Using case based data stream processing for smart house systems

• Autores: Martínez, Alejandro Maximiliano; Granado Martínez, Natalia Lucía; Martín, María de los Ángeles
• Año de publicación: 2020
• Idioma: inglés
• Tipo de recurso: documento de conferencia
• Materia: Ciencias Informáticas; Data stream processing; Big data; Case based reasoning learning; Domotic; Ontology
• Institución: Universidad Nacional de La Plata

The latest technological advances have allowed the development of smart home systems that establish a connection between humans and the devices that surround them, living in homes and working in fully automated companies. While these systems improve the quality of life of people in terms of comfort, safety and energy savings, as they automate aspects such as lighting, temperature, humidity, among others; they lack an organizational memory that manages the knowledge of the preferences, customs and behavior patterns of the inhabitants of the home or company they automate. The aforementioned lack shows an opportunity to improve these products, taking into account that the market trend in domestic devices, is to maximize automation, making them increasingly intelligent, to make decisions proactively, and to collaborate with each other and with the human being for his better quality of life. In this paper we show that it is possible to improve the management of the data stream captured by the devices, providing them with interoperability through the use of ontologies and metadata, so that "intelligent modules" process the acquired knowledge automatically, with little intervention from the humans. Specifically, we will use the Processing Architecture based on Measurement Metadata (PAbMM) and the Case based Reasoning (CBR) technology to intelligently establish the environmental conditions of the home, in order to improve comfort and reduce energy consumption.
Sociedad Argentina de Informática