Asia – AI in Maritime & Homeland Security

Asia’s coastlines, straits and island chains shape the world’s busiest sea lanes—and some of its most complex security challenges. From smuggling and illegal, unreported and unregulated (IUU) fishing to grey-zone incursions, drone swarms and cyber-physical attacks on ports, the threat surface is expanding across air, sea and spectrum. Artificial intelligence is becoming the quiet force-multiplier behind how nations see sooner, decide faster and act more precisely. This feature explores three live fronts—AI in coastal defence, drone-based threat detection, and AI-enabled border monitoring—through the work of five influential players: Bharat Electronics Limited (India), ST Engineering (Singapore), Hanwha Systems (South Korea), NEC (Japan), and DJI (China, non-lethal surveillance applications).

Why AI—and why Asia?

The region’s maritime geometry sets the agenda. Chokepoints such as narrow straits and crowded archipelagos produce dense, noisy data: overlapping radar returns, look-alike small craft, and weather that confuses legacy analytics. Borders are long, porous and often amphibious—coast meets city, port meets hinterland. Conventional monitoring strains under the load.

AI earns its keep here by converting sensor overload into decision-ready insight. Edge models triage video, radar and radio-frequency (RF) feeds; fusion engines reconcile contradictions; and learning systems adapt to local patterns—monsoon lighting, seasonal fishing fleets, festival traffic—so operators act on signals, not noise.

Coastal defence: from watchposts to intelligent shorelines

Coastal defence is shifting from discrete sensors to software-defined shorelines where radars, cameras, AIS receivers, passive RF listeners and acoustic arrays behave as one.

What’s changing:

• Edge AI on the waterline. Instead of shipping every frame to a control room, smart towers perform on-site detection—classifying small targets, suppressing wave clutter and flagging unusual tracks. This reduces bandwidth, lowers latency and keeps surveillance effective even when links are degraded.

• Multi-INT fusion by default. Modern command centres correlate AIS declarations, non-cooperative radar plots, thermal imagery and RF emissions to build confidence before dispatch. A wooden skiff without AIS is treated differently if thermal shows a hot engine, RF sniffers detect handheld radios, and radar notes erratic speed profiles.

• From dots to behaviours. AI models learn local “normal”. A boat hugging a reef at 02:00 may be a fisherman in one bay, a smuggler in another. Behavioural baselining turns context into cues.

Bharat Electronics Limited (BEL) has been instrumental in building integrated coastal surveillance across the Indian littoral and island territories. Its approach pairs shore-based radars, electro-optic payloads and command-and-controlwith AI-assisted classification to prune false alarms and prioritise intercepts. The practical win: fewer fruitless dispatches and faster cueing of navy, coast guard or marine police assets.

ST Engineering brings a systems engineer’s discipline to harbour security, port perimeters and strait monitoring. By hardening edge nodes against salt, heat and corrosion, and by standardising interfaces, it enables sensor-agnostic fusion—the backbone of truly maritime-grade AI. Where budgets are tight, ST’s modularity lets authorities add capability in layers: start with thermal cameras, add RF detection and radar later, without refactoring the whole stack.

Hanwha Systems extends coastal awareness into air and surface counter-intrusion. AI-enhanced radars and optronics sharpen detection of small, low-RCS targets—fast boats, hobby drones, micro-UAVs—while tracking algorithms sustain custody in cluttered inshore waters. Its strength lies in tracking continuity: keeping a truth track across sensor hand-offs and manoeuvres.

What ‘good’ looks like on the coast

• Edge detection first, central fusion second

• A single evidence thread per contact (sensor hits, imagery, RF)

• Confidence scores exposed to operators (and patrol apps)

• Incident learning loops that retrain models on local edge cases

• Cyber hygiene for every mast and box on the pier

Drone-based threat detection: eyes above, minds at the edge

Drones have rewritten both sides of maritime security. On defence, they offer rapid, flexible ISR at a fraction of helicopter cost. On offence, low-cost quadcopters and fixed-wings can stalk perimeters, seed distractions or conduct intelligence gathering. AI determines who wins the exchange.

