Intelligent Loneliness Monitoring in the Elderly: A Serverless Architecture with Real-Time Communication API

• DOI: https://doi.org/10.22533/at.ed.3942412073

• Palavras-chave: -

• Keywords: Loneliness, Serverless, AWS, wearables, Monitoring, IoT

• Abstract: Loneliness and social isolation pose critical public health challenges, particularly among older adults grappling with factors such as living alone, loss of social connections, chronic illness, and hearing impairment. These conditions significantly elevate the risk of premature death from various causes, including dementia, heart disease, and stroke. To combat these issues, the integration of technological platforms and commercial monitoring devices is increasingly prevalent in healthcare and elderly care. In this study, we leverage serverless architectures due to their manifold benefits, such as simplified application deployment, enhanced security-performance combination, cost and time savings, scalability without constraints, and streamlining of internal processes for continuous improvement. Our objective is to design and develop a loneliness monitor serverless architecture aimed at obtaining real-time data from commercial activity wristbands through an Application Programming Interface (API). Leveraging the Amazon Web Services (AWS) platform, we employ the Fitbit Charge 5 bracelet for loneliness monitoring. Data acquisition and storage are conducted within AWS services using the web API provided by the AWS Lambda service, with automated frequency facilitated by the event bridge. Additionally, a serverless IoT device is integrated to augment the architecture's effectiveness where applicable. In the pilot phase, the system demonstrates promising capabilities in simplifying data collection and programming sampling frequencies. Upon request, the collected data is automatically analyzed to monitor loneliness. The proposed architecture holds significant potential for streamlined data collection, analysis, security, personalization, real-time inference, and scalability of sensors and actuators. It offers valuable benefits for application in the healthcare sector, mitigating cases of depression and loneliness among vulnerable populations.