the AIS navigation status, ships can no longer be detected in the AIS or whether they have deactivated their AIS.
Project Duration:
August 2021 to July 2023
Project Homepage:
https://research.fleetmon.com/projects/maremis-air-pollution-in-harbor-cities/
