Coastal environment
People, waves, tides, weather, water conditions, and rescue coverage
ShoreSense
Menu
One system from shoreline sensing to coordinated response.
ShoreSense is a camera-and-sensor-agnostic architecture that combines physical coastal infrastructure with edge computer vision, environmental forecasting, a littoral digital twin, and human-reviewed rescue coordination.
The complete response loop.
The system is built to preserve context as data moves from the coast to a decision. Each stage adds a different form of understanding.
Sensing hardware
Distributed cameras, environmental nodes, connected coastal feeds, and responder locations
Edge intelligence
Person detection, tracking, optical flow, hazard segmentation, and privacy-aware local processing
Littoral digital twin
Adaptive shoreline cells connect people, sensors, hazards, and rescue assets
Prediction
Localized risk and uncertainty are estimated now and across 5, 15, and 30 minute horizons
Coordination
Warnings, patrol positioning, rescue staging, routing, and human-reviewed decisions
Hardware designed around the shoreline, not one equipment vendor.
The prototype accepts visual, environmental, and operational inputs through a flexible sensing layer. Local processing keeps the system responsive even when connectivity is limited.
Coastal sensing
Distributed shoreline cameras, environmental sensor nodes, wave and tide inputs, weather and water-condition feeds, and responder locations create the physical picture of the site.
Beach-side computing
A local edge gateway synchronizes observations and runs safety-relevant visual analysis close to the source. Event metadata can move upstream without continuously transmitting full video.
Connected operations
The same architecture can incorporate existing public data feeds, beach-specific sensor networks, and the positions of lifeguards, rescue boards, watercraft, and other response assets.
Computer vision follows motion over time.
Potential distress cannot be understood from a single frame. ShoreSense links detections across time, analyzes movement, and evaluates them alongside changing water conditions.
Video
Camera streams enter the local processing gateway.
People
Detection and multi-object tracking maintain continuous swimmer trajectories.
Movement
Pose, direction, offshore drift, submergence, and purposeful motion are analyzed over time.
Water
Optical flow and segmentation estimate hazardous current structure and surf-zone change.
Context
Visual outputs are fused with tide, waves, shoreline geometry, visibility, and uncertainty.
A living model of the shoreline.
The littoral digital twin represents the coast as adaptive georeferenced cells. Tracked people, sensor nodes, hazards, and rescue assets become connected parts of one changing model.
- Hydrodynamic relationships
- How conditions can move between neighboring shoreline cells.
- Visibility relationships
- What each camera and observer can reliably see.
- Human-motion relationships
- How tracked people are moving through the surf zone.
- Travel-time relationships
- How quickly rescue assets can reach changing areas of risk.
Risk is mapped across place and time.
Every update produces localized estimates instead of one beach-wide label. The forecasting layer projects how conditions may evolve and keeps uncertainty visible to the operator.
NowObserved and inferred state
5 minImmediate movement
15 minDeveloping exposure
30 minOperational planning
From observation to response.
An end-to-end prototype demonstration moves through one continuous sequence.
Data enters the system.
Camera streams, environmental observations, public coastal feeds, and responder locations are synchronized and georeferenced.
People and conditions are detected.
Edge models track swimmers, analyze temporal behavior, estimate optical flow, and identify changing hazard structure.
The digital twin updates.
Localized cells connect physical conditions with people, sensors, visibility, rescue coverage, and uncertainty.
Risk is forecast.
The fusion layer estimates how hazards and exposure may evolve across immediate and future horizons.
Response options are prioritized.
ShoreSense recommends warnings, patrol positioning, rescue staging, and asset routing for trained human review.
Patent-pending architecture.
U.S. Patent Application No. 64/117,500 covers the integrated system architecture, including multimodal sensing, adaptive shoreline cells, temporal risk modeling, and rescue-resource orchestration.
Up to 98%
person-in-water detection accuracy across controlled prototype evaluations
Tested across complementary environments.
Evaluation has combined recorded coastal footage, public datasets, field data, and simulated hazard, distress, and rescue-coordination scenarios.
See the scientific foundationSee the research behind the system.
The environmental-intelligence layer grew from work on offshore wave spectra and coastal water-level oscillations.
Explore the research