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Wildfire Response

Multi-agent coordination for detection, evacuation routing, and resource deployment.
๐Ÿ”ฅ spread: 0/step ๐Ÿƒโ€โ™‚๏ธ evacuation: 0% ๐Ÿ“‹ blackboard: 0 ๐Ÿš UAV: 0 active ๐Ÿค– robots: 0 deployed
๐ŸŽฏ Goals ยท Roles ยท I/O

Goals

  • ๐Ÿƒโ€โ™‚๏ธ Evacuation efficiency (evacuated / total)
  • ๐Ÿ”ฅ Spread rate (new burning cells / step)

Roles & Agents

  • ๐Ÿš UAV: emit fire spread data/images
  • ๐Ÿค– Ground robots: route evac paths; blackboard share
  • ๐Ÿง‘โ€๐Ÿ’ผ Dispatcher: spawn evacuation tasks
  • ๐Ÿƒโ€โ™‚๏ธ Evacuees: follow guidance to safe zones

Inputs / Outputs / Ops

  • Inputs: ๐Ÿ”ฅ spread ยท ๐Ÿ—บ๏ธ map ยท ๐Ÿ‘ฅ positions
  • Outputs: ๐Ÿšถโ€โ™€๏ธ routes ยท ๐Ÿ’ผ resource plan ยท ๐Ÿ“ feedback
  • Ops: emit โ†’ route โ†’ blackboard โ†’ spawn
Response Timeline
Agent Activity
DSL Showcase
// ATSLP: Assign detection, routing, evacuation tasks
schedule_tasks([
  detect_hotspots(area=A),
  plan_routes(evac_zone=Z1),
  deploy_resources(type=BULDOZER)
])

// HCMPL: Cache and reuse GIS layers
cache_store(key="risk_map@t", data=compute_risk_map(A))
risk_map = cache_get(key="risk_map@t")

// CALK: Share knowledge between agents
broadcast({ alert: "smoke_detected", location: L })
Fire Grid Map
step 0 ๐Ÿ”ฅ spread: 0/step Speed: 1x Time: 00:00
๐Ÿƒโ€โ™‚๏ธ evacuation: 0% ๐Ÿ“‹ blackboard: 0 items
Evacuation Planner
  • Routes will appear here based on the current risk grid.
CALK Visualization
Video Analysis (Beta)
Client-side motion; no upload.
Analysis Report

Load a video to see motion-based incident analytics here.

Multi-Agent Collaboration

Load a video to simulate masterโ€“sub agent coordination traces driven by detected events.

Performance Snapshot
  • Throughput: 2.4 tasks/s
  • Avg Latency: 0.78s
  • Success Rate: 100%
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