Supported projects in maritime transport


Maritime transport focuses on all topics regarding transport of goods and passengers by waterways


Partner: EXTREM’VISION (France) and SOLARIS OPTICS (Poland)

The objective of the GREAT EYES 1 project is to create a solution that consists of a new observation device like a compact and portable binocular integrating ultra-specialized digital sensor. This new product development aims to offer a new tool of supervision for the actors of the maritime and river transport as well as for security and borders surveillance. Today for the surveillance of the aquatic surface from a ship the devices used are traditional binoculars with prisms. These are available in several versions that are more or less efficient: magnification, compass, auto zoom, image stabilization... But these have all limitation when the brightness decreases at dusk or at dawn. The emergence of new ultra-high-definition sensor (U-HD> 4K) and ultra low-light sensor allows us to see the design paths of new equipment integrating these solutions with a controlled market positioning. GREAT EYES 1 project co-financed by NEPTUNE will allow the consortium driven by the French company EXTREM' VISION to develop the study and prototyping of this new and innovative binocular. The company SOLARIS OPTICS as the Polish consortium partner will work and contribute on his side on the design and prototyping of the special optical path adapted to the integration of these new sensors technology.



Partners: OptionsNET (Greece) and Sparsity Technologies (Spain)

The aim of MaSSy is to deliver an improved technological prototype that will carry the integration of two technologies/services that have been developed separately by the two companies for different sectors, SaMMY ( and CIGO! ( respectively.

The improved service that is planned to be created will exploit cutting-edge technologies and it will provide significant advances for marinas and the yachting community. Those services will also address the daily environmental protection challenges in yachting marinas, by improving the yachts mobility and route planning, by minimizing the yachters’ influence to the natural environment and by solving the most important needs and administrational processes of the marinas.



Partner: Predict (France)

The project aims to validate the scalability and also the worldwide internationalization deployment of the BMCI innovative technologies. The BMCI innovative technologies were developed thanks to the financial support of the French Funds for industrial research and the maturation support and project proposal improvement of the Pole Mer Méditerranée cluster. The digital technologies address the prognostics and health management (PHM) of vessels and fleet of vessels. The TRL of these technologies is 7 at this stage and the objective of the PROPHESEA project is to upscale the technologies in order to reach a TRL9. All the innovative technologies, independently of their own TRL, are integrated within the algorithms toolbox of CASIP® and KASEM®. CASIP® and KASEM® are well established platform with a TRL9 and able to exploit and disseminate disruptive or innovative technologies. The main interests of these innovative digital technologies are to improve the vessel efficiency and the environmental footprint by a better anticipation of drifts and abnormal functioning having impact on the embedded systems performances and emissions. These innovative digital technologies are related to Big Data, machine learning and predictive ones. Thanks to the complement with aggregation and ontologism technologies, PROPHESEA will address the fleet wide management of the whole vessels efficiency and global environmental footprint.



Partners: MyCFD and BSG (France)

The project consists in providing sail markers with an automated CAD-CFD workflow to allow them to produce more competitive sails. Unaffordable so far for small companies, CFD is essential to guide innovation. Our goal is to offer a low-coast CFD cloud service to sail makers through an automated CFD workflow that will be integrated into a web service. The user will assess the aerodynamic performance of his new sail design compared to a previous design, without being an expert in fluid mechanics. Thanks to the project “Sail-Automat”, sail makers can rely on innovative technology to develop higher performance sails.


Wave Model Confidence Index

Partners: Noveltis and Compagnie Maritime Chambon (France)

The project is implemented thanks to a partnership between two French SMEs: Noveltis, from Occitanie Region, specialized in Earth Observation and Compagnie Maritime Chambon, from Provence-Alpes-Côte-d’Azur Region specialized in port towage, sea rescue, offshore oil exploitation and Marine Renewable Energy. The project aims to develop a demonstrator of a system able to gather all measurements data made in the sea, by sensors or altimetry satellites as well as the sea state models forecasts. It will allow maritime users to be informed about wave heights and sea conditions in order to take the best decision regarding their itinerary.  



