If you are a border security agency struggling to coordinate patrols across vast land or maritime borders — this project developed an integrated sensor-and-AR system that fuses data from drones, cameras, acoustic sensors, and ground platforms into a single situational picture. It was tested in real conditions across 4 countries (Finland, Greece, Romania, Portugal) covering both land and maritime scenarios. The system optimizes team deployment and sensor positioning automatically.
AI-Powered Border Surveillance With Augmented Reality for Security Operations Teams
Imagine border patrol officers wearing AR glasses that show them exactly what's happening around them — detected people, vehicles, drone feeds, underwater sensor alerts — all fused into one clear picture. ARESIBO built a system that connects fixed sensors, drones (air, ground, sea, underwater), and cameras, then uses deep learning to make sense of all that data at once. The command center gets a live tactical map while field teams get only the information they need, right in their line of sight. They built three versions of the system and tested it in real border conditions across Finland, Greece, Romania, and Portugal.
What needed solving
Border security agencies struggle to process and coordinate information from dozens of different sensors, drones, and camera feeds across vast stretches of land and sea. Patrol teams in the field often lack real-time intelligence about what sensors are detecting nearby, while command centers are overwhelmed with raw data they cannot act on quickly enough. The result is blind spots, slow response times, and misallocated patrol resources.
What was built
ARESIBO built an integrated hardware-software system across 3 major versions (V1, V2, V3) that fuses data from fixed sensors, unmanned vehicles (air, ground, surface, underwater), cameras, and acoustic sensors into an augmented reality display for field teams and a tactical C2 dashboard for command centers. The system uses deep learning for data correlation and threat analysis, and was delivered through 37 project deliverables including dedicated sensing infrastructure components.
Who needs this
Who can put this to work
If you are a defense systems integrator looking for proven multi-sensor fusion and AR visualization technology — ARESIBO developed 3 iterative versions of an integrated hardware-software system with 20 consortium partners including Airbus Defence and Space. The platform handles collaboration between heterogeneous surveillance platforms (air, ground, surface, underwater) and could be adapted for your existing C2 infrastructure.
If you manage security for a large facility and need better awareness of what your cameras and sensors are actually detecting — ARESIBO built deep learning-based sensor correlation that turns raw data from multiple sensor types into actionable knowledge. The AR interface was designed to deliver minimum information for maximum understanding, reducing operator overload across 37 deliverables worth of development.
Quick answers
What would it cost to deploy this kind of system?
The project data does not include pricing or per-unit costs. ARESIBO was a research project led by Airbus Defence and Space with 20 partners, so any commercialization would likely come through Airbus or consortium members. Expect defense-grade pricing given the complexity of integrated hardware and software across air, ground, surface, and underwater platforms.
Can this scale to cover an entire national border?
The system was designed for tactical-level operations and tested in real conditions in 4 countries (Finland, Greece, Romania, Portugal) covering both land and maritime borders. It includes optimization of team deployment and sensor positioning, which suggests scalability was a design goal. However, full national-scale deployment would require further integration with existing national infrastructure.
Who owns the IP and can I license this technology?
ARESIBO was a Horizon 2020 RIA project with 20 partners across 11 countries, coordinated by Airbus Defence and Space SAS (France). IP is likely shared among consortium members under the grant agreement. Licensing inquiries should be directed to Airbus Defence and Space or specific technology providers within the consortium.
Has this been tested in real operational conditions?
Yes. The objective explicitly states testing in real conditions in Finland, Greece, Romania, and Portugal across 2 major system versions. Testing also took place in a controlled environment. The project produced 3 integrated system versions (V1, V2, V3) showing iterative development and validation.
Can this integrate with our existing surveillance infrastructure?
ARESIBO was designed to work with heterogeneous sensor types — fixed sensors, unmanned vehicles (air, ground, surface, underwater), cameras, and acoustic sensors. The sensing infrastructure deliverables specifically address communication interfaces between these elements. Integration with existing C2 systems was a core design principle.
Is this compliant with EU border security regulations?
The project was funded under the EU Security topic SU-BES02-2018-2019-2020, meaning it was designed to align with EU border security policy priorities. The consortium includes partners from 11 EU/associated countries. Specific regulatory compliance details would need to be confirmed with the consortium.
What ongoing support is available?
The project ended in July 2022. Ongoing support would depend on whether consortium members — particularly Airbus Defence and Space — have continued development commercially. The project website (aresibo.eu) and consortium contacts are the best starting points for current availability.
Who built it
This is a heavyweight consortium led by Airbus Defence and Space (France), one of Europe's largest defense contractors — a strong signal that the technology has commercial potential in the defense and security market. With 20 partners across 11 countries and a 40% industry ratio (8 industry partners including 5 SMEs), the project had both the engineering muscle and the operational expertise to build something real. The mix of 7 research organizations and 1 university provided the deep learning and sensor processing science, while the industry side handled integration and real-world testing. Testing in 4 different countries (Finland for arctic land borders, Greece and Portugal for maritime, Romania for land) shows the system was validated across diverse operational conditions, not just a lab demo.
- AIRBUS DEFENCE AND SPACE SASCoordinator · FR
- SERVICIUL DE PROTECTIE SI PAZAparticipant · RO
- ISTITUTO DI SOCIOLOGIA INTERNAZIONALE DI GORIZIAparticipant · IT
- TEAMVIEWER GERMANY GMBHparticipant · DE
- ROBOTNIK AUTOMATION SLparticipant · ES
- CROSS-BORDER RESEARCH ASSOCIATIONparticipant · CH
- ETHNIKO KENTRO EREVNAS KAI TECHNOLOGIKIS ANAPTYXISparticipant · EL
- RAJAVARTIOLAITOSparticipant · FI
- ETHNIKO KAI KAPODISTRIAKO PANEPISTIMIO ATHINONparticipant · EL
- TEKNOLOGIAN TUTKIMUSKESKUS VTT OYparticipant · FI
- INSTITUT PO OTBRANAparticipant · BG
- TEKEVER ASDSparticipant · PT
- OCEANSCAN - MARINE SYSTEMS & TECHNOLOGY LDAparticipant · PT
- NATO SCIENCE AND TECHNOLOGY ORGANISATIONparticipant · BE
- VIASAT ANTENNA SYSTEMS SAparticipant · CH
- MINISTERIO DA DEFESA NACIONALparticipant · PT
- ADMES MONOPROSOPI IDIOTIKI KEFELAIOUCHIKI ETAIREIAparticipant · EL
- INTELLIGENCE FOR ENVIRONMENT AND SECURITY SRL IES SOLUTIONS SRLparticipant · IT
- YPOURGEIO ETHNIKIS AMYNASparticipant · EL
Airbus Defence and Space SAS, France — reach out to their border security or surveillance solutions division
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