Regarding Smart Cities in China, the North and Emerging Economies—One Size Does Not Fit All

Browne, Nigel J. W.

doi:10.3390/smartcities3020011

Cited by 10 publications

(9 citation statements)

References 54 publications

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“…Information and communication technologies intersect with the entire infrastructure of Smart Cities [45]. They penetrate the fields of smart mobility, energy, and services, enabling the efficient functioning of other technologies and creating opportunities for their mutual synergy [46,47]. At the same time, they themselves represent a tool for information and communication between the city or municipality management and citizens, as well as for improving the quality of decisions offering a positive impact on the overall quality of life of citizens and the economy [48].…”

Section: Citizens' Online Votingmentioning

confidence: 99%

The Concept of a Smart City Communication in the Form of an Urban Mobile Application

et al. 2021

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The current state of technological progress offers extensive opportunities for the development of urban infrastructure and the construction of Smart Cities, but the city will only become intelligent if it raises the living standards of all citizens in it. The Smart City uses information and communication technologies to improve its functionality and long-term sustainability and to increase the living standards of its citizens. In this context, it is necessary to address the issue of mutual communication between the city and the citizen and its implementation. The aim of the paper is to design a suitable smart solution that would streamline two-way communication between the city and its citizens. This solution is an urban mobile application, which is also a simple and yet sufficiently effective solution for the transformation of cities into Smart Cities. The main benefit is the implementation of research assessing the requirements of the citizens of a particular city for the services and functions that the application should offer. After analysing the results, a specific urban application design was processed using User Interface and User Interface design. The proposal consists of seven consecutive phases. All phases were completed in solving the design and the result can be seen in the resulting interactive prototype, which was finally tested by authors and random users representing all age categories. The results of the prototype usability tests enabled a gradual improvement of the solution, which culminated in the confirmation of its effectiveness.

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Section: Citizens' Online Votingmentioning

confidence: 99%

The Concept of a Smart City Communication in the Form of an Urban Mobile Application

et al. 2021

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“…Aiming for a technology-enabled city is fundamental [3]. The dominant research field for smart cities is ICT disciplines, such as computer science, engineering, electronics, and information systems [9]. These technological notions overlap with the meanings of the term 'smart,' defined as intelligent or knowledgeable [15,22].…”

Section: Characteristics Of Smart Citiesmentioning

confidence: 99%

Smart City Strategies—Technology Push or Culture Pull? A Case Study Exploration of Gimpo and Namyangju, South Korea

2020

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This study aims to address strategies, models, and the motivation behind smart cities by analyzing two smart city project cases in medium-sized cities, i.e., Gimpo and Namyangju in South Korea. The case of Smartopia Gimpo represents a top-down, infrastructure-focused smart city innovation that invested in building state-of-the-art big data infrastructure for crime prevention, traffic alleviation, environmental preservation, and disaster management. On the other hand, Namyangju 4.0 represents a strategy focused on internal process innovation through extensive employee training and education regarding smart city concepts and emphasizing data-driven (rather than infrastructure-driven) policy decision making. This study explores two smart city strategies and how they resulted in distinctively different outcomes. We found that instilling a culture of innovation through the training of government managers and frontline workers is a critical component in achieving a holistic and sustainable smart city transformation that can survive leadership changes.

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“…A wide range of sensors and IoT based applications data is being stored and processed in the digital infrastructure of the cities to support decision making [26]. With the change in tools and techniques on the digital platform, a variety of data from apps and other real-time data sources are combined to analyse and make a decision to address specific issues of the city [27]. There have been qualitative and quantitative data for decision making to meet some objectives, which often appear with conflict.…”

Section: Literature Reviewmentioning

confidence: 99%

Explainable Artificial Intelligence for Developing Smart Cities Solutions

et al. 2020

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Traditional Artificial Intelligence (AI) technologies used in developing smart cities solutions, Machine Learning (ML) and recently Deep Learning (DL), rely more on utilising best representative training datasets and features engineering and less on the available domain expertise. We argue that such an approach to solution development makes the outcome of solutions less explainable, i.e., it is often not possible to explain the results of the model. There is a growing concern among policymakers in cities with this lack of explainability of AI solutions, and this is considered a major hindrance in the wider acceptability and trust in such AI-based solutions. In this work, we survey the concept of ‘explainable deep learning’ as a subset of the ‘explainable AI’ problem and propose a new solution using Semantic Web technologies, demonstrated with a smart cities flood monitoring application in the context of a European Commission-funded project. Monitoring of gullies and drainage in crucial geographical areas susceptible to flooding issues is an important aspect of any flood monitoring solution. Typical solutions for this problem involve the use of cameras to capture images showing the affected areas in real-time with different objects such as leaves, plastic bottles etc., and building a DL-based classifier to detect such objects and classify blockages based on the presence and coverage of these objects in the images. In this work, we uniquely propose an Explainable AI solution using DL and Semantic Web technologies to build a hybrid classifier. In this hybrid classifier, the DL component detects object presence and coverage level and semantic rules designed with close consultation with experts carry out the classification. By using the expert knowledge in the flooding context, our hybrid classifier provides the flexibility on categorising the image using objects and their coverage relationships. The experimental results demonstrated with a real-world use case showed that this hybrid approach of image classification has on average 11% improvement (F-Measure) in image classification performance compared to DL-only classifier. It also has the distinct advantage of integrating experts’ knowledge on defining the decision-making rules to represent the complex circumstances and using such knowledge to explain the results.

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Regarding Smart Cities in China, the North and Emerging Economies—One Size Does Not Fit All

Cited by 10 publications

References 54 publications

The Concept of a Smart City Communication in the Form of an Urban Mobile Application

The Concept of a Smart City Communication in the Form of an Urban Mobile Application

Smart City Strategies—Technology Push or Culture Pull? A Case Study Exploration of Gimpo and Namyangju, South Korea

Explainable Artificial Intelligence for Developing Smart Cities Solutions

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