Virtual agent organizations for user behaviour pattern extraction in energy optimization processes: A new perspective

Abstract

The optimization of energy use in family homes and public buildings is an ongoing topic of discussion. State-of-the-art research has almost always focused on reducing the consumption of heating systems, air-conditioning or lighting. Despite their importance, user-related variables, such as comfort, are normally not included in the optimization process. These aspects should be considered to be able to e↵ectively minimize energy consumption. Thus, there is a need for a comprehensive energy optimization approach, one that will consider both climatological factors and user behaviour. Learning about user behaviour is key to e↵ective optimization. In this work, the proposed architecture's capacity to organize Virtual Agent Organizations (VAO) allows it to adapt to highly variable user behavior and preferences. This agent methodology has the ability to manage Wireless Sensor Networks (WSNs), Artificial Neural Networks (ANN) and Case-Based Reasoning (CBR) to obtain user preferences and predict their behaviour in the home or building. The proposed approach has been tested in two di↵erent buildings, a traditional-construction house and a modular home, obtaining savings of 30.16% and 13.43%, respectively. These results validate the proposed mixed approach of temperature adjustment algorithms together with the extraction of user behavior patterns for the establishment of a threshold based on preferences.

A Systematic Study on the Extraction and Image Reproduction of Ceramic Sculpture Artworks

“…The central coordinates of each pattern in the pattern are abstracted into points, and the paths between each point are abstracted into lines; the topology formed by these points and lines is called the pattern configuration rule. According to the pattern configuration extraction rules, the configuration rules of each pattern in the case library are extracted, and the configuration rule library is established [ 11 ].…”

Dual Modality Collaborative Learning for Cross-Source Remote Sensing Retrieval

“…Therefore, content-based remote sensing retrieval (CBRSIR) attracts researchers' attention. As a useful image management tool, CBRSIR plays an essential role in broad applications, such as land cover extraction, energy optimization, and agriculture and forest monitoring [5][6][7].…”