Exploring data lakehouse as data infrastructure for ambient assisted living

• Autor(a) principal: Cunha, Diogo Guilherme Rocha
• Data de Publicação: 2023
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10773/41714
• topic: Data lake; Data lakehouse; Smart mirror; Smart home; Ambient assisted living

Over the past decade, a data explosion has generated 30,000 gigabytes of data every second. Within this data-rich landscape, emergent data infrastructures like data lakes and, notably, data lakehouses have emerged. The data lakehouse represents a revolutionary approach, seamlessly combining the agility of data lakes with the structured querying capabilities of data warehouses. One of our primary objectives is to conduct a comparative analysis and gain a deeper understanding of the distinctions between these concepts (data warehouse, data lake, and data lakehouse). Data lakehouse solutions offer a promising, technology-agnostic approach to handle data from gathering to information extraction and visualization. One relevant context nowadays is Ambient Assisted Living (AAL) systems, which are increasingly essential due to aging populations. AAL environments generate vast amounts of data from various sources, making traditional data management systems inadequate. This dissertation explores implementing a data lakehouse architecture to address technical and privacy concerns associated with integrating sensor data for contextdependent AAL objectives. As a proof of concept scenario, we used smart mirrors, a challenging monitoring solution with potential privacy and resource issues involving real-time video processing to extract health-related measures. The deployed system illustrates the data lakehouse’s ability to cover scenario requirements while following typical data lakehouse architecture blueprints and patterns using open-source solutions. Although a proof of concept, it provided caregivers with tools for informed decision-making through user-friendly dashboards. The system development process also allowed us to highlight some issues and concerns that must be taken into consideration when applying data lakehouse solutions to an AAL-like scenario.