Research & Development at FleetMon
Driving Maritime Innovation with Smart Technologies and Ambitious Minds
Our research approach at FleetMon is based on two different objectives. First of all, we want to play an active role in shaping the maritime industry’s future. Therefore, we raise challenging questions and investigate innovative methods. We support researchers and innovators by offering access to the FleetMon API Suite and our extensive AIS Data Archive with historical vessel position and port call data. Combining those resources with the distinct know-how of our engineers and the maritime network we grew over time empowers us to develop innovative applications for the maritime domain.
For contributing to a greener and safer future of shipping, we collaborate with numerous well-known institutes and universities worldwide. Since FleetMon was established in 2010, more than 120 research institutes and universities contacted us to seek support. Our involvement ranges from onetime data deliveries to students or institutes, conducting field studies, to managing major funded research projects.
On the other hand, our research approach is customer-oriented. Our mission is to support our customers from the maritime industry to better cope with their maritime challenges. For this reason, we collaborate with a wide variety of partners, e.g., national and international research institutes, universities, shipping companies, global players of the logistics industry, consultants, and maritime interest groups. Our maritime network helps us to understand the needs and gaps in demand of the stakeholders. We conduct research and development to improve our products in line with customer needs.
Let’s just say, we combine intelligent technologies, creative minds, and a client-focused approach to drive maritime innovation.
Key Information
Research Areas
FleetMon Blog Posts
Require AIS Data for your Project?
Please reach out to us to discuss which FleetMon offering will support your research project or academic study in the best possible and efficient way.
Latest Projects
LEAS – shore-side decision support for traffic situations with highly automated or autonomous vessels using AI.
This project aims to increase maritime safety and is designed in the area of safety research. Through the use of artificial intelligence, the Vessel Traffic Service Center (VTS), Fleet Operation Center (FOC), and Vessel Coordination Center (VCC) will be technologically prepared for the occurrence of highly automated vessels. Concepts are being developed to visualize this information in the Human Machine Interface (HMI).
Case Study – Forecasting Inland Vessel ETA with Predictive Analytics
The Technical University Berlin conducted a case study in collaboration with the SELECT research project. Students were given the task to develop an arrival time prediction dashboard for inland vessels using AIS data provided by FleetMon.
MAREMIS – AI-based calculation of air pollution emitted by ships and its dispersion.
This is an international joint project between Singapore and Germany. In this project, artificial intelligence technology is used to investigate the spread of pollutants from ships in the ports. The results will be used to develop suggestions on how to improve air quality in cities near the ports. The project is supported, among others, by the ministries of transport of the cities and states as well as the port authorities.
LEAS – shore-side decision support for traffic situations with highly automated or autonomous vessels using AI.
This project aims to increase maritime safety and is designed in the area of safety research. Through the use of artificial intelligence, the Vessel Traffic Service Center (VTS), Fleet Operation Center (FOC), and Vessel Coordination Center (VCC) will be technologically prepared for the occurrence of highly automated vessels. Concepts are being developed to visualize this information in the Human Machine Interface (HMI).
Case Study – Forecasting Inland Vessel ETA with Predictive Analytics
The Technical University Berlin conducted a case study in collaboration with the SELECT research project. Students were given the task to develop an arrival time prediction dashboard for inland vessels using AIS data provided by FleetMon.
Latest Publications
SELECT – Artificial Intelligence in Inland Navigation
FleetMon provided inland AIS data for the SELECT project of the TU Berlin. This article, published in the journal Internationales Verkehrswesen, features how data-based arrival time forecasts can increase the reliability of inland waterway transports.
CADMUSS – an innovative project to improve maritime safety
The evaluation of a (maritime) traffic situation requires sound training and professional experience. Decisions can be made based on this training and experience. (Partially) autonomous ships must be trained or require generalized algorithms to react appropriately in any situation. The goal is for vessels to be able to determine the technical manoeuvring distance and the required personal perceived safety distance.
Determining the bilge water waste risk and management in the Gulf of Antalya by the Monte Carlo method
FleetMon supported researchers at the Akdeniz University in Antalya, Turkey and their study on bilge water waste risk in the Gulf of Antalya.
SELECT – Artificial Intelligence in Inland Navigation
FleetMon provided inland AIS data for the SELECT project of the TU Berlin. This article, published in the journal Internationales Verkehrswesen, features how data-based arrival time forecasts can increase the reliability of inland waterway transports.
CADMUSS – an innovative project to improve maritime safety
The evaluation of a (maritime) traffic situation requires sound training and professional experience. Decisions can be made based on this training and experience. (Partially) autonomous ships must be trained or require generalized algorithms to react appropriately in any situation. The goal is for vessels to be able to determine the technical manoeuvring distance and the required personal perceived safety distance.
Research Partners
FleetMon maintains long-term research relationships with companies and institutes around the world. See our Research Partner Gallery.
Academic Partners
Every month, we receive numerous data requests from universities and institutes to provide AIS data for research studies. View a collection of universities we supported in our Academic Partner Gallery.
About FleetMon
FleetMon is the world’s leading data company in the field of vessel tracking. We provide AIS-based data solutions from our own extensive, worldwide network of AIS receivers. Thousands of antenna stations send 5,000 signals per second to our database with some of the world’s best-known and best-performing companies making use of FleetMon’s data solutions. Our mission is to make shipping more transparent and efficient. To achieve that, we monitor the fleets of the world and create relevant, actionable data widely accessible. Established in 2007, FleetMon is a privately-owned company with its headquarters in Rostock, Germany.
Join Us
In R&D we believe that outstanding talent attracts outstanding talent. If you want to work in a culture that incentivizes courageous and smart risk-taking to help deliver the next generation of vessel tracking, join our team.