Artificial Intelligence in Border Control and Surveillance in the U.S. and EU

Border protection has always been a critical aspect of national security, evolving from rudimentary methods like horseback patrols and watchtowers to sophisticated technologies such as video surveillance systems and aerial patrols. However, these traditional methods face significant limitations, including slow response times, restricted coverage, and high operational costs. 

Artificial Intelligence (AI) has revolutionized border control and surveillance, offering unprecedented capabilities in threat detection, operational efficiency, and data analysis. 

This article delves into the transformative role of AI in border security, focusing on its applications in the United States (U.S.) and the European Union (EU).

The Rise of AI in Border Security

AI has emerged as a game-changer in border control, offering capabilities that far surpass traditional methods. By leveraging machine learning, computer vision, and data analytics, AI-powered systems can process vast amounts of information in real-time, enabling faster and more accurate threat detection. 

AI is transforming border security by improving surveillance capabilities. AI-powered cameras can monitor large crowds and vehicles in real-time, swiftly detecting unusual behavior or potential threats. Analysts can then assess this data to respond quickly and prevent security breaches. Additionally, AI technology aids in tracking cross-border movements and recognizing patterns of activity, allowing authorities to anticipate and mitigate future threats more effectively.

AI is increasingly being recognized as a valuable tool in border management, with governments and technology experts highlighting its potential to enhance border security and efficiency while, in some cases, making operations safer.

Border protection involves a variety of measures and technologies aimed at preventing unauthorized entry, criminal activities, and security threats. These efforts include physical barriers like fences and walls, as well as advanced monitoring systems such as drones, surveillance cameras, and satellite imaging. Additionally, border patrol units, checkpoints, and customs enforcement play a key role in regulating cross-border movements.

The primary goals of border security are to prevent illegal immigration, disrupt smuggling networks, combat human trafficking, and protect national security by detecting and intercepting individuals engaged in illicit activities, including potential terrorist threats.

The U.S. and EU have been at the forefront of adopting AI technologies to enhance border security, each with its unique approach and set of challenges.

AI in U.S. Border Control

U.S. border security agencies, including Customs and Border Protection (CBP) and the Department of Homeland Security (DHS), are implementing AI to enhance border surveillance, biometric identification, and threat detection. 

AI-driven border security technologies take various forms, including advanced algorithms that analyze subtle emotional cues in travelers, biometric systems for fingerprint and facial recognition, and intelligent scanning software.

Traveler Verification Service (TVS)

The Traveler Verification Service (TVS) is a biometric entry/exit system used by the U.S. Customs and Border Protection (CBP) to record arrivals and departures. TVS employs facial recognition technology to match live images with historical photo templates stored in a secure database. 

The system is designed to verify the identity of travelers quickly and accurately, enhancing security while streamlining the entry and exit process [1].

Case study: U.S. Department of Homeland Security Selects Biometric Face Verification Technology for Secure Border Crossings [2] 

The U.S. The Department Of Homeland Security (DHS) required an advanced, scalable, and secure method to verify the identity of travelers at border crossings. iProov provided the DHS with its Biometric Solutions Suite, featuring Dynamic Liveness technology. 

This AI-driven solution verifies a person’s identity by ensuring that the presented biometric data is authentic and captured in real time, eliminating risks associated with deep fakes, masks, or other spoofing attempts.

Dynamic Liveness Detection ensures that biometric data originates from a live individual during the scan.

Autonomous Surveillance Towers (Anduril)

The U.S. Customs and Border Protection (CBP) has deployed a network of autonomous surveillance towers. These 33-foot, solar-powered towers use a combination of radar, cameras, and AI-driven algorithms to monitor remote border areas and pinpoint movement sources.

Designed for flexibility and mobility, the towers can communicate with each other to track objects moving beyond their individual range and can be easily relocated as needed. The data collected from these towers—along with input from cameras, drones, LIDAR systems, and infrared sensors—is processed by the Lattice system, which provides real-time analysis.

