Ocean Mode in Expert RAW App Empowers Nonprofits to Monitor Coral Reefs with Advanced Underwater Imaging for Galaxy Phones

Samsung Galaxy Ocean Mode: Coral Reef Monitoring Through NPU-Accelerated Underwater Imaging

Samsung’s Ocean Mode, embedded within the Expert RAW application for Galaxy S24 Ultra and newer devices, has received the 2026 International Coral Reef Initiative Innovation Award for enabling low-light, high-dynamic-range underwater imaging critical to marine conservation workflows. The feature leverages the device’s Neural Processing Unit (NPU) to perform real-time spectral correction and noise reduction in submerged environments where traditional smartphone cameras fail due to wavelength attenuation and particulate scattering. While marketed as a consumer photography mode, its adoption by NGOs like Reef Check and the Coral Restoration Foundation reveals a deeper utility: transforming flagship smartphones into calibrated, geotagged data collection tools for benthic habitat assessment. This isn’t merely computational photography—it’s edge AI deployed at the intersection of consumer hardware and environmental telemetry, raising questions about sensor fidelity, data integrity, and the feasibility of using unregulated mobile devices in scientific monitoring protocols.

The Tech TL. DR:

• Ocean Mode uses the Galaxy S24 Ultra’s Qualcomm Hexagon NPU to achieve 12ms end-to-end latency in underwater RAW processing, outperforming dedicated underwater housings with legacy DSPs by 40% in turbid conditions.
• Generated DNG files include embedded GPS, depth (via barometric sensor fusion), and spectral calibration metadata, enabling direct ingestion into QGIS and ReefCloud analytics pipelines.
• Despite its utility, Ocean Mode lacks ISO 19115-1 geographic metadata certification, creating interoperability gaps for formal marine spatial data infrastructures requiring FGDC compliance.

The core technical innovation lies in how Ocean Mode repurposes the ISP-NPU pipeline typically reserved for portrait mode and nightography. Instead of relying solely on multi-frame stacking, the system employs a lightweight CNN trained on synthetic underwater imagery datasets (generated via BlenderProc and POSBench) to estimate and compensate for water column absorption coefficients in real time. Benchmarks reveal the NPU achieves 3.2 TOPS sustained during Ocean Mode operation, maintaining 30fps at 12MP RAW output while consuming 1.8W—significantly below the 4.5W thermal throttle threshold of the Snapdragon 8 Gen 3 under sustained load. This efficiency allows extended deployment in field conditions where external power is unavailable, a critical advantage over action cameras like the GoPro Hero12 Black, which draws 3.3W under similar 4K underwater video encoding.

“We’ve validated Ocean Mode’s color accuracy against a Spectralon reference panel in controlled tank tests—Delta-E 2000 values average 3.8 across 400-700nm, which is acceptable for qualitative reef health scoring but falls short of the < 2.0 threshold required for quantitative pigment quantification."

From an IT triage perspective, organizations deploying Ocean Mode at scale face a data governance challenge: the Expert RAW app stores geotagged DNG files in encrypted sandboxed storage by default, but exporting to external SD cards or cloud services triggers Android’s scoped storage restrictions, requiring explicit user consent per file transfer. For NGOs managing hundreds of daily surveys across distributed volunteer teams, this creates friction in data aggregation pipelines. Here, managed service providers specializing in mobile workflow automation—such as those listed under mobile device management consultants—can deploy Samsung Knox Configure profiles to pre-approve export permissions and enforce centralized DNG ingestion into secure object storage buckets via MDM-triggered Intune workflows.

the absence of real-time hash chaining or blockchain-based audit trails in the current Ocean Mode implementation raises concerns about data provenance in legal or regulatory contexts. While Samsung signs each DNG with a device-unique RSA-2048 key stored in the Trusted Execution Environment (TEE), the signature verifies authenticity but not temporal integrity—leaving room for replay attacks if files are copied and re-imported. Cybersecurity auditors familiar with mobile forensic chains of custody, accessible via digital forensics specialists, recommend supplementing Ocean Mode with third-party apps like ProofMode that append SHA-3-256 hashes and GPS timestamps to a distributed ledger before export.

Technical Implementation: Accessing Ocean Mode Metadata via Android Jetpack CameraX

Developers seeking to integrate Ocean Mode outputs into custom marine data pipelines can leverage the CameraX UseCase API to extract embedded sensor fusion data. The following Kotlin snippet demonstrates how to access depth and spectral calibration tags from Ocean Mode DNG files using the androidx.camera.core.ImageProxy interface:

// Requires CameraX 1.3.0+ and Android 14 (API 34) val imageAnalyzer = ImageAnalysis.Builder() .setTargetResolution(Size(4000, 3000)) .setBackpressureStrategy(ImageAnalysis.STRATEGY_KEEP_ONLY_LATEST) .build() .also { it.setAnalyzer(ContextCompat.getMainExecutor(this)) { imageProxy -> val metadata = imageProxy.imageInfo val depthMeters = metadata.getLong(Characteristics.LENS_FOCUS_DISTANCE) ?: 0L val spectralGain = metadata.getRationalArray(Characteristics.SENSOR_CALIBRATION_TRANSFORM1) // Process DNG bytes via LibRaw or OpenCV for underwater correction imageProxy.close() }} // To initiate Ocean Mode explicitly (requires Expert RAW v2.1+): val intent = Intent("com.samsung.android.camera.expertraw.ACTION_OCEAN_MODE") intent.putExtra("com.samsung.extra.OUTPUT_FORMAT", ImageFormat.RAW_SENSOR) startActivityForResult(intent, REQUEST_OCEAN_MODE) 

This level of access confirms Ocean Mode is not a opaque firmware blob but a configurable ISP pipeline exposed through standard Android camera HAL interfaces—though Samsung restricts the “Ocean Mode” trigger string to its first-party Expert RAW app, preventing third-party camera applications from activating the underwater spectral correction model without privileged OEM signatures.

The broader implication is clear: consumer-grade AI accelerators are closing the gap with industrial sensing platforms, but without standardized metadata schemas and audit trails, their scientific utility remains provisional. As environmental monitoring shifts toward decentralized, smartphone-based observatories, the burden falls on device makers to align with GEOSS principles—or on integrators to bridge the gap via middleware. For now, Ocean Mode represents a compelling proof of concept, but its transition from award-winning feature to trusted scientific instrument requires more than NPU horsepower—it demands adherence to the FAIR data principles that underpin modern cyberinfrastructure.

Disclaimer: The technical analyses and security protocols detailed in this article are for informational purposes only. Always consult with certified IT and cybersecurity professionals before altering enterprise networks or handling sensitive data.