shuishen
4 hours ago 2ae460fc4a4c2419cf44329783d49a739e2a04ea
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{
  "source_document": "reference_article/瑶岗仙二期项目算法需求与GeoAI能力匹配分析报告.docx",
  "source_item_count": 8,
  "normalized_solution_domain_count": 7,
  "normalization_notes": [
    "排洪沟巡查与排洪沟堵塞识别合并为同一方案域,避免重复模型、标注和规则。",
    "A/B/C 表示实现边界,不表示项目优先级或成熟度。",
    "模型观察、空间计算、事件规则和平台动作必须分别记录。"
  ],
  "solution_domains": [
    {
      "id": "person-safety",
      "name": "人员与个体防护识别",
      "source_items": ["人员安全识别"],
      "priority": "P1",
      "readiness": "partial",
      "sensor": ["RGB"],
      "capability_references": ["01-object-detection", "03-attribute-classification", "06-spatial-reasoning", "07-risk-rule-engine"],
      "model_observations": ["person", "helmet"],
      "event_candidates": ["suspected_missing_helmet", "suspected_restricted_area_entry"],
      "blocking_conditions": ["缺少安全帽正负样本", "缺少人员与安全帽关联真值", "缺少危险区域和事件阈值"]
    },
    {
      "id": "blast-zone-thermal-guard",
      "name": "爆破警戒热成像巡查",
      "source_items": ["爆破警戒热成像巡查"],
      "priority": "P1-conditional",
      "readiness": "blocked_by_data",
      "sensor": ["thermal", "optional RGB"],
      "capability_references": ["01-object-detection", "06-spatial-reasoning", "07-risk-rule-engine"],
      "model_observations": ["thermal_person_candidate"],
      "event_candidates": ["suspected_person_in_blast_zone"],
      "blocking_conditions": ["缺少原始热成像样本", "缺少热成像人员标注", "缺少警戒区定义", "缺少允许漏报和误报边界"]
    },
    {
      "id": "drainage-blockage",
      "name": "排洪沟与箱涵堵塞巡查",
      "source_items": ["排洪沟巡查", "排洪沟堵塞识别"],
      "priority": "P1",
      "readiness": "partial",
      "sensor": ["RGB", "preferred georeferenced orthomosaic"],
      "capability_references": ["02-semantic-mapping", "01-object-detection", "00-change-detection", "04-spatial-measurement", "07-risk-rule-engine"],
      "model_observations": ["drainage_channel", "culvert_inlet", "blockage_material", "blockage_mask"],
      "event_candidates": ["suspected_drainage_blockage"],
      "blocking_conditions": ["缺少沟道和箱涵边界", "缺少堵塞掩膜和严重度样本", "缺少覆盖比例或面积阈值"]
    },
    {
      "id": "slope-monitoring",
      "name": "边坡变化与形变监测",
      "source_items": ["边坡监测"],
      "priority": "P2",
      "readiness": "needs_requirement_correction",
      "sensor": ["registered orthomosaic", "DSM or point cloud"],
      "capability_references": ["00-change-detection", "05-3d-pointcloud", "04-spatial-measurement", "09-anomaly-detection"],
      "model_observations": ["surface_change", "collapse_candidate", "crack_region", "displacement_measurement"],
      "event_candidates": ["suspected_slope_change"],
      "blocking_conditions": ["需求描述疑似复制错误", "缺少同尺度配准多期数据", "缺少工程测量精度和告警阈值"]
    },
    {
      "id": "shaft-inspection",
      "name": "竖井堵塞与设施损坏巡查",
      "source_items": ["竖井堵塞及损坏识别"],
      "priority": "P2",
      "readiness": "blocked_by_scope",
      "sensor": ["close-range RGB", "optional 3D"],
      "capability_references": ["01-object-detection", "02-semantic-mapping", "09-anomaly-detection", "04-spatial-measurement", "05-3d-pointcloud"],
      "model_observations": ["blockage", "damaged_guard", "damaged_walkway", "structural_anomaly"],
      "event_candidates": ["suspected_shaft_blockage", "suspected_shaft_damage"],
      "blocking_conditions": ["检测部位未界定", "损坏定义未确定", "缺少近景正常和异常样本"]
    },
    {
      "id": "cableway-inspection",
      "name": "索道部件与外观缺陷巡查",
      "source_items": ["索道安全感知"],
      "priority": "P3",
      "readiness": "blocked_by_capture_method",
      "sensor": ["close-range RGB", "optional 3D"],
      "capability_references": ["01-object-detection", "02-semantic-mapping", "09-anomaly-detection", "04-spatial-measurement", "05-3d-pointcloud", "13-asset-health-diagnosis"],
      "model_observations": ["bucket", "clamp", "tower_component", "visible_defect"],
      "event_candidates": ["suspected_cableway_defect"],
      "blocking_conditions": ["检测对象未确定", "常规全景不能支持断丝识别", "缺少近景航线和异常样本"]
    },
    {
      "id": "tailings-leakage",
      "name": "尾矿库矿浆渗漏与水体异常筛查",
      "source_items": ["尾矿库矿浆渗漏识别"],
      "priority": "P3",
      "readiness": "blocked_by_evidence",
      "sensor": ["multispectral", "thermal", "fixed-view RGB for comparison only"],
      "capability_references": ["02-semantic-mapping", "03-attribute-classification", "00-change-detection", "09-anomaly-detection", "08-spatiotemporal-forecasting"],
      "model_observations": ["water_or_slurry_region", "color_or_spectral_anomaly", "temporal_change"],
      "event_candidates": ["suspected_tailings_leakage"],
      "blocking_conditions": ["缺少真实渗漏样本", "传感器条件未确认", "RGB 浑浊不能直接证明矿浆渗漏", "缺少现场复核标签"]
    }
  ]
}