Partner: SAFETY DATA (France)

The aim of the DABBIE project is to realize the prototype of a future software solution whose purpose is to analyse the trajectories and the data of the movements (speed, speed variations, heading, heading variations) of cooperative vessels (vessels to be equipped with AIS Transponders) of the same type (deep-sea container vessels) in order to detect unusual behaviours or dangerous situations (collisions, violation of regulations, etc.). The main innovation of this solution is to transpose the existing approaches from aviation to maritime domain. The prototype will carry out a posteriori analysis (delayed time) whereas the solution that will be developed later will have to operate in real time and will have to integrate other functionalities not present in this prototype (including an alert system). In a first step, it is necessary to analyse vessels' positions using terrestrial and satellite AIS (Automatic Identification System) data. The second step is to describe the behaviour of groups of similar trajectories in form of spatiotemporal patterns and to characterize the behaviour of each vessel using these patterns. The modelling of the behaviour of vessels requires knowledge of the positions and trajectories, the itineraries and the homogeneous groups of trajectories. Using these spatiotemporal patterns and information such as speed, speed variations, heading or heading variations, it is possible to automatically detect and characterize the vessels' activity. Finally, by adapting them to the maritime domain, we will use algorithms coming from the field of aviation in order to determine the unusual and / or at risk behaviours based on the spatiotemporal patterns produced and the associated metadata (IMO, MMSI, the type of vessel, the flag state, the gross tonnage, the deadweight, overall length x overall width, the year of construction, the vessel's condition, the port of origin...) on vessels. The goal of the DABBIE project is to produce a software prototype in order to analyse, in delayed time, the behaviour of six deep-sea container vessels "mainline" or doing the "world tour" circuit, of three different ship-owners based on data collected during one year. The six vessels are: MAERSK SEVILLE, MAERSK EINDHOVEN, COSCO TAICANG, COSCO EUROPE, CMA-CGM MARCO POLO, CMA-CGM CHRISTOPHE COLLOMB and the three ship-owners are MAERSK, COSCO & CMA-CGM.



Partner: QUANTCUBE (France)

The modelling between shipping damages and oceanographic data will enable to create a maritime risk index series. This project aims at creating innovative risk index based on external and heterogeneous non-structured data such as oceanographic, meteorological and satellite data. The project will consist of assessing shipping risk exposure to the most important underlying risks such as rogue waves direct, cyclonic predictions and seasonal impacts. Indeed, our R&D team found out a direct significant relationship between oceanographic conditions and the size of the incidents within the shipping industry. Data access, heterogeneous data and technological issues have been obstacles to take account those external factors. QuantCube Technology aims at analyzing those external risks to create a new generation of maritime risk index. This index series creates value for the insurance industry and the shipping industry. Maritime Insurance applications: The addition of external data – predictions of cyclonic energy, waves strength…- enables a better estimation of risks during the shipping trajectory. Currently, maritime risk premiums are computed from actuarial mathematical model (GLM ) based on the characteristics of the ship and its final destination such as its value, dimensions, age, fuel and the harbours destination. Those “inherent features” are essential for an insurer to determine the insurance contract’s price but other factors such as oceanographic conditions are key to compute more accurate risk premia.

Shipping applications: During the three previous years, loss of containers phenomenon kept on increasing to reach a record annual average of about 2700 containers loss. Therefore, the addition of data sources as oceanographic data will be beneficial to the shipping industry, especially by defining optimal trajectories to reduce overboard losses of containers and damages. For both purposes, datasets such as oceanographic data from Copernicus Marine Service and Shipping Flows data combined with Artificial Intelligence will create value to set up new applications ‘Maritime Risk Index’ taking account additional risks generated by ocean conditions.