Objective: This activity will design, implement and test software techniques to use multiple sources of data for maritime object detection, identification, localization and situation awareness services. Targeted Improvements:Improve maritime object vessel detection, identification and feature monitoring and intervention in open sea by at least by one order of magnitude compared to only Automatic Identification System (AIS) services. Description: Maritime transportation accounts for 90% of global trade volumes. While existing technologies such as terrestrial and space-based Automatic Identification System AIS have played a significant role in creating digital connectivity and localization of vessels, the needs for geospatial information and analytics across the globe for maritime awareness services is rapidly growing so that AIS alone is not sufficient to address such demands. This activity aims to utilize multiple sources of geospatial data together with interactive communication links and develop techniques to enhance the detection andlocalization of vessels at least one order of magnitude compared to pure AIS detection and tracking. Proposed activities include:-Investigate the use of Satellite VHF Data Exchange (VDE) services to collect additional information (Application Specific Messages) and download specific messages to vessels-Apply data mining and deep learning techniques to increase the accuracy of the vessel detection and localization, taking into account the past history of the vessel signature using multiple sources of data (Radio frequencyand imagery).-demonstrate the use of developed software for detection, identification and monitoring maritime asset.-Optimize the use of data sources in terms of timeliness, required resolution and cost-Work with Standardization such as IALA and IMO for initiatives such as e-Navigation. The proposed activity is expected to deliver a near-real time software functions for interfacing and combining multi-sources data analytics for maritime awareness services such as vessel detection, identification, monitoring unmanned vessels operation, Fuel and route optimization, weather and environment situation monitoring and intervention. The developed algorithms are expected to reduce the cost of maritime services by sharing the same data sources for multiple situation awareness services.

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