The negative effects of climate change are calling for new approaches to promote energy efficiency and the use of renewable energy sources at multiple scale levels. As virtual assistants are becoming a common household item, recent studies have looked at integrating IoT and virtual assistants for energy management purposes. Despite the prominence of these works, a critical gap in the current body of research is the almost absence of real-world implementations covering different sectors of society. To address this gap, we developed the PowerShare Virtual Assistant (VA), a voice-based eco-feedback system. The paper presents results from the real-world deployment of the PowerShare VA in three distinct sectors - 1) residential, 2) commerce, and 3) industry. By looking at the human response to our system in different daily life scenarios, we aim to contribute to future research on using VA in the context of energy efficiency.

Virtual Assistants for Energy Efficiency: Real World Tryouts

Scuri S.;
2023-01-01

Abstract

The negative effects of climate change are calling for new approaches to promote energy efficiency and the use of renewable energy sources at multiple scale levels. As virtual assistants are becoming a common household item, recent studies have looked at integrating IoT and virtual assistants for energy management purposes. Despite the prominence of these works, a critical gap in the current body of research is the almost absence of real-world implementations covering different sectors of society. To address this gap, we developed the PowerShare Virtual Assistant (VA), a voice-based eco-feedback system. The paper presents results from the real-world deployment of the PowerShare VA in three distinct sectors - 1) residential, 2) commerce, and 3) industry. By looking at the human response to our system in different daily life scenarios, we aim to contribute to future research on using VA in the context of energy efficiency.
2023
Proceedings of the 2023 ACM Conference on Information Technology for Social Good
9798400701160
artificial intelligence
energy efficiency
real-world
virtual assistant
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1257339
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