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The IMPReSS project is a 30-months EU-Brazil cooperative research project started in 2013.

The project is partly funded by the European Commission under the 7th Framework Programme in the area of EU-Brazil Research and Development cooperation under Grant Agreement no. 614100

The Brazilian funding is provided by CNPq Conselho Nacional de Desenvolvimento Científico e Tecnológico

 

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Downloads: Economia de Energia Elétrica em Ambientes Inteligentes Baseada no Reconhecimento de Atividades do Us
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Downloads Home > Scientific Papers > Economia de Energia Elétrica em Ambientes Inteligentes Baseada no Reconhecimento de Atividades do Us

Economia de Energia Elétrica em Ambientes Inteligentes Baseada no Reconhecimento de Atividades do Us In Portuguese


In recent years, power consumption has gradually increased in all sectors, especially in residential areas. This increase is mainly due to the emergence of new electrical appliances, for this reason, several solutions have been proposed by government and industry in order to minimize the energy consumption in homes. Among the proposed approaches, people's awareness, use of renewable energy sources and the creation of intelligent devices are highlighted . In addition, the use of Information and Communication Technologies (ICTs) in smart environments has been seen as an interesting alternative to deal with this problem. The idea is that the residences are instrumented with sensors and actuators in order to monitor people activities and, thereby, manage the power consumption based on their habits. In this context, this work proposes and validates a method to save energy through user activities in an intelligent environment using artificial intelligence techniques. The goal is to identify the devices related to user activities and make recommendations during their execution, avoiding waste. The proposed method, called AAEC (Activity-Appliance-Energy Consumption), is able to analyze a set of data collected from sensors available in the environment, after it recognizes user activities and recommends actions aimed at cost containment. Tests on a real database shown that the proposed method is able to save up to 35% of electricity. In general, the inclusion of AAEC method was a good solution to help people save energy without effort on individual behavior changes, contributing to the conscious use of energy and to the development of a sustainable society
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March 29 2016 11:08:59
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