The AI system is trained to differentiate between natural movement (such as tumbleweeds) and significant activity (such as vehicles or people), reducing false alerts. When it detects human or vehicle movement, it automatically notifies Border Patrol agents for further investigation. [3]

Case study: Autonomous Surveillance Tower (AST) for Border Security [4] 

Anduril Industries has deployed autonomous surveillance towers along the U.S.-Mexico border. These towers are equipped with cameras, sensors, and AI algorithms to detect and track people and vehicles attempting to cross the border illegally.

ASTs utilize AI, ML, and computer vision to automatically identify border crossings. This allows Border Patrol Agents to focus on more complex tasks, unlike traditional systems that require manual operation and monitoring for detecting incursions.

Vessel Detection

Advanced technologies and AI-driven analytics enhance maritime surveillance and sensor networks, improving the detection of illicit vessels amid high levels of legitimate trade and recreational boating. AI-assisted tracking increases situational awareness and threat response capabilities.

With Vessel Detection, agents can define search areas and criteria (e.g., people, drones, or vehicles), which are then relayed to sensors. AI-powered image recognition processes sensor data, identifying, filtering, and categorizing objects into Items of Interest (IoI) and non-relevant detections.

IoIs are automatically shared with detection systems for continuous tracking, while irrelevant detections (e.g., animals) are excluded. This system ensures seamless tracking across multiple sensors, optimizing border security efforts in maritime environments [5].

Case Study: The Increasing Use of Artificial Intelligence in Border Zones Prompts Privacy Questions [6] 

CBP has implemented AI-powered systems like the Northern Border Remote Video Surveillance System (NBRVSS) to monitor vessel movements along the U.S.-Canada border. 

According to CBP, the system is designed to identify and track vessels departing from the Canadian shoreline from a considerable distance. It can issue alerts when a vessel enters specific zones by differentiating between unusual vessel movements and regular traffic. If a vessel is flagged as suspicious, the system can use a camera to capture its appearance, determine the number of people on board, and retrieve its registration number for further investigation.

The NBRVSS system enhances the efficiency of border agents, addressing potential staffing shortages while also improving their safety. By enabling fewer agents to handle more tasks, the system could help the agency better adapt to workforce fluctuations.

Facial Recognition (The Technology to Identify Proof of Life, or “Liveness Detection”)

AI-powered facial recognition systems are widely used in e-passport gates and automated border control (ABC) systems. These systems compare travelers’ facial images with biometric data stored in passports or databases, enabling seamless identity verification and enhancing security by detecting fake passports and identity fraud.

International Airports and around 30 other locations, begins with capturing a traveler’s photo [7, 8]. Facial recognition software then compares the image to a scanned passport or license for identity verification. According to officials, the photo was deleted soon after the process.

This system, which passengers can choose to opt out of, is set to expand to approximately 400 additional airports in the coming years. [9]

Autonomous Aerostat

High-altitude aerial surveillance systems, such as aerostats, are used for persistent surveillance over border areas. AI algorithms enable autonomous launch and recovery of aerostats, even in adverse weather conditions, reducing the need for on-site staffing [10].

Case study 1: Advanced Balloon Manufacturing for Defence [11] 

The U.S. Department of Defense sought a low-cost, scalable alternative to satellites for ISR and communication in remote areas. Raven Aerostar’s high-altitude balloons provide persistent surveillance and reliable data transmission, navigating using wind currents and AI-powered flight control. A machine-learning algorithm predicts wind patterns, optimizing flight paths. 

This cost-effective alternative operates for weeks or months at a fraction of satellite costs, supporting defense, public safety, and disaster response.

Case study 2: Enhancing Maritime Security with Persistent Sea Surveillance System [12]

The U.S. Government partnered with TCOM, a recognized leader in persistent surveillance technology, to deploy its 71M strategic-class aerostat systems, renowned for their superior performance and durability compared to competitors. These aerostats, capable of reaching altitudes of up to 15,000 feet (4,600 meters) and providing a radar range of 370 kilometers (200 nautical miles), delivered the range and reliability required by the U.S. Coast Guard and Customs authorities to effectively manage border security operations.

TCOM Persistent Sea Surveillance System employs advanced aerostat platforms with integrated AI-driven technologies. By integrating wide-area monitoring capabilities, the solution has significantly reduced illicit activities and improved resource allocation.

