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Submitted by Manuel Brandão (recipp@sc.ipp.pt) on 2021-03-04T12:42:00Z No. of bitstreams: 1 DREAM-GO_3rd-Workshop_Proceedings_D7.4(1).pdf: 4711055 bytes, checksum: e08bb3ac8af1fd66fddb33f06ac61bbc (MD5) Approved for entry into archive by Ana Rebelo (amsr@isep.ipp.pt) on 2021-03-09T15:08:02Z (GMT) No. of bitstreams: 1 DREAM-GO_3rd-Workshop_Proceedings_D7.4(1).pdf: 4711055 bytes, checksum: e08bb3ac8af1fd66fddb33f06ac61bbc (MD5) Made available in DSpace on 2021-03-09T15:08:03Z (GMT). No. of bitstreams: 1 DREAM-GO_3rd-Workshop_Proceedings_D7.4(1).pdf: 4711055 bytes, checksum: e08bb3ac8af1fd66fddb33f06ac61bbc (MD5) Previous issue date: 2018 info:eu-repo/semantics/publishedVersion

Ambient intelligent has advanced in the last years. The inclusion of Artificial Intelligent techniques, as pattern recognition, has allowed these systems to have a better adaptation to the environments. In this work, a multiagent system based on PANGEA and embedded agents to manage and monitor alarms is shown. The system incorporates embedded agents in Arduino hardware devices with modules to detect sounds and luminosity bands.

Simulation of consumers and markets towards real time demand response Proceedings of the First DREAM-GO Workshop Institute of Engineering - Polytechnic of Porto, Porto, Portugal, April 6-7, 2016.

Ambient intelligent has advanced in the last years. The inclusion of Artificial Intelligent techniques, as pattern recognition, has allowed these systems to have a better adaptation to the environments. In this work, a multiagent system based on PANGEA and embedded agents to manage and monitor alarms is shown. The system incorporates embedded agents in Arduino hardware devices with modules to detect sounds and luminosity bands., The research of Alberto López has been financed by the Regional Ministry of Education in Castilla y León and the European Social Fund (Operational Programme 2014-2020 for Castilla y León, EDU/310/2015 BOCYL)

Through monitoring the power consumption of a house, it is possible to establish if someone is on it at a particular time. Currently there are several approaches to determine the occupation of a home. There are works that ad-dress the use of intrusive systems that require user interaction, while other works address the non-intrusive use of sensors for presence detection. In this article, we propose the use of a sensor network for measuring the electricity consumption of a family home. In particular, the use of a multi-agent system is proposed for the intelligent management of the data generated by the deployed sensor network. Through nonintrusive occupation monitoring algorithm, it can be determined when a house is occupied by users and when it is empty., This work has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 641794 (project DREAM-GO).