鸿蒙跨设备老人跌倒监测系统：分布式行为识别与紧急响应方案原创

进修的泡芙

发布于 2025-6-22 17:34

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鸿蒙跨设备老人跌倒监测系统：分布式行为识别与紧急响应方案

一、系统架构设计

!https://example.com/harmonyos-fall-detection-arch.png

采用四层架构：
感知层：多设备摄像头与传感器网络

分析层：分布式行为识别与风险评估

响应层：紧急通知与协同救助

展示层：多终端状态监控与历史记录

二、核心模块实现
跌倒行为识别模块

// FallDetector.ts
import image from ‘@ohos.multimedia.image’;
import poseEstimation from ‘@ohos.ai.poseEstimation’;
import distributedData from ‘@ohos.data.distributedData’;

interface FallDetectionResult {
timestamp: number;
deviceId: string;
confidence: number;
position: [number, number]; // [x,y] 相对坐标
posture: ‘standing’ ‘sitting’ ‘lying’
‘fallen’;
export class FallDetector {

private poseEstimator: poseEstimation.PoseEstimator;
private kvManager: distributedData.KVManager;
private kvStore?: distributedData.KVStore;

async init() {
// 初始化姿态估计模型
this.poseEstimator = await poseEstimation.createEstimator({
model: ‘fall_detection_v3’,
jointThreshold: 0.3
});

// 初始化分布式数据同步
const context = getContext(this);
this.kvManager = distributedData.createKVManager({ context });
this.kvStore = await this.kvManager.getKVStore('fall_alerts', {
  createIfMissing: true,
  autoSync: true,
  securityLevel: distributedData.SecurityLevel.S2
});

async detectFromCamera(image: image.Image): Promise<FallDetectionResult | undefined> {

const pose = await this.poseEstimator.estimate(image);
const result = this.analyzePose(pose);

if (result.posture === 'fallen') {
  await this.kvStore?.put(alert_${result.timestamp}, result);
  return result;

}

private analyzePose(pose: poseEstimation.Pose): FallDetectionResult {
const joints = pose.joints;
const head = joints.find(j => j.type === ‘head’);
const hips = joints.find(j => j.type === ‘hip_center’);

// 简单跌倒检测逻辑（实际项目应使用更复杂算法）
let posture: FallDetectionResult['posture'] = 'standing';
let confidence = 0;

if (head && hips) {
  const verticalAngle = this.calculateAngle(head, hips);
  if (verticalAngle > 45) {
    posture = 'fallen';
    confidence = 0.9;

else if (verticalAngle > 30) {

    posture = 'lying';
    confidence = 0.7;

}

return {
  timestamp: Date.now(),
  deviceId: 'local_device',
  confidence,
  position: [pose.center.x, pose.center.y],
  posture
};

// 其他辅助方法…

紧急响应协同模块

// EmergencyResponder.ts
import deviceManager from ‘@ohos.distributedHardware.deviceManager’;
import notification from ‘@ohos.notification’;
import call from ‘@ohos.telephony.call’;

export class EmergencyResponder {
private contacts: EmergencyContact[] = [];

async init() {
// 加载紧急联系人
this.contacts = await this.loadEmergencyContacts();
async handleFallDetection(alert: FallDetectionResult) {

// 本地警报
await this.triggerLocalAlarm();

// 通知其他设备
await this.notifyLinkedDevices(alert);

// 拨打紧急电话
if (alert.confidence > 0.8) {
  await this.callEmergencyContact();

}

private async triggerLocalAlarm() {
await notification.publish({
id: 999,
content: {
title: ‘跌倒警报’,
text: ‘检测到可能的跌倒事件！’,
additionalData: { type: ‘fall_alert’ }
},
color: ‘#FF0000’
});
private async notifyLinkedDevices(alert: FallDetectionResult) {

const devices = await deviceManager.getTrustedDeviceListSync();
await Promise.all(devices.map(device => 
  this.sendAlertToDevice(device.deviceId, alert)
));

// 其他方法…

主页面实现（ArkUI）

// FallMonitorApp.ets
import { FallDetector } from ‘./FallDetector’;
import { EmergencyResponder } from ‘./EmergencyResponder’;

@Entry
@Component
struct FallMonitorApp {
@State isMonitoring: boolean = false;
@State lastAlert?: FallDetectionResult;
@State activityLog: ActivityEvent[] = [];

private detector = new FallDetector();
private responder = new EmergencyResponder();
private cameraController?: CameraController;

async aboutToAppear() {
await this.detector.init();
await this.responder.init();
this.setupAlertListener();
private setupAlertListener() {

eventBus.on('fall_alert', (alert: FallDetectionResult) => {
  this.lastAlert = alert;
  this.activityLog.unshift({
    type: 'alert',
    timestamp: alert.timestamp,
    data: alert
  });
  
  if (alert.confidence > 0.7) {
    this.responder.handleFallDetection(alert);

});

async startMonitoring() {

this.isMonitoring = true;
this.cameraController = new CameraController({
  onFrame: async (image: image.Image) => {
    const result = await this.detector.detectFromCamera(image);
    if (result) {
      eventBus.emit('fall_alert', result);

  frameRate: 5 // 5fps足够用于跌倒检测
});
this.cameraController.start();

build() {

Column() {
  // 状态显示
  MonitoringStatus({
    active: this.isMonitoring,
    lastAlert: this.lastAlert
  })
  
  // 活动日志
  ActivityLog({
    events: this.activityLog
  })
  