Defender playbook:

• Autonomous patrols with event-driven focus. Drones fly pre-planned routes, but AI re-tasks them on triggers—anomalous wake from a small craft, a silent AIS gap, or acoustic signatures of outboards near a restricted area.

• On-board perception. Edge models detect hulls, lifejackets, weapons postures and even tell-tale behaviours (rapid loading/unloading at odd hours), sending back metadata not raw video. This protects bandwidth and privacy while accelerating review.

• Counter-UAS fusion. Defenders catalogue RF fingerprints, radar micro-Doppler and EO signatures of hostile drones. AI fuses these to classify make, model and likely intent, then cues soft-kill or intercept measures per rules of engagement.

DJI dominates commercial drones used in non-lethal, civilian surveillance—shoreline patrols, search and rescue, disaster assessment and environmental monitoring. Many agencies across Asia exploit AI-assisted waypointing, object detection and gimbal tracking to cover beaches, estuaries and breakwaters efficiently, while complying with local law and oversight.

QinetiQ-style counter-UAS integration (relevant though UK-based) has informed regional deployments: multi-sensor towers that cross-cue radar, RF and EO/IR so operators receive one alert with a likelihood score and a recommended action, not three discordant feeds. Asian agencies are adopting similar open architectures to avoid lock-in and to keep up with rapidly evolving commercial drone ecosystems.

Hanwha Systems and ST Engineering are active in drone detection and airfield/harbour airspace management, applying AI to distinguish birds from micro-UAVs and to predict flight paths in wind shear and urban canyons—crucial for safe intercept.

Operational takeaways

• Treat drones as consumable surveillance, not crown jewels

• Push analytics into the airframe; stream events, not video

• Maintain a “threat library” for hostile UAS that updates weekly

• Drill joint responses: harbour police, port authority, coast guard, air defence

AI-enabled border monitoring: land, sea and the seams between

Borders in Asia are often amphibious. Rivers turn into marsh, coastline fades into city, and trade routes slip into backroads. AI helps agencies watch the seams—where smugglers and infiltrators exploit jurisdictional hand-offs.

How it works:

• Smart corridors. Road checkpoints, rail nodes and ferry terminals share a common risk picture. If a suspicious boat drops off the radar at a creek, roadside ANPR (automatic number plate recognition) and bridge cameras in that sector receive a temporary risk boost, raising sensitivity thresholds for specific vehicle classes or behaviours.

• Identity and movement analytics. Biometrics, travel records and watch-lists are fused with privacy controls and audit, enabling faster, fairer triage. Edge devices handle liveness checks and document verification, while central services run pattern-of-life models to flag organised smuggling networks.

• Riverine and green-border sensing. Low-power thermal cameras, seismic sensors and passive RF nodes form mesh networks that self-heal. AI sifts animal movement from human teams and correlates detections with terrain and weather.

NEC sits at the intersection of public safety AI, biometrics and command solutions. Its strengths in face and iris recognition, re-identification and crowd analytics are being applied to border e-gates, ferry terminals and city-to-port flows, with explainability and consent mechanisms suited to Japan’s standards—attributes increasingly mirrored across the region.

BEL contributes C4I (command, control, communications, computers and intelligence) tailored to large, federal systems: maritime police, customs, fisheries, coast guard. Its platforms prioritise sovereign data control, on-prem compute and air-gapped resilience where cloud is constrained.

ST Engineering builds whole-of-node security: smart fences, turnstiles, camera stacks and vehicle barriers instrumented with analytics that feed into urban operations centres. The philosophy is pragmatic—reduce operator clicks, raise throughput, keep audit trails clean.

The architecture that makes it work

Technology lists can seduce; architecture wins wars. The Asian programmes that scale share five design habits:

1. Edge-first, cloud-smart. Push inference to sensors; use central resources for model training, long-horizon analytics and cross-jurisdiction fusion. This keeps sites operational even with contested links.

2. One ontology across missions. A speedboat is the same object whether seen by radar, thermal or drone. A shared schema prevents “multiple truths” and accelerates AI retraining.

3. ML Ops for security. Treat models like software: version them, monitor drift, roll back safely, red-team regularly. Build data pipelines as first-class infrastructure.

