Title: Early Warning for Increased Situational Awareness


Grant agreement no: 608174


Duration: 1 September 2014 – 30 June 2019


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Research area:

This project proposal EARLY WARNING FOR INCREASED SITUATIONAL AWARENESS (EWISA) is addressing the FP7 Theme for Security Research the work programme topic SEC-2013.3.2-1 Pre-Operational Validation (POV) on land borders, the topic Area 10.3.2 Land borders as is aimed to promote further cooperation between public authorities as the end-users on developing new solutions to improve the quality and efficiency of public services related to security issues on topics of common European interest. The proposal is in the area of Activity 10.3, regarding the Intelligent Surveillance and Border Security with the specific funding scheme Pre-Operational Validation (POV), a Combination of Collaborative Project and Coordination (CP-CSA) and Support Action.
The project implements the actual strategic approach of Frontex, expressed in EuroSur , through which an intelligence picture of possible threats against MS is obtained, picture created outside the MS and Schengen area, through the combination of radar pictures with video pictures and with the intelligence collected from the sensor stations together with the ones from the MS partners, from checked sources. The threats which are subject to analysis in this project are the following: a) illegal migration, b) smuggling, c) trafficking in drugs and forbidden materials, d) trafficking in weapons.

The project will provide not only the assessment of a stand-alone technology, but also assessment of the integration into current surveillance infrastructure of the new capabilities provided by the industry.

The objective is to increase intelligence in video surveillance. The approach is a process like entity, which consists of:

  • camera-specific processes
  • a modular implementation of successive analysis layers, which is applied for optimal situational awareness: chaining, motion, figure.
  • in addition to the camera's processing capabilities, the network consists of: sensors, network analysis and system for control room.




This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 608174




European Commission