Summary of Artificial Intelligence Approaches For Energy Efficiency: a Review, by Alberto Pasqualetto et al.
Artificial Intelligence Approaches for Energy Efficiency: A Review
by Alberto Pasqualetto, Lorenzo Serafini, Michele Sprocatti
First submitted to arxiv on: 31 Jul 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper addresses the United Nations’ Sustainable Development Goals 7, 9, and 13 by exploring energy efficiency through Artificial Intelligence (AI). The focus is on multi-agent systems for smart buildings, highlighting the connection between AI, Internet of Things (IoT), and Big Data. Specifically, the authors discuss applying AI to anomaly detection in smart buildings and categorize Intelligent Energy Management Systems into Direct and Indirect approaches. The paper also touches on potential drawbacks of AI-based solutions and proposes future research directions. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about using Artificial Intelligence (AI) to make our energy systems more efficient and clean. It looks at how AI can help us reduce waste and create smart buildings that use energy better. The authors talk about how AI works with other technologies like the Internet of Things (IoT) and Big Data to detect problems in buildings and manage energy usage. They also discuss some challenges and potential areas for further research. |
Keywords
» Artificial intelligence » Anomaly detection