4. Explainability in the loop. Show operators why the system is confident. Expose features (wake pattern, course change, RF signature) and let humans challenge or confirm. This builds trust and improves training data.

5. Zero-trust by default. Every camera, radar and drone is an IT asset. Use strong identity, encryption, segmentation and continuous monitoring. Here Rohde & Schwarz Cybersecurity is a regional reference for crypto-agile gateways and high-assurance networks that allow agencies to share insight without leaking data.

Governance and public trust: capability with consent

Asia’s security remit intersects with dense cities, tourism and trade. The social licence to operate matters.

• Purpose limitation. Use cases are narrowly scoped; reuse requires explicit approval.

• Data minimisation. Share metadata where possible; retain video only when necessary.

• Bias and fairness checks. Validate models across ethnicities, dress, vessel types and languages.

• Independent oversight. Logs and model cards enable audits; red teams probe for drift and blind spots.

• Human primacy. Systems recommend; humans decide—especially where force or liberty is at stake.

These are not just ethical preferences; they are operational enablers. Transparent systems onboard faster, survive legal challenge and integrate more readily with partners.

Company snapshots: strengths at a glance

• Bharat Electronics Limited (India): Large-scale coastal surveillance, optronics + radar integration, C4I with sovereign control. Strong in harsh-environment edge nodes and federated command centres serving multi-agency missions.

• ST Engineering (Singapore): Port and airport security, counter-UAS integration, open architectures. Strong in modular rollouts and lifecycle hardening for tropical maritime conditions.

• Hanwha Systems (South Korea): AI-enhanced sensors for air and maritime domains; tracking continuity in clutter; integration with air and naval C2 for rapid cue-to-intercept.

• NEC (Japan): Biometrics, re-ID and public safety AI with explainability and privacy constructs; city-to-border orchestration and command solutions for complex urban-maritime seams.

• Rohde & Schwarz Cybersecurity (Germany, active in Asia): High-assurance crypto, gateways and monitoring for mission networks carrying AI signals across sensitive boundaries.

• DJI (China, non-lethal applications): Search-and-rescue, shoreline patrol and inspection drones with AI-assisted flight and object detection; widely used by civil agencies under local law and oversight.

Twelve-month roadmap for agencies

Quarter 1: Frame and instrument

• Pick two pain points (e.g., false alarms on small craft; drone incursions at port perimeters).

• Inventory sensors and data contracts; fix time sync and metadata.

• Stand up a pilot fusion node with role-based access and audit.

Quarter 2: Prove and harden

• Deploy edge models to two coastal towers and one drone fleet; stream events, not video.

• Integrate a counter-UAS stack with RF, radar and EO; run red-team drills.

• Implement zero-trust controls (identity, segmentation, encrypted telemetry).

Quarter 3: Scale and train

• Expand to a corridor (harbour + approaches + hinterland checkpoints).

• Embed operator feedback loops; publish model cards; monitor drift dashboards.

• Establish cross-agency playbooks for cue-to-intercept and incident response.

Quarter 4: Interoperate and audit

• Stand up a federated data exchange with a trusted neighbour (state or national).

• Conduct an independent ethics and security review; tune retention and oversight.

• Move from project to platform funding, with KPIs on detection quality, response time and queue time.

The Asian edge: agility, pragmatism, partnership

Asia’s security innovators are not chasing abstract perfection; they’re building durable, fieldable systems that withstand heat, salt and human complexity. BEL’s sovereign C4I ethos, ST Engineering’s modularity, Hanwha’s tracking continuity, NEC’s explainable identity stack, Rohde & Schwarz’s secure plumbing, and DJI’s accessible aerial workhorses together sketch a practical pathway: start at the edge, fuse what you have, harden the pipes, keep people in charge.

Done right, AI will not turn coastlines into cordons or borders into barriers. It will make them smarter, calmer and more humane—less guesswork at checkpoints, fewer dangerous chases at sea, faster rescue when storms hit, and better protection for the commerce that keeps Asia thriving.

The mandate is clear: solve the operational pain, scale what works, measure relentlessly, govern with care. In maritime and homeland security, that is how AI moves from demo to doctrine—and how Asia keeps its waters open, its borders secure, and its people safe.