In response to the social issue of the increasing number of elderly vulnerable groups going missing due to the aggravating aging population in China, our team has developed a wearable anti-loss device and intelligent early warning system for elderly individuals with intermittent dementia using artificial intelligence and IoT technology. This system comprises an anti-loss smart helmet, a cloud computing module, and an intelligent early warning application on the caregiver's mobile device. The smart helmet integrates a miniature camera module, a GPS module, and a 5G communication module to collect first-person images and location information of the elderly. Data is transmitted remotely via 5G, FTP, and TCP protocols. In the cloud computing module, our team has proposed for the first time a multimodal dangerous state recognition network based on scene and location information to accurately assess the risk of elderly individuals going missing. Finally, the application software interface designed for the caregiver's mobile device implements multi-level early warnings. The system developed by our team requires no operation or response from the elderly, achieving fully automatic environmental perception, risk assessment, and proactive alarming. This overcomes the limitations of traditional monitoring devices, which require active operation and response, thus avoiding the issue of the digital divide for the elderly. It effectively prevents accidental loss and potential dangers for elderly individuals with dementia.

翻译：针对我国人口老龄化加剧背景下老年弱势群体走失事件频发的社会问题，本团队基于人工智能与物联网技术，研发了面向老年间歇性痴呆患者的可穿戴防走失设备及智能预警系统。该系统由防走失智能头盔、云计算模块及监护人移动端智能预警应用三部分构成。智能头盔集成微型摄像模块、GPS模块与5G通信模块，用于采集老年人的第一视角图像与位置信息，并通过5G、FTP及TCP协议进行远程数据传输。在云计算模块中，本团队首次提出了基于场景与位置信息的多模态危险状态识别网络，以精准评估老年人走失风险。最后，面向监护人移动端设计的应用软件界面实现了多级预警功能。本团队研发的系统无需老年人进行任何操作或响应，实现了全自动的环境感知、风险评估与主动告警，克服了传统监测设备需主动操作响应的局限性，从而避免了老年人面临的数字鸿沟问题，有效预防老年痴呆患者的意外走失及潜在危险。