Unmanned Aerial Vehicles (UAVs) / Drones

Drones have become an integral part of U.S. border security, offering versatile applications such as general border surveillance, drug trafficking prevention, anti-illegal immigration, search and rescue operations, and border infrastructure inspection. AI enhances drone capabilities by enabling autonomous navigation, real-time data analysis, and advanced sensor integration.

Since 2015, the U.S. Border Patrol has progressively expanded its fleet of drones, incorporating a diverse range of unmanned aerial systems [13].

Drones are playing an increasingly vital role in border security due to their versatility, rapid deployment, and ability to cover large areas efficiently. These unmanned aerial systems assist in various aspects of border control and surveillance, enhancing security operations with advanced technology.

1. General Border Surveillance

Drones equipped with pre-programmed flight paths and autonomous navigation systems systematically monitor specific border routes without continuous human control. Their obstacle avoidance technology and high-resolution cameras allow them to operate effectively in varied terrain and weather conditions. With real-time data transmission and AI integration, drones enhance threat detection and decision-making.

2. Combatting Drug Trafficking and Smuggling

Drones equipped with advanced sensors and aerial imaging assist authorities in identifying suspicious activities, detecting smuggling routes, and tracking illicit movements. Their agility and real-time intelligence capabilities enable dynamic tracking of suspect vehicles or individuals, improving border enforcement responses and disrupting criminal activities before they escalate.

3. Preventing Illegal Immigration and Terrorism

Drones with thermal imaging and facial recognition technology efficiently detect unauthorized crossings, even in extreme weather or remote areas. These capabilities help pinpoint individuals, ensuring officer safety and accurate threat assessment. Facial recognition further aids in identifying individuals with prior illegal entry attempts or known ties to criminal organizations.

4. Search and Rescue Operations

Equipped with thermal cameras and GPS tracking, drones have transformed search and rescue missions by scanning vast and challenging terrains quickly. By detecting heat signatures, they pinpoint missing persons with high accuracy, significantly reducing response time and improving the likelihood of successful rescues in remote or hazardous areas.

5. Border Infrastructure Inspection

Drones surpass manual inspections by providing high-resolution imagery for assessing border infrastructure. AI-powered analysis detects wear, damage, or structural weaknesses, while LiDAR sensors create detailed 3D terrain maps. This helps authorities identify vulnerabilities and reinforce border defenses strategically.

6. Incident Response and Crowd Monitoring

Drones are valuable for monitoring large gatherings, protests, or security incidents, providing live aerial footage for enhanced situational awareness. 

Their bird’s-eye view allows authorities to track movement patterns, anticipate disruptions, and coordinate rapid responses. Additionally, equipped with loudspeakers, drones enable direct communication with crowds, delivering warnings or instructions in real time.

With real-time intelligence, AI integration, and advanced sensors, drones are reshaping border security, making surveillance more effective, responsive, and cost-efficient.

Examples of UAVs in Border Security:

• Predator B (MQ-9 Reaper): Used by the U.S. Customs and Border Protection for long-endurance, high-altitude surveillance.
• Elbit Systems Hermes 900: Utilized by various countries for border surveillance, featuring high-endurance and advanced sensor suites.
• DJI Matrice 300 RTK: A commercial drone with versatile applications in border security due to its high stability, advanced imaging capabilities, and AI integration [14].

Automated License Plate Recognition (ALPR)

ALPR systems use cameras and AI software to read and record vehicle license plates, enabling the tracking and monitoring of vehicle movements across borders [15].

Case Study:  Embedding Security at Border Checkpoints. Application Story [16]

A provider of border security solutions is integrating VersaLogic’s Lion PCIe/104 OneBank single-board computer (SBC) into equipment that is being deployed at U.S. border checkpoints. 

Automated License Plate Reader (ALPR) technology has been implemented in both incoming and outgoing lanes at various land border checkpoints across the United States. This system enables the automatic scanning of vehicle license plates and cross-references them with law enforcement databases to identify any outstanding warrants or alerts. Additionally, ALPR is utilized to read truck license plates and verify them against pre-filed manifests submitted to Customs and Border Protection (CBP), significantly speeding up the processing time.

