Data-Driven Understanding of Smart Service Systems Through Text Mining

Smart service systems are everywhere, in homes and in the transportation, energy, and healthcare sectors. However, such systems have yet to be fully understood in the literature. Given the widespread applications of and research on smart service systems, we used text mining to develop a unified understanding of such systems in a data-driven way. Specifically, we used a combination of metrics and machine learning algorithms to preprocess and analyze text data related to smart service systems, including text from the scientific literature and news articles. By analyzing 5,378 scientific articles and 1,234 news articles, we identify important keywords, 16 research topics, 4 technology factors, and 13 application areas. We define ???smart service system??? based on the analytics results. Furthermore, we discuss the theoretical and methodological implications of our work, such as the 5Cs (connection, collection, computation, and communications for co-creation) of smart service systems and the text mining approach to understand service research topics. We believe this work, which aims to establish common ground for understanding these systems across multiple disciplinary perspectives, will encourage further research and development of modern service systems

Smart Grid for the Smart City

Modern cities are embracing cutting-edge technologies to improve the services they offer to the citizens from traffic control to the reduction of greenhouse gases and energy provisioning. In this chapter, we look at the energy sector advocating how Information and Communication Technologies (ICT) and signal processing techniques can be integrated into next generation power grids for an increased effectiveness in terms of: electrical stability, distribution, improved communication security, energy production, and utilization. In particular, we deliberate about the use of these techniques within new demand response paradigms, where communities of prosumers (e.g., households, generating part of their electricity consumption) contribute to the satisfaction of the energy demand through load balancing and peak shaving. Our discussion also covers the use of big data analytics for demand response and serious games as a tool to promote energy-efficient behaviors from end users

People centred eco-design: consumer adoption of low and zero carbon products and systems

Literature review, research model and findings of exploratory empirical research on consumer adoption and effective use of low and zero carbon technologies ranging from a hybrid car to solar water heating systems

M-health review: joining up healthcare in a wireless world

In recent years, there has been a huge increase in the use of information and communication technologies (ICT) to deliver health and social care. This trend is bound to continue as providers (whether public or private) strive to deliver better care to more people under conditions of severe budgetary constraint

The case for public-private partnerships in infrastructure capital budgeting

textCivil Infrastructure is needed both in the developed world and in developing countries. However, governments alone can no longer deliver the much needed projects mainly because of lack of money, but also due to the lack of technical skills and a changing type of citizenry. In today’s world, governments have to consult the market place to efficiently and optimally deliver the much needed infrastructure. The case for Public-Private Partnerships being better than the options of government run projects or fully privatized projects is that Public-Private Partnerships offer real advantages in three major areas: 1) risk benefits (financial, legal and project related benefits), 2) management and communication benefits (within the partnership but also importantly between both partners and the general public), and 3) the value addition to the public common good.Engineering Managemen

AI-native Interconnect Framework for Integration of Large Language Model Technologies in 6G Systems

The evolution towards 6G architecture promises a transformative shift in communication networks, with artificial intelligence (AI) playing a pivotal role. This paper delves deep into the seamless integration of Large Language Models (LLMs) and Generalized Pretrained Transformers (GPT) within 6G systems. Their ability to grasp intent, strategize, and execute intricate commands will be pivotal in redefining network functionalities and interactions. Central to this is the AI Interconnect framework, intricately woven to facilitate AI-centric operations within the network. Building on the continuously evolving current state-of-the-art, we present a new architectural perspective for the upcoming generation of mobile networks. Here, LLMs and GPTs will collaboratively take center stage alongside traditional pre-generative AI and machine learning (ML) algorithms. This union promises a novel confluence of the old and new, melding tried-and-tested methods with transformative AI technologies. Along with providing a conceptual overview of this evolution, we delve into the nuances of practical applications arising from such an integration. Through this paper, we envisage a symbiotic integration where AI becomes the cornerstone of the next-generation communication paradigm, offering insights into the structural and functional facets of an AI-native 6G network

Current trends on ICT technologies for enterprise information s²ystems

The proposed paper discusses the current trends on ICT technologies for Enterprise Information Systems. The paper starts by defining four big challenges of the next generation of information systems: (1) Data Value Chain Management; (2) Context Awareness; (3) Interaction and Visualization; and (4) Human Learning. The major contributions towards the next generation of information systems are elaborated based on the work and experience of the authors and their teams. This includes: (1) Ontology based solutions for semantic interoperability; (2) Context aware infrastructures; (3) Product Avatar based interactions; and (4) Human learning. Finally the current state of research is discussed highlighting the impact of these solutions on the economic and social landscape

Smart furniture as a component of a smart city-definition based on key technologies specification

There are dozens of definitions of smart furniture with meanings that vary greatly. Thus, the aim of this paper is to provide an exact definition of the phrase ``smart furniture'' based on literature and patent analysis. Why a definition? Because by providing a good definition, we have a statement that captures the meaning, the use, the function, and the essence of a term or a concept and allows the impacts on stakeholders to be described. A literature search was undertaken between 20 July 2018 and 31 August 2018, and the databases searched included SCOPUS, Web of Science, and IEEE Xplore (1998 2017), which were searched by keywords that included the phrase ``smart furniture.'' Patent searching was performed in the ESPACENET database, where 226 articles from scientific databases and 737 patent applications were examined. After the application of strict criteria, we obtained 23 articles and six patents containing meaningful definitions of smart furniture. Based on the results, smart furniture should be defined as designed, networked furniture that is equipped with an intelligent system or is controller operated with the user's data and energy sources. Smart furniture needs to have the ability to communicate and anticipate a user's needs using a plurality of sensors and actuators inside the user's environment, resulting in user-adapted furniture. The research results and discussion presented in this paper are based on the recognition that the smart furniture research has great policymaking, technological, and economy potential while contributing to the user's wellbeing and Quality of Life (QoL). This paper indicates that the collaboration between the ICT and social-economic research has to be initiated and consolidated in a sustainable way or in an environment that satisfies the needs expressed by the user.This work supported in part by the LTC INTER COST, Evaluation of the Potential for Reducing Health and Social Expenses for Elderly People Using the Smart Environment, through the Ministry of Education, Youth and Sports, Czech Republic, under Project LTC18035, in part by the Spanish Ministry of Science and University under Project TIN2016-75850-R, in part by the Universiti Teknologi Malaysia (UTM) under Research University Grant Vot-20H04, in part by the Malaysia Research University Network (MRUN) under Grant Vot 4L876, and in part by the Fundamental Research Grant Scheme (FRGS) through the Ministry of Education Malaysia under Grant Vot 5F073