Knowledge-Based Smart City Service System

Towards Semantic Smart Cities: A Study on the Conceptualization and Implementation of Semantic Context Inference Systems

Smart cities provide integrated management and operation of urban data emerging within a city, supplying the infrastructure for smart city services and resolving various urban challenges. Nevertheless, cities continue to grapple with substantial issues, such as contagious diseases and terrorism, that pose severe financial and human risks. These problems sporadically arise in various locales, and current smart city frameworks lack the capability to autonomously identify and address these issues. The challenge intensifies especially when trying to recognize and respond to unprecedented problems. The primary objective of this research is to predict potential urban issues and support their resolution proactively. To achieve this, our system makes use of semantic reasoning to understand the ongoing situations within the city. In this process, the 5W1H principles serve as inference rules, guiding the extraction and consolidation of context. Firstly, utilizing domain-specific annotation templates, we craft a semantic graph by amalgamating information from various sources available in the city, such as municipal public data and IoT platforms. Subsequently, the system autonomously infers and accumulates contexts of situations occurring in the city using 5W1H-based reasoning. As a result, the accumulated contexts allow for inferring potential urban problems by identifying repeated disruptions in city services at specific times or locations and establishing connections among them. The main contribution of this paper lies in proposing a comprehensive conceptual model for the suggested system and presenting actual implementation cases and applicable use cases. These contributions facilitate awareness among city administrators and citizens within a smart city regarding potential problem-prone areas or times, thereby aiding in the preemptive identification and mitigation of urban challenges.

Rethinking Technology-Based Services to Promote Citizen Participation in Urban Mobility

Cities are complex and dynamic systems in which a network of actors interact, creating value through different activities. Cities can, therefore, be viewed as service ecosystems. Municipalities take advantage of digitalization to implement a service-dominant logic in urban and mobility planning and management, developing strategies with which citizens, local authorities, and other actors can create value together. While citizens are offered a better service experience, local authorities use citizens' input to improve decision-making processes. This research considers that designing an integrated service supported by an integrated information system can respond to current challenges in decision-making and information access for transport and mobility. Through a multidisciplinary methodological approach, this work proposes some guidelines to design an integrated information system to improve citizens' participation in urban planning and mobility services.

Building Green Smart City Capabilities in South Sumatra, Indonesia

Information and communication technology is currently developing rapidly. It has created a great number of opportunities for governments worldwide to meet the demands of the public in providing services including environmentally friendly public services for the community and citizens. This study aims to present a case study on public services of South Sumatra government programs in order to develop a green smart city concept by combining smart city and green IT concepts which aim to align and incorporate green IT components, including pollution prevention, product stewardship, and clean technology into conceptual variants, essential elements, and strategic principles. A smart city is an innovative and modern concept utilising technology to facilitate and provide public information and to improve environmentally friendly public services through smart applications. South Sumatera is one of the provinces in Indonesia that has been implementing a smart city to provide environmentally friendly public services through the command centre. It is used to monitor an entire government agency’s activities and communicates with the public. To fulfil the aims of the study, this study identifies the comprehensive environmentally friendly public services through Natural Resource-Based View Theory perspectives. In addition, this study deploys in-depth interviews with sources or informants as a form of data search and direct observation. The number of informants used as research respondents consisted of several elements of the government, including the executive, legislative, and implementing agencies. The study reveals that the South Sumatera Government has several environmentally friendly public services that could be deployed to prevent pollution and reduce the emission in their activities. Further, the government in South Sumatra has product and service stewardships and invests in clean technology to minimise the adverse impacts of their activities on the environment.

Usage of V2X Applications in Road Tunnels

Many smart city applications work with calculated position and time using the Global Navigation Satellite System (GNSS) signals for enhanced precision. However, there are many places where the availability of GNSS is limited, e.g., road tunnels, which are an essential part of transport infrastructure. Tunnels also require greater attention and greater importance of approaches to ensure the safety and security aspects of traffic. The safety, distribution of information, awareness, and smooth traffic can also be ensured by V2X applications, but the current position is also needed. An experimental analysis of data connection and communication availability was performed in the Blanka tunnel (Prague) and its surroundings. The main objective of the work was to find and clearly describe the tunnel blind spots, with an emphasis on communication between cars and potentially between cars and infrastructure. This article summarizes the evaluation results of the V2X tunnel experimental test, the outputs from the analysis of these blind spots, and it provides a future perspective and suggestions that make tunnels smart by using advanced positioning approaches.

