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引用次数: 3
摘要
我们描述了Sammen Om Demens (SOD)的架构,这是一种便携式设备的应用程序,旨在通过护理人员、家庭成员和志愿者的普通公民的参与,帮助痴呆症患者流浪和迷路。为了能够实时检测失去方向的痴呆症患者,我们将痴呆症患者智能手机前端的位置数据高频传输到后端系统。后端系统必须能够处理高吞吐量数据,并通过人工智能技术进行可能的大量计算,以检测异常行为。这对后端设计设置了一定的性能和体系结构要求。在本文中,我们讨论了SOD后端的设计和实现选择,包括微服务和无服务器服务,以实现效率和可扩展性。我们通过在公共云上部署SOD后端并在模拟负载测试中测量性能来证明已实现的目标。
Wandering and getting lost: the architecture of an app activating local communities on dementia issues
We describe the architecture of Sammen Om Demens (SOD), an application for portable devices aiming at helping persons with dementia when wandering and getting lost through the involvement of caregivers, family members, and ordinary citizens who volunteer.To enable the real-time detection of a person with dementia that has lost orientation, we transfer location data at high frequency from a frontend on the smartphone of a person with dementia to a backend system. The backend system must be able to cope with the high throughput data and carry out possibly heavy computations for the detection of anomalous behavior via artificial intelligence techniques. This sets certain performance and architectural requirements on the design of the backend.In the paper, we discuss our design and implementation choices for the backend of SOD that involve microservices and serverless services to achieve efficiency and scalability. We give evidence of the achieved goals by deploying the SOD backend on a public cloud and measuring the performance on simulated load tests.