Roadside Wildlife Warning, built on proven architecture.
Wildlife-vehicle collisions are a road safety and conservation problem that static signage does not solve. We apply a sensor-fused, edge-first detection architecture, already proven in defence-engineering deployments, to detection, identification, monitoring and alerting.
- Detection
- Identification
- Monitoring
- Alerting
Four pillars, one architecture.
Four things the system does, all built on SENTIA, our decision-intelligence framework.
Detection
Multi-sensor fusion at the roadside: optical, thermal and audio, following the pattern proven in FABHUMS.
Identification
Species classification using the structured-intelligence pattern WISDOM applies to unstructured sensor inputs.
Monitoring
Every confirmed sighting adds to a heat map of where animals cross, following the usage-tracking pattern FABHUMS applies to vehicle crossings.
Alerting
Trigger logic and recommended action, following the pattern ENG|AIDE applies to engineering decisions, delivered over SWIFT.
How it works
Anywise uses sensors already on the road to warn drivers before they reach wildlife. The warning comes from the roadside, not the cloud. Scroll to follow one sighting.
Detection
Fixed and mobile sensors watch the road. Existing cameras run our software. Add-ons fill the gaps.
- Existing CCTV cameras
- Thermal add-on
- Low-cost AI camera
- PIR sensor
- Freight dash cam
Identification
AI on the roadside unit checks the species and filters false alarms. This happens on site. There is no continuous video.
- Roadside edge unit
- Vehicle edge app
Alerting
The roadside unit produces the alert locally and sends it straight away. Existing electronic signs light up, and drivers heading toward the animal get an alert in the car.
- Roadside edge unit
- Roadside electronic signs
- In-car alerts
Example alert.
Monitoring
Identification happens at the edge. The roadside unit then sends each identified sighting to the cloud. There, the platform builds a heat map of where animals cross. Later, it can help predict where and when they will cross.
- Cellular, satellite or LoRa mesh
- Roadside Wildlife Warning platform
- Heat map
- Future: prediction
Six stages, sensor to driver.
Roadside Wildlife Warning runs on SENTIA, our six-stage framework. Here is what each stage does on the road.
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Sense
Sensors spot animals near the road.
- Fixed: existing CCTV cameras, existing PIR motion sensors, and thermal add-ons fitted to existing poles. Thermal covers night and poor light.
- Mobile: dash cams on freight trucks, government vehicles and opt-in public cars. Each sighting gets a GPS location.
-
Enrich
AI confirms the sighting at the sensor, not in the cloud.
- At fixed sites, a roadside edge unit checks the image, identifies the species and uses more than one sensor to filter false alarms.
- In vehicles, an app on the dash cam or phone does the same and tags the GPS location.
- Only the alert, the location and a short clip are sent. No continuous video stream, so data and bandwidth stay low and privacy is protected.
-
Nexus
The roadside unit sends each confirmed sighting to the central platform. The platform joins fixed and mobile sightings into a live heat map by road section. Later, it can help predict where and when animals will cross.
-
Think
The roadside unit decides on the spot whether to raise an alert, so a warning never waits on the cloud. The platform sets the recommended speed for each road section.
-
Inform
The roadside unit sends the alert straight away. Alerts go to three places.
- In-car: a map alert in Apple CarPlay, Android Auto or Google Maps, for example “Kangaroo detected ahead. Slow down.”
- Roadside: existing electronic signs.
- Road authority: hotspot reports from the platform, for road planning.
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Assure
Every alert traces back to the sighting, sensor and clip behind it. Sighting history is kept for planning.
Why this design: it is software first. It uses the road authority’s existing cameras, signs and poles, so new hardware is needed only where there are gaps. Mobile sensors add coverage on roads with no fixed sites.
Sensor-agnostic by design.
No single sensor performs well in every condition. Sensor types are selected or fused per deployment. Try a condition below.
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Thermal / infrared
Night, dawn, dusk
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Vision / optical
Daylight classification
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PIR motion
Body heat and movement, day or night
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Audio
Vegetation movement, cover
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Particulate
Dust, fog density
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Environmental
Temperature, humidity
Coverage that grows without new hardware.
The classification layer can be retrained to extend species coverage over time, rather than requiring new sensing hardware. A narrow, single-species system cannot manage the risk a wider range of wildlife presents.
Each icon above is illustrative of an added class, not a published species list. The retraining method and timeframe for a given deployment is set once a target species list is agreed.
Where the technology actually stands today.
The underlying architecture and its sensing, classification, decision-support and communications components are proven and in active use today, in a defence-engineering domain. Applied to wildlife detection specifically, the work is at prototype and demonstration stage.
A field-tested communications approach and a successful detection test against a dog-size target class are on file for the wildlife-specific work. Quantitative range, accuracy, latency and false-positive figures are not yet published. This page states that plainly rather than estimating it.
Detection as a service.
Delivered as managing contractor: scalable, modular edge processing, with cloud as an option, and workshops included to transfer operating knowledge.
Discovery
Define a representative pilot scenario, site, species and scale, and begin field calibration of the Sense-stage module.
Detailed design and scoping
Run a trial producing detection-accuracy, false-positive and response-time evidence, with an independent validation method, and scope the uplift that follows.
Uplift
Extend species coverage, integrate audit-ready reporting as the deployment scales, and deliver workshops that transfer operating knowledge.
Got a corridor that needs watching?
Tell us about the corridor, the conditions and the outcome you need. We'll scope what is available now, what could be delivered, and what it would take.