Musawah: A Data-Driven AI Approach and Tool to Co-Create Healthcare Services with a Case Study on Cancer Disease in Saudi Arabia

The sustainability of human existence is in dire danger and this threat applies to our environment, societies, and economies. Smartization of cities and societies has the potential to unite individuals and nations towards sustainability as it requires engaging with our environments, analyzing them, and making sustainable decisions regulated by triple bottom line (TBL). Poor healthcare systems affect individuals, societies, the planet, and economies. This paper proposes a data-driven artificial intelligence (AI) based approach called Musawah to automatically discover healthcare services that can be developed or co-created by various stakeholders using social media analysis. The case study focuses on cancer disease in Saudi Arabia using Twitter data in the Arabic language. Specifically, we discover 17 services using machine learning from Twitter data using the Latent Dirichlet Allocation algorithm (LDA) and group them into five macro-services, namely, Prevention, Treatment, Psychological Support, Socioeconomic Sustainability, and Information Availability. Subsequently, we show the possibility of finding additional services by employing a topical search over the dataset and have discovered 42 additional services. We developed a software tool from scratch for this work that implements a complete machine learning pipeline using a dataset containing over 1.35 million tweets we curated during September–November 2021. Open service and value healthcare systems based on freely available information can revolutionize healthcare in manners similar to the open-source revolution by using information made available by the public, the government, third and fourth sectors, or others, allowing new forms of preventions, cures, treatments, and support structures.

KnowMIS-ABSA: an overview and a reference model for applications of sentiment analysis and aspect-based sentiment analysis

The analysis of the opinions of customers and users has been always of great interest in supporting decision-making in many fields, especially in marketing. Sentiment analysis (SA) is the umbrella term for techniques and approaches that analyze user’s sentiments, emotions, opinions in text or other media. The need for a better understanding of these opinions paved the way to novel approaches that focus on the analysis of the sentiment related to specific features of a product, giving birth to the field of aspect-based sentiment analysis (ABSA). Although the increasing interest in this discipline, there is still confusion regarding the basic concepts of ABSA: terms like sentiment, affect, emotion, opinion, are used as synonyms while they represent different concepts. This often leads to an incorrect analysis of the users’ opinions.This work presents an overview of the state-of-the-art techniques and approaches for ABSA, highlighting the main critical issues related to current trends in this field. Following this analysis, a new reference model for SA and ABSA, namely the KnowMIS-ABSA model, is proposed. The model is grounded on the consideration that sentiment, affect, emotion and opinion are very different concepts and that it is profoundly wrong to use the same metric and the same technique to measure them. Accordingly, we argue that different tools and metrics should be adopted to measure each of the dimensions of an opinion. A qualitative case study, regarding product reviews, is proposed to motivate the advantages of the KnowMIS-ABSA model.

Using Deep Learning for Collecting Data about Museum Visitor Behavior

Nowadays, technology makes it possible to admire objects and artworks exhibited all over the world remotely. We have been able to appreciate this convenience even more in the last period, in which the pandemic has forced us into our homes for a long time. However, visiting art sites in person remains a truly unique experience. Even during on-site visits, technology can help make them much more satisfactory, by assisting visitors during the fruition of cultural and artistic resources. To this aim, it is necessary to monitor the active user for acquiring information about their behavior. We, therefore, need systems able to monitor and analyze visitor behavior. The literature proposes several techniques for the timing and tracking of museum visitors. In this article, we propose a novel approach to indoor tracking that can represent a promising and non-expensive solution for some of the critical issues that remain. In particular, the system we propose relies on low-cost equipment (i.e., simple badges and off-the-shelf RGB cameras) and harnesses one of the most recent deep neural networks (i.e., Faster R-CNN) for detecting specific objects in an image or a video sequence with high accuracy. An experimental evaluation performed in a real scenario, namely, the “Exhibition of Fake Art” at Roma Tre University, allowed us to test our system on site. The collected data has proven to be accurate and helpful for gathering insightful information on visitor behavior.

Analyzing the Evolution of Interdisciplinary Areas

Recently, various new areas of research have been of great interest to researchers. As these areas are highly based on academic and industrial needs, it is necessary to examine the change and evolution in research. This study proposed a framework for identifying emerging areas and their evolution. The proposed framework suggests that latent Dirichlet allocation is applied to identify emerging topics and their networks in such interdisciplinary areas. The simulation for empirical network analysis was then applied to the identified topic networks to terminate continuous evolution. The proposed framework is applied to a smart city, which is one of the most interdisciplinary and fast-evolving areas. These findings indicate that the evolution of smart transportation and smart grids is likely to be the focus. The findings also indicate that newly emerging research may lack openness and diversity. This study contributes to further investigate research trends and planning research strategies for new and interdisciplinary areas.

A Low Energy IoT Application Using Beacon for Indoor Localization

In recent years, a great number of applications in Internet of Things (IoT) have been developed. In this context, many methodologies and technologies are used for several frameworks, including indoor localization. In this field, as highlighted in recent years, one of the most important aims of modern indoor applications in IoT is to identify how to manage and correctly convey people flow. This study aims to investigate the most common methods, technologies and applications for indoor localization in IoT and analyze the major systems currently in use and the application of these solutions to actual conditions. Following this, we propose an innovative method to detect people flow in indoor location. Based on Bluetooth low energy (BLE) technology, in this paper we analyze the possibility to use our system for many kinds of applications. The first experimental results show good performance of our system.

