Artificial Intelligence Approaches for Energy Efficiency: A Review

TL;DR

This review paper discusses how Artificial Intelligence, especially multi-agent systems, can improve energy efficiency in smart buildings, addressing global climate goals and highlighting current methods, challenges, and future directions.

Contribution

It provides a comprehensive summary of AI-based approaches for energy efficiency, focusing on multi-agent systems and their application in smart buildings, along with challenges and future research areas.

Findings

AI enhances anomaly detection in smart buildings.

Classification of energy management systems into direct and indirect.

Identification of drawbacks and future research directions in AI for energy efficiency.

Abstract

United Nations set Sustainable Development Goals and this paper focuses on 7th (Affordable and Clean Energy), 9th (Industries, Innovation and Infrastructure), and 13th (Climate Action) goals. Climate change is a major concern in our society; for this reason, a current global objective is to reduce energy waste. This work summarizes all main approaches towards energy efficiency using Artificial Intelligence with a particular focus on multi-agent systems to create smart buildings. It mentions the tight relationship between AI, especially IoT, and Big Data. It explains the application of AI to anomaly detection in smart buildings and a possible classification of Intelligent Energy Management Systems: Direct and Indirect. Finally, some drawbacks of AI approaches and some possible future research focuses are proposed.