Today, Karst Firewall 5.0 is a cross-border wildfire twin. This is where we want to take it next: a living, multi-hazard decision platform that learns, sips energy, scales from the Karst to the whole Mediterranean, and gives insurers, infrastructure operators and planners modular tools to build on. A roadmap, openly shared.
Four shifts shape everything below: from a single hazard (fire) to many; from static maps to living data that updates itself; from a finished tool to a modular platform others can build on; and from one plateau to a sea. None of this is live yet — it is the direction we are taking the twin, openly and with our partners.
Shovel-ready: the satellite NDVI / vegetation-health pipeline already feeds the platform. Turning it into a live “how dry is the fuel today” layer sharpens every fire forecast for the least new effort — the clearest win.
The fastest way to become multi-hazard: the cross-border weather network and 3D terrain we already run are most of what flood and heat-wave mapping needs. Two hazards that touch every citizen — not only fire crews.
Mostly data and compute, little new science. Covering the whole region multiplies the platform’s reach and value before the harder leap to the wider Mediterranean.
Everything else below — compound multi-risk, agentic & frugal AI, the modular decision-support platform, the Mediterranean twin — builds on these three foundations.
The Karst does not face only wildfire. The same living twin — terrain, weather, exposure — can read flood, heat, slope and seismic risk, and, crucially, where they overlap on the same people and assets.
Pluvial and flash-flood exposure from rainfall, terrain hydrology and the karstic underground drainage — where water gathers fast on the limestone, and which roads, homes and assets sit in its path.
Impact: High · reuses the weather network + 3D terrainHeat-wave and urban-heat exposure from the station network and land cover — a public-health early warning for the most vulnerable people and places, and a fuel-drying signal that feeds the fire model too.
Impact: High · directly serves citizens & health servicesLandslide susceptibility from slope, soil and rainfall — sharpened after fires, when burnt ground sheds water and the risk of debris flows climbs. A natural pairing with the post-fire recovery view.
Impact: Medium · compounds with wildfire & floodOverlay seismic hazard and cross-correlate the layers into one compound-risk index: where do wildfire, flood, heat and earthquake stack on the same zone? Compound exposure, not four maps read in isolation, is what planning and insurance really need.
Impact: High · the multi-hazard payoffStatic fuel maps go stale the moment they are drawn. Reading vegetation from space, continuously, makes the twin’s fuel “alive” — and a living fuel layer is the single biggest accuracy gain available to the fire model.
Turn the satellite “greenness” (NDVI) signal into a live fuel-moisture and fuel-state layer, so the fuel the simulator burns is today’s fuel — green and damp, or cured and flammable — not last season’s static map.
Impact: High · the NDVI pipeline already existsBurn scars, drought stress, harvests and regrowth update the fuel map automatically from each new satellite pass — and flag stressed, fire-prone vegetation weeks ahead, turning the twin into an early-warning instrument for the land itself.
Impact: Medium · keeps every hazard model honestThe platform should get better on its own, and do so frugally. More capable does not have to mean more power-hungry: the goal is intelligence that learns from every fire, always under human oversight, while using less energy each year.
Software agents that watch the live data, draft the morning risk briefing, surface anomalies and propose interventions — always presented for a human to approve, never acting unsupervised.
Impact: High · saves operators time dailySmaller, distilled models and inference at the edge — closer to the sensors — for lower energy, lower cost and resilience when connectivity drops. Sustainability built into the AI itself, not just the forest.
Impact: High · cuts running cost & carbonClose the loop: the platform calibrates itself against what really happened — every fire it predicted well or badly becomes training signal — so accuracy improves over time without a manual rebuild.
Impact: High · but needs careful governanceThe real prize is a modular platform — composable building blocks that let a twin or a decision-support tool be assembled for a new territory, a new hazard or a new audience, instead of rebuilt from scratch each time.
Reusable bricks — a hazard model, a data feed, a map layer, a report — that snap together. Stand up a new digital twin by composing parts that are already tested, not by writing it all again.
Impact: High · multiplies everything elseA decision-support tool (DST) tuned for insurers (risk pricing & portfolio exposure), infrastructure operators (network resilience) and spatial & urban planners (risk-aware planning) — new audiences for the same evidence base.
Impact: High · opens a sustainable business modelOpen APIs and connectors so the twin talks to GIS, emergency-management, environmental and IoT systems — one holistic cockpit for managing territorial sustainability, rather than another silo.
Impact: Medium · the glue for an ecosystemAim beyond resisting hazard toward restoring it: nature-based, net-positive interventions that leave ecosystems and communities stronger than before. The twin becomes a design tool for regeneration, not only defence.
Impact: Strategic · the long-term ethosThe cross-border Karst is the proving ground. The same engine can grow outward in deliberate steps — each one mostly data and compute, the science already in place.
Extend from the Karst AOI to the whole region — the natural next catchment, with data partners already in place.
A truly national, cross-border twin — completing the picture for the whole Slovenian side, not just the border strip.
The climate-and-fire frontline. A shared twin for a shared sea — the ambition that gives every brick above its full meaning.
The same initiatives, sequenced by impact and readiness. This is our honest view of the order — not a contract, but where the leverage is.