Advanced Technologies and Their Use in Smart City Management

Building Smart City management concepts is based on the implementation and use of advanced technologies. The primary impulse for writing the article was the ambition to identify the current advanced technologies of Smart City management. The aim of the article is to propose a general model for the implementation of advanced technologies for Smart City management, based on the knowledge gained from the analysis of literature and case studies. In order to fulfill the set goal, it is necessary to obtain answers to two research questions. The findings were obtained through a secondary analysis of the literature, i.e., relevant articles from the scientific databases Web of Science and Scopus analysis of case studies of the best Smart Cities practices. According to the Smart City Index 2020 and IESE Cities in Motion, the leaders among the Smart Cities are Singapore and London, followed by Helsinki. In addition to the analyses, the article also uses methods of summarization, comparison, creativity, logic, induction and deduction. Smart Cities use 12 identified advanced technologies in their practice. Strategic management in Singapore, London and Helsinki adapts technology to the needs and requirements of its citizens, thus connecting the technological aspect with the managerial and social aspects. The contributions of the work include results for fellow researchers and a model for strategic management of new Smart Cities. The results of the article provide fellow researchers with the findings of a secondary analysis of relevant articles, from which they can draw when writing their own publications without the need for time-consuming search of the articles about this topic in databases. The general model of implementation of advanced technologies serves as a basis for strategic management of new Smart Cities that want to implement a technological base and at the same time do not want to forget the managerial and social aspects. Testing the model in practice with a new Slovak Smart City is part of future research activities.

Smart City Ontologies and Their Applications: A Systematic Literature Review

The increasing interconnections of city services, the explosion of available urban data, and the need for multidisciplinary analysis and decision making for city sustainability require new technological solutions to cope with such complexity. Ontologies have become viable and effective tools to practitioners for developing applications requiring data and process interoperability, big data management, and automated reasoning on knowledge. We investigate how and to what extent ontologies have been used to support smart city services and we provide a comprehensive reference on what problems have been addressed and what has been achieved so far with ontology-based applications. To this purpose, we conducted a systematic literature review finalized to presenting the ontologies, and the methods and technological systems where ontologies play a relevant role in shaping current smart cities. Based on the result of the review process, we also propose a classification of the sub-domains of the city addressed by the ontologies we found, and the research issues that have been considered so far by the scientific community. We highlight those for which semantic technologies have been mostly demonstrated to be effective to enhance the smart city concept and, finally, discuss in more details about some open problems.

A knowledge organization framework for influencing tourism-centered place-making

Purpose

This study demonstrates the synthesis of a knowledge organization framework from tourist reviews and an ontological model with its implementation in graph database, which is based on this framework. The aim is to influence place-making outcomes at tourist destinations.

Design/methodology/approach

The faceted classification approach has been used for generating and validating the framework based on online reviews about urban tourism parks. The framework was used to develop an ontology using Protégé ontology editor that was implemented using GraphDB.

Findings

Three fundamental facet categories, namely Component, Aspect and Outcome, each consisting of several sub-facets, were synthesized from the analyses of the reviews. Besides helping in constructing the ontology, the analysis also helped in calculating an importance-score for the reviews that helped in ranked information retrieval.

Research limitations/implications

The analyses of the reviews were done manually and may carry human bias. But it is robust as it is based on a canonical faceted methodology.

Practical implications

It is envisaged that this study will help tourist destination planners in decision-making by easing the utilization of tourist generated reviews by the knowledge management systems they use. Opinions of tourists will be induced in destination planning thereby helping in the production of quality “places.”

Originality/value

The presented faceted framework aims to specifically aid knowledge organization pertaining to online reviews related to tourist destinations. The focus is on organizing knowledge to facilitate tourism development for better place-making outcomes, which is an important area of research though it has little contributions.

IoT Technology Applications-Based Smart Cities: Research Analysis

The development of technologies enables the application of the Internet of Things (IoT) in urban environments, creating smart cities. Hence, the optimal management of data generated in the interconnection of electronic sensors in real time improves the quality of life. The objective of this study is to analyze global research on smart cities based on IoT technology applications. For this, bibliometric techniques were applied to 1232 documents on this topic, corresponding to the period 2011–2019, to obtain findings on scientific activity and the main thematic areas. Scientific production has increased annually, so that the last triennium has accumulated 83.23% of the publications. The most outstanding thematic areas were Computer Science and Engineering. Seven lines have been identified in the development of research on smart cities based on IoT applications. In addition, the study has detected seven new future research directions. The growing trend at the global level of scientific production shows the interest in developing aspects of smart cities based on IoT applications. This study contributes to the academic, scientific, and institutional discussion to improve decision making based on the available information.