feat(ai-cam): 增强AI摄像头人脸检测逻辑

- 引入时间范围限制配置，支持按分钟设置检测窗口
- 创建DetectResult内部类，记录人脸检测的分数和时间信息
- 优化照片筛选逻辑，先按分数排序再应用时间范围过滤
- 更新设备类型名称，将"微单"改为"AI微单"
- 增强日志记录，提供更详细的调试信息

src/main/java/com/ycwl/basic/service/mobile/impl/AppAiCamServiceImpl.java

@@ -81,8 +81,30 @@ public class AppAiCamServiceImpl implements AppAiCamService {
                 }
             }
 
-            // 收集该设备符合阈值的faceSampleId
+            // 获取该设备的时间范围限制(分钟)
-            List<Long> deviceFaceSampleIds = new ArrayList<>();
+            Integer timeRangeMin = null;
+            if (configManager != null) {
+                Integer range = configManager.getInteger("ai_cam_time_range_min");
+                if (range != null && range > 0) {
+                    timeRangeMin = range;
+                    log.debug("设备{}使用配置的时间范围: {}分钟", deviceId, timeRangeMin);
+                }
+            }
+
+            // 收集该设备符合阈值的faceSampleId,同时记录分数和时间信息用于后续过滤
+            class DetectResult {
+                Long faceSampleId;
+                Float score;
+                Date detectTime;
+
+                DetectResult(Long faceSampleId, Float score, Date detectTime) {
+                    this.faceSampleId = faceSampleId;
+                    this.score = score;
+                    this.detectTime = detectTime;
+                }
+            }
+
+            List<DetectResult> detectResults = new ArrayList<>();
             for (FaceDetectLogAiCamEntity detectLog : deviceLogs) {
                 if (detectLog.getMatchRawResult() == null) {
                     continue;
@@ -95,7 +117,11 @@ public class AppAiCamServiceImpl implements AppAiCamService {
                             if (item.getScore() != null && item.getScore() >= scoreThreshold && item.getExtData() != null) {
                                 try {
                                     Long faceSampleId = Long.parseLong(item.getExtData());
-                                    deviceFaceSampleIds.add(faceSampleId);
+                                    detectResults.add(new DetectResult(
+                                        faceSampleId,
+                                        item.getScore(),
+                                        detectLog.getCreateTime()
+                                    ));
                                 } catch (NumberFormatException e) {
                                     log.warn("解析faceSampleId失败: extData={}", item.getExtData());
                                 }
@@ -108,10 +134,50 @@ public class AppAiCamServiceImpl implements AppAiCamService {
             }
 
             // 应用照片数量限制(保留前N个)
-            if (deviceFaceSampleIds.size() > photoLimit) {
+            if (detectResults.size() > photoLimit) {
                 log.debug("设备{}的照片数量{}超过限制{},截取前{}张",
-                    deviceId, deviceFaceSampleIds.size(), photoLimit, photoLimit);
+                    deviceId, detectResults.size(), photoLimit, photoLimit);
-                deviceFaceSampleIds = deviceFaceSampleIds.subList(0, photoLimit);
+                detectResults = detectResults.subList(0, photoLimit);
+            }
+
+            // 应用时间范围限制
+            List<Long> deviceFaceSampleIds;
+            if (timeRangeMin != null && !detectResults.isEmpty()) {
+                // 找到分数最高的照片
+                DetectResult highestScoreResult = detectResults.stream()
+                    .max(Comparator.comparing(r -> r.score))
+                    .orElse(null);
+
+                if (highestScoreResult != null && highestScoreResult.detectTime != null) {
+                    Date baseTime = highestScoreResult.detectTime;
+                    long halfRangeMillis = (long) timeRangeMin * 60 * 1000 / 2;
+                    Date startTime = new Date(baseTime.getTime() - halfRangeMillis);
+                    Date endTime = new Date(baseTime.getTime() + halfRangeMillis);
+
+                    // 过滤出时间范围内的照片
+                    List<DetectResult> filteredResults = detectResults.stream()
+                        .filter(r -> r.detectTime != null
+                            && !r.detectTime.before(startTime)
+                            && !r.detectTime.after(endTime))
+                        .collect(Collectors.toList());
+
+                    log.debug("设备{}应用时间范围{}分钟过滤: {}张 -> {}张 (基准时间: {})",
+                        deviceId, timeRangeMin, detectResults.size(), filteredResults.size(), baseTime);
+
+                    deviceFaceSampleIds = filteredResults.stream()
+                        .map(r -> r.faceSampleId)
+                        .collect(Collectors.toList());
+                } else {
+                    // 没有时间信息,不过滤
+                    deviceFaceSampleIds = detectResults.stream()
+                        .map(r -> r.faceSampleId)
+                        .collect(Collectors.toList());
+                }
+            } else {
+                // 不限制时间范围
+                deviceFaceSampleIds = detectResults.stream()
+                    .map(r -> r.faceSampleId)
+                    .collect(Collectors.toList());
             }
 
             if (!deviceFaceSampleIds.isEmpty()) {

src/main/java/com/ycwl/basic/service/mobile/impl/GoodsServiceImpl.java

@@ -128,7 +128,7 @@ public class GoodsServiceImpl implements GoodsService {
         } else if (sourceType == 2) {
             goodsNamePrefix = "图片";
         } else if (sourceType == 3) {
-            goodsNamePrefix = "微单";
+            goodsNamePrefix = "AI微单";
         } else {
             goodsNamePrefix = "其他类型";
         }