Abstract The Indoor Household Environment (IHE) has caught the attention of industry and
academia due to the substantial amount of time that families spend indoors. Domestic air …

Indoor environmental quality is an important issue since people spend most of their time
indoors. This paper aims to develop an autonomous indoor environment management …

Heating, ventilation, and air-conditioning (HVAC) systems are responsible for a
considerable proportion of total building energy consumption but are also vital for improved …

The use of machine learning techniques has been proven to be a viable solution for smart
home energy management. These techniques autonomously control heating and domestic …

In this short communication, a data-driven deep reinforcement learning (deep RL) method is
applied to minimize HVAC users' energy consumption costs while maintaining users' …

Advanced metering infrastructure and bilateral communication technologies facilitate the
development of the home energy management system in the smart home. In this paper, we …

This paper presents Model-based Reinforcement Learning (MB-RL) techniques to control
the indoor air temperature, and CO2 concentration level, and minimize the energy …

With the development of artificial intelligence technology, various intelligent algorithms are
applied in building energy system optimization. Deep reinforcement learning (DRL) …

The rising demand for electricity and its essential nature in today's world call for intelligent
home energy management systems that can reduce energy usage. This article aims a novel …

In recent years, home energy management systems (HEMS), which enable the automatic
control of electrical equipment and home appliances, have been attracting attention as a …