feat(aiot): 离岗检测重写 - 单次告警 + 回岗确认 + 持续时长追踪

算法逻辑修改：
- OFF_DUTY状态只告警一次，不再每600秒重复告警
- 人员回岗后需经CONFIRMING(10秒)重新确认才恢复ON_DUTY
- 确认在岗后清除冷却记录，允许新一轮离岗检测
- 非工作时间进入时清除冷却记录

持续时长追踪（新增resolve机制）：
- 离岗告警记录alarm_id和leave_start_time
- 人员回岗确认后生成resolve事件(duration_ms + last_frame_time)
- 进入非工作时间时也生成resolve事件
- ResultReporter新增report_alarm_resolve()写入Redis队列
- AlarmUploadWorker新增_process_resolve() HTTP POST到云端
- main.py区分普通告警和resolve事件，回填alarm_id到算法实例
- 告警ext_data附加first_frame_time(离岗开始时间)

main.py

@@ -514,6 +514,23 @@ class EdgeInferenceService:
             for alert in alerts:
                 alert_type = alert.get("alert_type", "detection")
 
+                # resolve 事件：更新已有告警，不创建新告警
+                if alert_type == "alarm_resolve":
+                    resolve_data = {
+                        "alarm_id": alert.get("resolve_alarm_id"),
+                        "duration_ms": alert.get("duration_ms"),
+                        "last_frame_time": alert.get("last_frame_time"),
+                        "resolve_type": alert.get("resolve_type"),
+                    }
+                    if self._reporter:
+                        self._reporter.report_alarm_resolve(resolve_data)
+                    self._logger.info(
+                        f"离岗告警结束: alarm_id={resolve_data['alarm_id']}, "
+                        f"duration_ms={resolve_data['duration_ms']}, "
+                        f"reason={resolve_data['resolve_type']}"
+                    )
+                    continue
+
                 # 摄像头级别去重：同一摄像头+告警类型在冷却期内只上报一次
                 dedup_key = f"{camera_id}_{alert_type}"
                 now = frame.timestamp
@@ -530,6 +547,13 @@ class EdgeInferenceService:
                 self._camera_alert_cooldown[dedup_key] = now
                 self._performance_stats["total_alerts_generated"] += 1
 
+                # 获取算法的离岗开始时间
+                leave_start_time = None
+                if alert_type == "leave_post":
+                    algo = self._algorithm_manager.algorithms.get(roi_id, {}).get(f"{roi_id}_{bind.bind_id}", {}).get("leave_post")
+                    if algo and hasattr(algo, '_leave_start_time') and algo._leave_start_time:
+                        leave_start_time = algo._leave_start_time.isoformat()
+
                 from core.result_reporter import AlarmInfo, generate_alarm_id
                 alarm_info = AlarmInfo(
                     alarm_id=generate_alarm_id(self._settings.mqtt.device_id),
@@ -548,10 +572,17 @@ class EdgeInferenceService:
                         "bind_id": bind.bind_id,
                         "message": alert.get("message", ""),
                         "edge_node_id": self._settings.mqtt.device_id,
+                        "first_frame_time": leave_start_time,
                     },
                 )
                 self._reporter.report_alarm(alarm_info, screenshot=frame.image)
 
+                # 回填 alarm_id 到算法实例（用于后续 resolve 追踪）
+                if alert_type == "leave_post":
+                    algo = self._algorithm_manager.algorithms.get(roi_id, {}).get(f"{roi_id}_{bind.bind_id}", {}).get("leave_post")
+                    if algo and hasattr(algo, 'set_last_alarm_id'):
+                        algo.set_last_alarm_id(alarm_info.alarm_id)
+
                 self._logger.info(
                     f"告警已生成: type={alert_type}, "
                     f"camera={camera_id}, roi={roi_id}, "