This advanced technology enhances the efficiency and accuracy of border operations, ensuring faster and more secure processing of vehicles and cargo.

AI in EU Border Control

In Europe, the importance of external border security has been underscored by a series of threats and crises, prompting policymakers to prioritize the protection of the EU’s borders as a key component of regional security. 

While borders remain a symbol of national authority, the EU, through its border agency Frontex, has taken significant steps toward establishing a more coordinated and unified approach to border management. 

Frontex, established in 2004 and based in Warsaw, has played a pivotal role in coordinating border security efforts across EU member states. In the wake of the 2015-2016 migration crisis, the agency’s mandate was significantly expanded, equipping it with new powers and resources. Today, Frontex deploys a range of advanced surveillance technologies, including drones acquired from Israeli military companies, mobile radars, thermal cameras, heartbeat detectors, and CO2 monitors designed to detect individuals concealed in vehicles.

The EU and its member states have also invested heavily in research and development for border technologies. Between 2014 and 2022, nearly €275 million was allocated to 49 research projects focused on innovations such as swarms of autonomous drones, AI-driven data integration, and systems for detecting illegal activities. Major beneficiaries of this funding include prominent research institutions like Germany’s Fraunhofer Institute, as well as private companies such as Leonardo, Smiths Detection, Engineering – Ingegneria Informatica, and Veridos [17].

Central to this effort are shared European IT systems, many of which are powered by AI. These systems form the backbone of the EU’s vision for “Smart Borders,” a complex network of automated and interconnected technologies designed to enhance border security while aligning with fundamental rights and ethical considerations.

In 2021, a comprehensive study funded by the European Commission explored how AI could be leveraged to improve border control, migration management, and security [18]. 

The study outlined a roadmap featuring nine key projects aimed at integrating AI into these critical areas. These projects include using AI to assess asylum applications, monitor compliance with immigration laws (such as analyzing welfare, tax, and social security records), and automate border surveillance. 

Given the unique challenges of patrolling sea borders, the EU has shown particular interest in deploying advanced technologies to monitor the Mediterranean, a region that has been a focal point of concern since the refugee and migration crisis of 2015-2016. EU leaders have consistently supported member states in their efforts to curb irregular crossings and enhance maritime border security.

One notable initiative in this space is the EU-funded ROBORDER project, which aimed to develop an integrated border surveillance and security system. 

This project utilized a range of cutting-edge technologies, including drones, robots, and AI-based software, to enhance the capabilities of border patrol agents. The system relied on a network of sensors, cameras, and unmanned vehicles to detect and track suspicious activities along borders in real-time [19].

The ROBORDER project, completed in August 2021 as part of the EU’s Horizon 2020 initiative, represented a significant step forward in autonomous border surveillance. It focused on deploying mobile robots capable of operating independently or in swarms across air, land, and water, equipped with advanced sensors such as optical, infrared, and thermal cameras, as well as radar and radio frequency detectors. These technologies were designed to identify criminal activities, including unauthorized border crossings and smuggling, while also addressing environmental threats like oil spills [20].

Automated Biometric Systems

The EU employs automated biometric systems, including fingerprint identification and facial recognition, to verify travelers’ identities at border crossings. These systems are integrated into e-gates and ABC systems, streamlining the border control process [21].

As part of the European Union’s “Smart Borders Initiative,” two fully automated systems will be introduced in 2025: the Schengen-wide Entry-Exit System (EES) and the European Travel Information and Authorization System (ETIAS). These systems are designed to record and verify the personal data of non-EU nationals as they cross the external borders of the Schengen Area. The goal of the EU’s “Smart Borders Programme” is to modernize and digitize the management of external borders, enhancing efficiency and security [22].

Emotion Detection AI

Emotion detection technologies aim to identify mental states and emotions based on facial expressions and other physiological characteristics. While not yet widely implemented at EU borders, research projects like iBorderCtrl [23] have explored the use of AI for deception detection during border checks.

