It is clear that the field of artificial intelligence (AI) as a decision-oriented tool has recently proven to be a viable alternative approach to solve environmental challenges. For example, artificial neural networks (ANNs) and support vector machines (SVMs), which are a subset of artificial intelligence, are going to be widely used to predict energy consumption in the buildings. The work aims to explore the use of user behaviour, smart and passive systems to improve energy efficiency and indoor environmental quality (IEQ) in buildings. The presence of users within buildings can affect process improvement. For example, users can contribute to energy efficiency by switching off artificial lighting during daylight hours. Furthermore, they can reduce the use of energy by changing their behaviour to act according to principles of sustainable development. In order to evaluate the impact of user behaviour on energy consumption, development of an assessment model based on artificial intelligence (AI) can be useful. On the other hand, use of a new concept from artificial intelligence in assessment tools can not only explore the potential benefits of approach but also provide ways to achieve an optimum level of efficiency.

Strategic Sustainable and Smart Development Based on User Behaviour

Theo ZAFFAGNINI
Co-primo
2018

Abstract

It is clear that the field of artificial intelligence (AI) as a decision-oriented tool has recently proven to be a viable alternative approach to solve environmental challenges. For example, artificial neural networks (ANNs) and support vector machines (SVMs), which are a subset of artificial intelligence, are going to be widely used to predict energy consumption in the buildings. The work aims to explore the use of user behaviour, smart and passive systems to improve energy efficiency and indoor environmental quality (IEQ) in buildings. The presence of users within buildings can affect process improvement. For example, users can contribute to energy efficiency by switching off artificial lighting during daylight hours. Furthermore, they can reduce the use of energy by changing their behaviour to act according to principles of sustainable development. In order to evaluate the impact of user behaviour on energy consumption, development of an assessment model based on artificial intelligence (AI) can be useful. On the other hand, use of a new concept from artificial intelligence in assessment tools can not only explore the potential benefits of approach but also provide ways to achieve an optimum level of efficiency.
2018
9783319945941
9783319945958
Indoor Environmental Quality (IEQ), Behavioural adaptation, Sustainable Smart Behaviour, Real-time monitoring of environmental data, ICT tools.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2392938
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