Contextual Knowledge and Information Fusion for Maritime Piracy Surveillance

Proceedings of: NATO Advanced Study Institute (ASI) on Prediction and Recognition of Piracy Efforts Using Collaborative Human-Centric Information Systems, Salamanca, 19-30 September, 2011Though piracy accounts for only a small fraction of the general losses of the maritime industry it creates a serious threat to the maritime security because of the connections between organized piracy and wider criminal networks and corruption on land. Fighting piracy requires monitoring the waterways, harbors,and criminal networks on the land to increase the ability of the decision makers to predict piracy attracts and manage operations to prevent or contain them. Piracy surveillance involves representing and processing huge amount heterogeneous information often uncertain, unreliable, and irrelevant within a specific context to detect and recognize suspicious activities to alert decision makers on vessel behaviors of interest with minimal false alarm. The paper discusses the role of information fusion, and context representation and utilization in building an piracy surveillance picture.This paper has utilized the results of the research activity supported in part by Projects CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02-02/TEC and CAM CONTEXTS (S2009/TIC-1485)Publicad

Applying the Dynamic Region Connection Calculus to Exploit Geographic Knowledge in Maritime Surveillance

Proceedings of: 15th International Conference on Information Fusion (FUSION 2012), Singapore, 9-12 July 2012.Concerns about the protection of the global transport network have risen the need of new security and surveillance systems. Ontology-based and fusion systems represent an attractive alternative for practical applications focused on fast and accurate responses. This paper presents an architecture based on a geometric model to efficiently predict and calculate the topological relationships between spatial objects. This model aims to reduce the number of calculations by relying on a spatial data structure. The goal is the detection of threatening behaviors next to points of interest without a noticeable loss of efficiency. The architecture has been embedded in an ontology-based prototype compliant with the Joint Directors of Laboratories (JDL) model for Information Fusion. The prototype capabilities are illustrated by applying international protection rules in maritime scenarios.This work was supported in part by Projects CICYT TIN2011-28620-C02-01, CICYT TEC2011-28626-C02-02, CAM CONTEXTS (S2009/TIC-1485) and DPS2008-07029- C02-02.Publicad

Overview of contextual tracking approaches in information fusion

Proceedings of: Geospatial InfoFusion III. 2-3 May 2013 Baltimore, Maryland, United States.Many information fusion solutions work well in the intended scenarios; but the applications, supporting data, and capabilities change over varying contexts. One example is weather data for electro-optical target trackers of which standards have evolved over decades. The operating conditions of: technology changes, sensor/target variations, and the contextual environment can inhibit performance if not included in the initial systems design. In this paper, we seek to define and categorize different types of contextual information. We describe five contextual information categories that support target tracking: (1) domain knowledge from a user to aid the information fusion process through selection, cueing, and analysis, (2) environment-to-hardware processing for sensor management, (3) known distribution of entities for situation/threat assessment, (4) historical traffic behavior for situation awareness patterns of life (POL), and (5) road information for target tracking and identification. Appropriate characterization and representation of contextual information is needed for future high-level information fusion systems design to take advantage of the large data content available for a priori knowledge target tracking algorithm construction, implementation, and application.Publicad