  // 控制按钮
  Row() {
    Button(this.isMonitoring ? '停止监测' : '开始监测')
      .onClick(() => this.isMonitoring ? this.stopMonitoring() : this.startMonitoring())
    Button('测试警报')
      .onClick(() => this.testAlert())

}

// 其他方法…

@Component

struct MonitoringStatus {
@Prop active: boolean;
@Prop lastAlert?: FallDetectionResult;

build() {
Column() {
Text(this.active ? ‘监测中…’ : ‘监测已停止’)
.fontSize(18)
.fontColor(this.active ? ‘#00FF00’ : ‘#FF0000’)

  if (this.lastAlert) {
    Text(最后警报: ${new Date(this.lastAlert.timestamp).toLocaleTimeString()})
      .fontSize(16)
    Text(置信度: ${(this.lastAlert.confidence * 100).toFixed(1)}%)
      .fontColor(this.lastAlert.confidence > 0.7 ? '#FF0000' : '#FFA500')

}

@Component
struct ActivityLog {
@Prop events: ActivityEvent[];

build() {
List() {
ForEach(this.events, (event) => {
ListItem() {
ActivityLogItem({ event })
})

.height(‘60%’)

}

@Component
struct ActivityLogItem {
@Prop event: ActivityEvent;

build() {
Row() {
Text(new Date(this.event.timestamp).toLocaleTimeString())
.fontSize(14)

  Text(this.event.type === 'alert' ? '跌倒警报' : '活动检测')
    .fontColor(this.event.type === 'alert' ? '#FF0000' : '#000000')

.padding(10)

}

三、跨设备协同关键实现
多视角验证机制

// 在FallDetector中添加
async verifyWithMultipleViews(alert: FallDetectionResult): Promise<boolean> {
const devices = await deviceManager.getTrustedDeviceListSync();
const verifications = await Promise.all(
devices.map(device => this.getDeviceVerification(device.deviceId, alert.timestamp))
);

// 至少两个设备确认才认为是真实跌倒
return verifications.filter(Boolean).length >= 2;
private async getDeviceVerification(deviceId: string, timestamp: number): Promise<boolean> {

try {
const remoteStore = await distributedData.getRemoteKVStore(deviceId, ‘fall_alerts’);
const alert = await remoteStore.get(alert_${timestamp});
return alert?.confidence > 0.6;
catch (err) {

console.error(获取设备${deviceId}验证失败:, err);
return false;

}

紧急响应协同

// 在EmergencyResponder中添加
private async activateEmergencyProtocol(alert: FallDetectionResult) {
// 1. 通知所有家庭成员设备
await this.notifyFamilyMembers(alert);

// 2. 启动最近设备的摄像头
await this.activateNearestCamera(alert.position);

// 3. 如果无响应，自动呼叫救护车
setTimeout(async () => {
if (!this.receivedAcknowledgement) {
await this.callAmbulance();
}, 30000); // 30秒无响应后呼叫

private async activateNearestCamera(position: [number, number]) {

const devices = await this.getLocationAwareDevices();
const nearest = this.findNearestDevice(devices, position);

if (nearest) {
await this.remoteActivateCamera(nearest.deviceId);
}

分布式状态同步

// 新增StatusMonitor.ts
export class StatusMonitor {
private kvManager: distributedData.KVManager;

async init() {
const context = getContext(this);
this.kvManager = distributedData.createKVManager({ context });
async updateDeviceStatus(status: DeviceStatus) {

const kvStore = await this.kvManager.getKVStore('device_status');
await kvStore.put(status_${status.deviceId}, status);

async getActiveDevices(): Promise<DeviceStatus[]> {

const kvStore = await this.kvManager.getKVStore('device_status');
const entries = await kvStore.entries('status_');

return entries
  .map(([_, v]) => v as DeviceStatus)
  .filter(s => s.lastActive > Date.now() - 300000); // 5分钟内活跃

}

四、性能优化方案
动态采样调整

// 在FallDetector中添加
private adjustSamplingRate(activityLevel: number): number {
// 根据活动程度调整采样率
if (activityLevel > 0.7) return 10; // 高活动时10fps
if (activityLevel > 0.3) return 5; // 中等活动5fps
return 2; // 低活动2fps

区域兴趣检测

// 在FallDetector中添加
private detectROI(image: image.Image): { x: number; y: number; width: number; height: number } {
// 使用轻量级运动检测确定感兴趣区域
return { x: 0, y: 0, width: image.width, height: image.height }; // 简化实现

本地结果缓存

const detectionCache = new Map<string, FallDetectionResult>();

async getCachedDetection(imageHash: string): Promise<FallDetectionResult | undefined> {
if (detectionCache.has(imageHash)) {
return detectionCache.get(imageHash);
const image = await this.loadImage(imageHash);

if (!image) return undefined;

const result = await this.detector.detectFromCamera(image);
if (result) {
detectionCache.set(imageHash, result);
return result;

五、应用场景扩展
日常活动监测

class ActivityTracker {
async trackDailyActivities(detections: FallDetectionResult[]) {
// 分析日常活动模式
}

服药提醒联动

class MedicationReminder {
async checkMedicationAfterFall(fallTime: number) {
// 检查跌倒后是否按时服药
}

康复进度评估

class RehabProgress {
async assessMobilityImprovement(history: FallDetectionResult[]) {
// 根据跌倒频率评估康复进度
}

夜间安全监测

class NightGuard {
async monitorNighttimeMovements() {
// 特别关注夜间活动安全
}

本系统充分利用HarmonyOS分布式能力，实现了：
多设备协同监测：消除监控盲区，提高检测准确率

分级响应机制：根据置信度采取不同响应措施