Cargo Inspection & Smuggling Detection

AI enhances cargo screening by analyzing X-ray and CT scan images in real time. Machine learning models identify hidden contraband, weapons, or illegal substances more accurately than traditional methods. AI also helps automate customs declarations, reducing human error and expediting clearance processes.

Case study: AI Technology Enhances Passenger Throughput for Airports [24] 

Hermes Airports, which manages Larnaca and Paphos International Airports in Cyprus, faced increasing passenger volumes and heightened security requirements. 

SeeTrue’s AI technology leverages advanced algorithms for automatic threat detection in X-ray and CT baggage scanning systems. 

SeeTrue’s advanced AI algorithms effectively identify suspicious objects, even when they have been modified or taken apart.

AI analyzes sample data and makes decisions by generalizing patterns and insights derived from the information it has been trained on.

By integrating seamlessly with existing infrastructure, the solution analyzes baggage contents in real-time, detecting potential threats with high precision. 

AI technology provides security operators with clear, actionable alerts, reducing reliance on manual intervention.

Maritime Domain Awareness

AI-powered systems are used to monitor maritime activities, integrating data from Automatic Identification Systems (AIS), coastal sensors, and contextual information. These systems enhance the EU’s ability to detect and respond to maritime threats.

Case study: An AI-driven Video Monitoring Solution to Enhance Efficiency in Managing Shipping Traffic [25] 

The port of Scheveningen control center faced challenges in monitoring vast shipping traffic due to the limitations of traditional surveillance systems. 

To handle the challenging lighting conditions at the port, Bosch’s Flexidome IP starlight 8000i cameras were selected. The customised solution developed by Bosch together with its partner BrainCreators automatically registers and classifies shipping traffic.

The AI operates continuously, recording, documenting, and storing all vessel identifiers. It automatically adds supplementary information, such as the date, time, direction of travel, and speed. The camera feeds are integrated into a video management system, where ships not immediately observed by on-duty staff appear as still images on the screen. By analyzing this data, insights such as peak traffic periods, vessel types, trends, and anomalies are identified.

Robotic Systems

The EU is exploring the use of networked robotic systems for border control, including unmanned ground, aerial, and maritime vehicles. These systems offer versatile applications, from environmental monitoring to counter-terrorism. 

Autonomous Unmanned Aerial Systems (UAS)

UAS technologies are used for border surveillance, environmental monitoring, and disaster relief. AI enhances UAS capabilities by enabling object detection, classification, and tracking.

The EU has integrated drones into its border security strategy, using them for surveillance, reconnaissance, and rapid response. AI-powered drones offer real-time tracking, object detection, and alert systems, enhancing situational awareness and operational efficiency.

Object Recognition

AI-powered object recognition systems are used to detect and classify suspicious packages, vehicles, and cargo at border crossings. These systems rely on machine learning algorithms trained on annotated data . 

Geospatial Data Analytics

AI is used to analyze satellite imagery, enhancing the EU’s ability to monitor border regions and detect potential threats. Machine learning tools automate the analysis process, reducing the reliance on human imagery analysts [26]. 

Conclusion

AI has transformed border control and surveillance, offering unprecedented capabilities in threat detection, operational efficiency, and data analysis. The U.S. and EU have been at the forefront of this transformation, each with its unique approach and set of challenges. 

By integrating AI-powered tools such as facial recognition, automated license plate readers, biometric systems, and geospatial analytics, border agencies can process travelers faster, detect threats more effectively, and allocate resources more strategically. 

These technologies have enabled real-time monitoring, predictive analysis, and seamless data integration, transforming how borders are managed in an increasingly interconnected world.

AI has not only enhanced security by identifying suspicious activities and preventing illegal crossings but also improved the traveler experience by reducing wait times and streamlining processes. Case studies demonstrate the tangible benefits of AI, from intercepting human trafficking operations to optimizing cargo inspections and managing refugee flows.

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Artificial Intelligence-Based Capabilities For The European Border And Coast Guard Final Report. https://www.frontex.europa.eu/assets/Publications/Research/Frontex_AI_Research_Study_2020_final_report.pdf