案例与成果CASES & RESULTS
我们通过标准化的试点流程与可量化的验收指标，在多个场景中验证了 AIOS 平台的端侧 AI 能力。 Through standardized pilot processes and quantifiable acceptance criteria, we have validated AIOS edge AI capabilities across multiple scenarios.
在某养老机构 20 个床位部署多模态感知节点，实现 50ms 级跌倒事件触发，试运行期间事件响应时间缩短至分钟级，误报率显著下降。Deployed multimodal sensing nodes across 20 beds in an elderly care facility, achieving 50ms fall event triggering with significantly reduced false alarm rates.
针对高风险护理对象的夜间离床检测，超时未归床自动分级告警并推送至护理站，覆盖率达到 100%。Nighttime bed-leaving detection for high-risk residents with auto-graded alerts and 100% coverage of monitored beds.
在模拟居家环境中部署感知节点与本地 AI 主机，验证异常行为识别（长时间静止、活动量骤降）与远程关怀通知能力。Deployed sensing nodes and local AI host in simulated home environment, validating anomaly detection and remote care notification capabilities.
在标准房间中部署完整 AIOS 系统，演示多模态感知-本地决策-设备联动-自适应进化的全链路能力，30 天内形成个性化场景策略。Full AIOS deployment in a standard room showcasing multimodal sensing, local decision-making, device orchestration, and personalized scenario formation within 30 days.
与客户共同确认试点场景、验证目标与可量化指标。Jointly confirm pilot scenario, validation goals, and quantifiable metrics with customer.
2-4 周内完成设备安装、系统部署与基础调试。Complete device installation, system deployment, and basic tuning within 2-4 weeks.
系统试运行期间持续收集数据、优化模型参数。Continuous data collection and model parameter optimization during trial operation.
输出包含指标达成情况、系统表现、优化建议的完整试点报告。Deliver comprehensive pilot report with KPI achievement, system performance, and optimization recommendations.
1 个边缘主机 + 2-4 个感知节点 + 护理端 / 用户端 APP，适用于试点验证与小规模场景。1 edge host + 2-4 sensing nodes + caregiver/user APP, suitable for pilot validation and small-scale scenarios.
1 个楼层网关 + 多房间感知覆盖 + 护理站大屏，适用于养老机构楼层级试点。1 floor gateway + multi-room sensing coverage + nursing station dashboard, suitable for floor-level institutional pilots.
多楼层联网 + 中控管理平台 + 远程运维通道，适用于整体机构或多站点部署。Multi-floor networking + central management platform + remote O&M channel, suitable for full institution or multi-site deployment.
以下功能已在真实或模拟环境中完成验证，可安排现场或远程演示。 The following capabilities have been validated in real or simulated environments and are available for on-site or remote demonstration.
多模态跌倒识别，50ms 级事件触发，自动推送至护理端并记录事件链。Multimodal fall recognition, 50ms event trigger, auto-push to caregiver with full event chain logging.
离床事件触发后自动计时，超时未归床逐级升级告警，支持自定义阈值。Auto-timer on bed-leaving, escalating alerts on timeout, with customizable thresholds.
温湿度 / 光照 / 气体多参数监测，自动触发空调、灯光、窗帘等设备联动。Multi-parameter monitoring (temp, humidity, light, gas) with auto-triggered device orchestration.
系统运行 30 天后自动形成个性化行为基线，持续优化误报率与策略精度。System auto-generates personalized behavior baseline after 30 days, continuously optimizing false alarm rates.