Smart Homes and Families to Enable Sustainable Societies: A Data-Driven Approach for Multi-Perspective Parameter Discovery using BERT Modelling

التفاصيل البيبلوغرافية
العنوان: Smart Homes and Families to Enable Sustainable Societies: A Data-Driven Approach for Multi-Perspective Parameter Discovery using BERT Modelling
المؤلفون: Sanaa Sharaf, Eman Alqahtani, Rashid Mehmood, Nourah Janbi
المصدر: Sustainability; Volume 14; Issue 20; Pages: 13534
بيانات النشر: Preprints, 2022.
سنة النشر: 2022
مصطلحات موضوعية: Renewable Energy, Sustainability and the Environment, Geography, Planning and Development, artificial_intelligence_robotics, Building and Construction, smart families, smart homes, sustainable societies, smart cities, natural language processing (NLP), Bidirectional Encoder Representations from Transformers (BERT), Management, Monitoring, Policy and Law
الوصف: Technological advancements and innovations have profoundly changed the lives of people giving rise to smart environments, cities, and societies. As homes are the building block of cities and societies, smart homes are critical to establishing smart living and are expected to play a key role in enabling smart cities and societies. The current academic literature and commercial advancements on smart homes have mainly focused on developing and providing smart functions for homes to provide security management and facilitate the residents in their various activities such as ambiance management. Homes are much more than physical structures, buildings, appliances, operational machines, and systems. Homes are composed of families and are inherently complex phenomena underlined by humans and their relationships with each other, subject to individual, intragroup, intergroup, and intercommunity goals. There is a clear need to understand, define, consolidate existing research, and actualize the overarching roles of smart homes, the roles of smart homes that would serve the needs of future smart cities and societies. This paper introduces our data-driven parameter discovery methodology and uses it to provide, for the first time, an extensive, rather fairly comprehensive, analysis of the families and homes landscape seen through the eyes of academics and the public using over a hundred thousand research papers and nearly a million tweets. We develop a methodology using deep learning, natural language processing (NLP), and big data analytics methods and apply it to automatically discover parameters that capture a comprehensive knowledge and design space of smart families and homes comprising social, political, economic, environmental, and other dimensions. The 66 discovered parameters and the knowledge space comprising 100s of dimensions are explained by reviewing and referencing over 300 articles from the academic literature and tweets. The knowledge and parameters discovered in this paper can be used to develop a holistic understanding of matters related to families and homes facilitating the development of better, community-specific, policies, technologies, solutions, and industries for families and homes, leading to strengthening families and homes, and in turn, empowering sustainable societies across the globe.
وصف الملف: application/pdf
اللغة: English
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::044ff373170fee17d111c462ad46e399
Rights: OPEN
رقم الانضمام: edsair.doi.dedup.....044ff373170fee17d111c462ad46e399
قاعدة البيانات: OpenAIRE