htlee
7573c84e91
- MIN_TRAJ_POINTS 100→20 (16척→684척, 파이프라인 병목 해소) - risk.py: SOG 급변 count를 위험도 점수에 반영 (+5/+10) - spoofing.py: BD09 오프셋 중국 MMSI(412*) 예외 (좌표계 노이즈 제거) - fishing_pattern.py: 마지막 조업 세그먼트 누락 버그 수정 - VesselAnalysisService: 인메모리 캐시 + 증분 갱신 (warmup 2h → incremental) - nginx: /api/gtts 프록시 추가 (Google TTS CORS 우회) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
87 lines
2.2 KiB
Python
87 lines
2.2 KiB
Python
from typing import Optional, Tuple
|
|
|
|
import pandas as pd
|
|
from algorithms.location import classify_zone
|
|
from algorithms.fishing_pattern import detect_fishing_segments, detect_trawl_uturn
|
|
from algorithms.dark_vessel import detect_ais_gaps
|
|
from algorithms.spoofing import detect_teleportation
|
|
|
|
|
|
def compute_vessel_risk_score(
|
|
mmsi: str,
|
|
df_vessel: pd.DataFrame,
|
|
zone_info: Optional[dict] = None,
|
|
is_permitted: Optional[bool] = None,
|
|
) -> Tuple[int, str]:
|
|
"""선박별 종합 위반 위험도 (0~100점).
|
|
|
|
Returns: (risk_score, risk_level)
|
|
"""
|
|
if len(df_vessel) == 0:
|
|
return 0, 'LOW'
|
|
|
|
score = 0
|
|
|
|
# 1. 위치 기반 (최대 40점)
|
|
if zone_info is None:
|
|
last = df_vessel.iloc[-1]
|
|
zone_info = classify_zone(last['lat'], last['lon'])
|
|
|
|
zone = zone_info.get('zone', '')
|
|
if zone == 'TERRITORIAL_SEA':
|
|
score += 40
|
|
elif zone == 'CONTIGUOUS_ZONE':
|
|
score += 10
|
|
elif zone.startswith('ZONE_'):
|
|
# 특정어업수역 내 — 무허가면 가산
|
|
if is_permitted is not None and not is_permitted:
|
|
score += 25
|
|
|
|
# 2. 조업 행위 (최대 30점)
|
|
segs = detect_fishing_segments(df_vessel)
|
|
ts_fishing = [s for s in segs if s.get('in_territorial_sea')]
|
|
if ts_fishing:
|
|
score += 20
|
|
elif segs:
|
|
score += 5
|
|
|
|
uturn = detect_trawl_uturn(df_vessel)
|
|
if uturn.get('trawl_suspected'):
|
|
score += 10
|
|
|
|
# 3. AIS 조작 (최대 35점)
|
|
teleports = detect_teleportation(df_vessel)
|
|
if teleports:
|
|
score += 20
|
|
|
|
from algorithms.spoofing import count_speed_jumps
|
|
jumps = count_speed_jumps(df_vessel)
|
|
if jumps >= 3:
|
|
score += 10
|
|
elif jumps >= 1:
|
|
score += 5
|
|
|
|
gaps = detect_ais_gaps(df_vessel)
|
|
critical_gaps = [g for g in gaps if g['gap_min'] >= 60]
|
|
if critical_gaps:
|
|
score += 15
|
|
elif gaps:
|
|
score += 5
|
|
|
|
# 4. 허가 이력 (최대 20점)
|
|
if is_permitted is not None and not is_permitted:
|
|
score += 20
|
|
|
|
score = min(score, 100)
|
|
|
|
if score >= 70:
|
|
level = 'CRITICAL'
|
|
elif score >= 50:
|
|
level = 'HIGH'
|
|
elif score >= 30:
|
|
level = 'MEDIUM'
|
|
else:
|
|
level = 'LOW'
|
|
|
|
return score, level
|