Anomaly Detection in Vessel Location Data for Coastal Security

18/06/2021 – 19/06/2021 all-day

Offre en lien avec l’Action/le Réseau : DOING/– — –

Laboratoire/Entreprise : Institut de recherche de l’école navale
Durée : 12 mois
Contact :
Date limite de publication : 2021-06-18

Contexte :
The ENDOUME project aims to design and develop a new solution to automatically secure a coastal maritime area. This innovative solution, based on machine learning algorithms but also rule-based analysis, meets various needs in terms of maritime security; sailing races, maritime events (e.g., G7 / G20, Cannes festival, nautical events, Olympic Games 2024…); port approaches, wind farms, marine protected area, etc.). The solution consists of (1) an autonomous coast station, comprising radar, optronic sensors and an AIS transponder, and (2) a set communicating beacons deployed on cooperative vessels connected through a resilient and secure radio network.

Under the umbrella of ENDOUME project, we aim to detect and prevent marine events such as intrusions into a controlled access area or unusual behaviors that may pose a risk on a maritime event (a focus on sailing races is considered) and its ecosystem (including onshore areas) by a continuous monitoring and understanding of marine movements.

Sujet :
The research to be addressed concerns the development of innovative analytical and learning algorithms combined with rule-based analysis supporting maritime security. The research will be organized by the different works to conduct:

– Definition, modelling or learning of regular behaviours, patterns, and unwanted movements.
– Preparation, annotation, curation of dataset (learning and scenario design).
– Design and implementation of rule-based and learning algorithms.

The research will be based on historical data provided by the Automatic Identification System which provide location of ships on a regular basis as well as nominative information. A data stream with a fusion of optronic sensor data, radar data and AIS data will be provided by project partners

Profil du candidat :
Post-doctoral researcher or research engineer in computer science / data science

Formation et compétences requises :
Good skills in machine learning and data analytics; knowledge in statistics and data fusion. Preferred programming language (Python, Java, C/C ++). Knowledge in databases and geographic information science is a plus. Speaking, reading, and writing in English

Adresse d’emploi :
Lanvéoc (Finistère)

Document attaché : 202106021249_Fiche de Poste ENDOUME 2021.pdf