System for Detection of Threat Agentsin Maritime Border Environment

System for Detection of Threat Agentsin Maritime Border Environment

WHO DEVELOPS THE SAFESHORE PROJECT?

a. Stationary detection point: b. Stationary chain-of-detectors along high-risk border areas

Border protectionorganizations

Criticalinfrastructureoperators

Lawenforcementagencies

Administrators of environmental protected areas

Governmentofficials protection organizations

Public andsports eventsorganizers

c. Mobile deployable system in areas where intelligence predicts higher volume of illegal or threatening activities

• in harbour areas, at river border crossing, to detect remote delivery of explosives or chemical weapons, and border trafficking of drugs

• for coast radars, to detect remote delivery of explosive charges

WHAT IS SAFESHORE?

SafeShore is a system developed to detect threat agents in maritime border environment: low altitude drones and their remote control equipment, small vessels coming to shore, humans emerging from the sea. It was designed to be affordable, easily deployable in border surveillance and incorporating low cost and green technologies, with reduced impact on the environment.

THE SAFESHORE SYSTEM CAN BE USED AS:

WHO ARE THE BENEFICIARIES OF THE SAFESHORE PROJECT?

WHAT TECHNOLOGIES DOES SAFESHORE USE?

SafeShore develops a system that integrates multiple commercially available detection technologies to ensure the detection of low-altitude flying drones and small boats.

• Laser ranging (LIDAR) detection• Passive acoustic detection• Visible and thermal CCTV target classification• Passive radio communication detection

FIXED SYSTEM DEPLOYABLE SYSTEM

Acoustic Sensors Acoustic Sensors

Acoustic Sensors Acoustic SensorsAcoustic Sensors Acoustic Sensors

LIDAR

CCTV CCTV

LIDAR

Radio Monitoring Radio Monitoring

Academia Partners Country ContributionRoyal Military Academy of Belgium Belgium Consortium coordinator, passive radio detectionQueen Mary University of London UK Video analyticsUniversity of Salento Italy Analysis and data fusion

Industry Partners Country ContributionDr. Frucht Systems Ltd. Israel Laser detection systems and algorithmsUTI Grup Romania Video analytics, data fusion, GIS & C2TG Drives Czech Republic Laser detection systems platformOptix Bulgaria Visible & thermal camera systems

End User Partners Country ContributionThe Protection and Guard Service Romania Field trial of the system (Black Sea)Romanian Border Police Romania Field trial of the system (Black Sea)Ministry of Public Security Israel Field trial of the system (Mediteranean Sea)Police Region West Coast Belgium Field trial of the system (North Sea)

Research Partners Country ContributionInstitute of Optoelectronics Romania Visible & thermal camera systems

UTI CONTRIBUTION TO THE SAFE SHORE PROJECT

SafeShore is a system developed to detect threat agents in maritime border environment: low altitude drones and their remote control equipment, small vessels coming to shore, humans emerging from the sea. It was designed to be affordable, easily deployable in border surveillance and incorporating low cost and green technologies, with reduced impact on the environment.

VIDEO ANALYTICS

Video analytics engine

Scenarios and decision support module development

C2 server, interfaces and GUI developmentData fusion engine development

GIS platform development

Our objective is to develop and implement innovative video analytics algorithms, create data fusion algorithms for multimodal detection and tracking of RPAS and develop the appropriate command and control engine and interface.

By developing a video analytics engine for the detection of threat agents in maritime boarder environment, the beneficiary will be able to check the target validity and generate alarms with the command and control centre.

SafeShore integrates different cutting-edge technologies & security systems into a unitary “system of systems”, capable to satisfy, at affordable costs, the maritime border security requirements. Non-intrusive topology, smarter design and better algorithms help avoiding over-complication, maximizing the accuracy. The solutions also enhances security by unifying all information into a centralized platform that increases significantly effectiveness by using fewer resources.

BENEFITS:

UTI TASKS:

Our company will create specifications of a prototype software solution specific for the maritime border protection scenario.

The SafeShore project philosophy is to integrate data and knowledge gathered by using different technologies & sources such as Lidar, Acoustic and Video analytics. Therefore, our experts will develop a data fusion engine: takes the outputs from sensor data processing components and uses them (aggregates) to make a unitary decision.

The UTI project team develops a GIS database and a graphic representation engine based on open-source software components. This will generate a representation of all the system elements, emphasizing their actual location and the detection characteristics, as well as the detected targets.

The GIS platform also provides the framework that integrates other real data collected form external systems.

Early warning on potentially unauthorised incidents

Define, based on end-user know-how, the operational procedures and scenarios

Development of the server modules to allow both horizontal and vertical integration

Development of a single graphical user interface for complete system operation

Development of the server modules for communication with each detection sub-system and other system modules

Development of a GIS module

Develop and implement a special software module, scenarios and decision support, based on a military approach

Maximum situational awarness

Accurate and robust automatic data processing with a low false alarm rates

DRONE DETECTION DEVICE

START START

RECEIVE SOUND SIGNAL Receive a feature frequency spectrum

Determine wasserstein metrics by comparing the feature frequency

spectrum to drone sound signature

Select closest drone sound signatures having the lowest wasserstein metrics

Determine a drone class of each of the drone sound signatures

Apply classification hit

Transmit alert

Indicate the appropriate drone sound signatures are false signatures

RECORD A SOUND SAMPLE FROM THE SOUND SIGNAL

DIGITIZE THE SOUND SAMPLE

PARTITION THE DIGITIZED SOUND SAMPLE INTO EQUAL SEGMENTS

CONVERT EACH SEGMENT INTO A FREQUENCY AMPLITUDE VECTOR

SMOOTH EACH OF THE FREQUENCY AMPLITUDE VECTORS

APPLY A BANDPASS FILTER TO THE FREQUENCY AMPLITUTE VECTORS

FORM A COMPOSITE FREQUENCY VECTOR

NORMALIZE THE COMPOSITE FREQUENCY VECTOR

APPLY LOCALIZED BACKGROUND SPECTRUM

TRANSMITVECTOR

DRONE SOUND SIGNATURE?

SAME DRONE CLASS?

CLASSIFICATIONHITS

RECEIVEFEEDBACK

YES

YES

YES

YES

NO

ACOUSTIC SENSING PLATFORM DEVELOPMENT

• The acoustic platform is designed to detect, locate and classify RPAS targets within its detection range.

• Audio signal analysis• It consists of a microphone array (tetrahedral or other configuration), a

signal conditioned module, a signal acquisition module for A/D conversion and the processing software.

• The detection software covers the blocks in the flow diagram next page:

Audio Pattern RecognitionThe results obtained under the following circumstances:

Distance: 250 metersAltitude: 10 metersUAV model: OctocopterType of classificatio: medium

NO

NO

NO

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