TY - GEN
T1 - Advice provision for energy saving in automobile climate control systems
AU - Azaria, Amos
AU - Kraus, Sarit
AU - Goldman, Claudia V.
AU - Tsimhoni, Omer
N1 - Publisher Copyright:
Copyright © 2014, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.
PY - 2014
Y1 - 2014
N2 - Reducing energy consumption of climate control systems is important in order to reduce human environmental footprint. We consider a method for an automated agent to provide advice to drivers which will motivate them to reduce the energy consumption of their climate control unit. Our approach takes into account both the energy consumption of the climate control system and the expected comfort level of the driver. We therefore build two models, one for assessing the energy consumption of the climate control system as a function of the system's settings, and the other, models human comfort level as a function of the climate control system's settings. Using these models, the agent provides advice to the driver considering how to set the climate control system. The agent advises settings which try to preserve a high level of comfort while consuming as little energy as possible. We empirically show that drivers equipped with our agent which provides them with advice significantly save energy as compared to drivers not equipped with our agent.
AB - Reducing energy consumption of climate control systems is important in order to reduce human environmental footprint. We consider a method for an automated agent to provide advice to drivers which will motivate them to reduce the energy consumption of their climate control unit. Our approach takes into account both the energy consumption of the climate control system and the expected comfort level of the driver. We therefore build two models, one for assessing the energy consumption of the climate control system as a function of the system's settings, and the other, models human comfort level as a function of the climate control system's settings. Using these models, the agent provides advice to the driver considering how to set the climate control system. The agent advises settings which try to preserve a high level of comfort while consuming as little energy as possible. We empirically show that drivers equipped with our agent which provides them with advice significantly save energy as compared to drivers not equipped with our agent.
KW - Human-agent interaction
KW - Persuasion
KW - Sustainability technologies
UR - http://www.scopus.com/inward/record.url?scp=84911362789&partnerID=8YFLogxK
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AN - SCOPUS:84911362789
T3 - 13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014
SP - 1391
EP - 1392
BT - 13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014
T2 - 13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014
Y2 - 5 May 2014 through 9 May 2014
ER -