Sustainable electric appliances are designed to minimize their environmental impact by reducing energy consumption, using environmentally friendly materials and minimizing waste during production and disposal. The purpose of this study is to analyze existing research on sustainable electric appliances using advanced machine learning methods, such as topic modeling, to identify key themes and trends. This research is crucial in light of increasing global electricity demand, the urgent need to reduce greenhouse gas emissions and the critical role of energy-efficient appliances in achieving sustainability goals and net-zero emission targets.
This study conducts a comprehensive literature evaluation on the topic of “Sustainable electric appliances” using a machine learning technique called topic modeling with latent Dirichlet allocation. This approach enables systematic analysis of the existing research and the identification of key themes.
The analysis identifies nine major themes based on the evaluation of research papers published in leading international journals. The major themes include climate change, minimizing pollution, the usage and popularity of electric appliances, the impact of electric appliances on the environment and different government initiatives to encourage the adoption of sustainable electric appliances. The findings of this research are highly relevant for stakeholders, including policymakers, manufacturers and consumers, as they provide actionable insights to promote the adoption and innovation of sustainable electric appliances, contributing to a more environmentally and economically resilient future. Furthermore, the study critically evaluates the current state of research and highlights opportunities for future exploration, offering valuable implications for academia and industry.
This study uniquely applies topic modeling to analyze research trends in sustainable electric appliances, providing a novel perspective on the advancements and challenges in this critical area.
