Wandering and getting lost: the architecture of an app activating local communities on dementia issues
This addresses the issue of wandering and getting lost for persons with dementia, involving caregivers and volunteers, but it is incremental as it focuses on backend design improvements.
The paper tackles the problem of real-time detection of disorientation in persons with dementia by designing a backend architecture for an app that uses high-frequency location data and AI techniques, achieving efficiency and scalability as demonstrated through simulated load tests on a public cloud deployment.
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.