Unleashing the Future of Smart Homes: A Revelation of Cutting-Edge Distributed Architecture
Recent discussions have delved extensively into Smart Homes, focusing on constructing and integrating services into an architecture capable of supporting the daily routine of the homes of several users and providing a stable operation. When artificial intelligence is added to a development architecture with devices that interface between man and machine, creating a system that operates in conjunction with users becomes a real challenge. How the system may or may not behave in the day-to-day lives of users becomes the genuine concern of developers. This brings challenges to be overcome and decisions to be made. Implementation decisions, division and creation of modules, communications between applications, user actions, communication interfaces, server response times, and other issues arise amidst all the complexity of developing for the real world. Observing the current scenario, we present our proposal for a distributed Smart Home architecture integrated with a third-party SAAS-based cloud service with an extensive catalog of smart devices used in a smart home environment. Our architecture obtains data about devices from users’ homes registered in a third-party cloud, and uses Artificial Intelligence to train a model using the user’s routine based on the behavior and use of devices in the house. The system provides recommendations sent directly to the smartphone or smartwatch to help with user comfort or to reduce energy consumption. This work presents the system architecture, technologies, and communications between services. Ultimately, we list the lessons learned in architectural design, solution coding, module integration, communication with smartphones and smartwatches, and working with intelligent physical devices in the user’s environment.
Authors
- Gustavo B. Figueiredo (ORCID: https://orcid.org/0000-0001-9756-378X)
- Cássio Prazeres (ORCID: https://orcid.org/0000-0003-0197-0909)
- Dhyego Tavares (ORCID: https://orcid.org/0000-0003-1633-0787)
- Frederico Araújo Dur�ão (ORCID: https://orcid.org/0000-0002-7766-6666)
- Eduardo Santana de Almeida (ORCID: https://orcid.org/0000-0002-9312-6715)
- Ivan Machado (ORCID: https://orcid.org/0000-0001-9027-2293)
- Denivan Campos (ORCID: https://orcid.org/0000-0002-0033-3791)
- Maycon Peixoto (ORCID: https://orcid.org/0000-0002-4851-5228)
- Joselito Jr
- Luana Martins
Publication Details
- Published
- 2024-09-30
- DOI
- https://doi.org/10.5753/sbcars.2024.3854
- Citations
- 1
- Primary Topic
- Context-Aware Activity Recognition Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.25
Funders
- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
- Conselho Nacional de Desenvolvimento Científico e Tecnológico
- Fundação de Amparo à Ciência e Tecnologia do Estado de Pernambuco
- Fundação de Amparo à Pesquisa do Estado da Bahia