Special Issue "Smart Government in Smart Cities"
A special issue of Informatics (ISSN 2227-9709).
Deadline for manuscript submissions: 15 July 2017
This Special Issue of Informatics welcomes submissions on the topic of smart technologies and their applications to public administration in Smart Cities. In the early 21st century, the use of information and communication technologies (usually ICTs) and data has been considered as the means to solve the city’s economic, social and environmental challenges and it has been thought to rationalize and improve government because it has the potential to transform governance and organizational issues. Under this framework, the Smart Cities concept has gained a lot of attention, but studies about Smart Cities have been focused mainly on business-led urban development, on the social inclusion agenda, on the role of creative industries in urban growth, on the importance of social capital in urban development and on the urban sustainability. This special issue should contribute to the literature by filling the existing void and expanding knowledge in the field of the implementation of smart technologies into public administration in different fields, such as the improvement of transparency, efficiency (in public services, in sustainability, in mobility into a municipality, etc.), governance in a smart city, as well as the study of organizational issues arisen by these implementations. Therefore, I encourage authors to submit their original research articles, work in progress, surveys, reviews, and viewpoint articles in this field. This Special Issue welcomes applications, theories, models, and frameworks—whether conceptual, analytical, prescriptive, predictive, design-related, or otherwise—that are concerned with (but not limited to) the following topics:
- Smart technologies implemented in public sector entities for improving transparency and interoperability (open data, disclosure of information, etc.).
- Smart technologies implemented in public sector entities for improving efficiency (in the delivery of public sector services, in smart mobility, in smart environment, and in smart living).
- Smart technologies implemented in public sector entities for improving governance of the city.
- Organizational issues in the implementation of smart technologies in public sector entities.
- Comparative studies on smart technologies implemented in public sector entities.
- Empirical analysis on smart technologies and their best fit for public administrations in making Smart Cities to be successful.
Prof. Dr. Manuel Pedro Rodríguez Bolívar
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Informatics is an international peer-reviewed Open Access quarterly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. For the first couple of issues the Article Processing Charge (APC) will be waived for well-prepared manuscripts. English correction and/or formatting fees of 250 CHF (Swiss Francs) will be charged in certain cases for those articles accepted for publication that require extensive additional formatting and/or English corrections.
- Smart Governance
- Smart Cities
- Smart technologies
- Smart Governments
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Fusion of Crowd-Sourcing and Smart Sensing for Flood Mapping in Coastal Mega-Cities
Authors: P. Perez, M. Berryman, R. Ogie and R. Clarke
Title: Reinforcement Machine Learning for Predictive Analytics in Smart
Authors: Kostas Kolomvatsos (University of Thessaly); Christos
Anagnostopoulos (University of Glasgow)
Abstract: The digitization of our lives cause a shift in the data
production as well as in the required data management. Numerous nodes
are capable of producing huge volumes of data in our everyday
activities. Sensors, personal smart devices as well as the Internet of
Things (IoT) paradigm lead to a vast infrastructure that covers all the
aspects of activities in modern societies. In the most of the cases, the
critical issue for public authorities (usually, local like
municipalities) is the efficient management of data towards the support
of novel services. The reason is that analytics provided on top of the
collected data could help in the delivery of new applications that will
facilitate citizens' lives. However, the provision of analytics demands
intelligent techniques for the underlying data management. The most
known technique is the separation of huge volumes of data into a number
of parts and their parallel management to limit the required time for
the delivery of analytics. Afterwards, analytics requests in the form of
queries could be realized and derive the necessary knowledge for
supporting intelligent applications. In this paper, we define the
concept of a Query Controller (QC) that receives queries for analytics
and assigns each of them to a processor placed in front of each data
partition. We discuss an intelligent process for query assignments that
adopts Machine Learning (ML). We adopt two learning schemes, i.e.,
Reinforcement Learning (RL) and clustering. We report on the comparison
of the two schemes and elaborate on their combination. Our aim is to
provide an efficient framework to support the decision making of the QC
that should swiftly select the appropriate processor for each query. We
provide mathematical formulations for the discussed problem and present
simulation results. Through a comprehensive experimental evaluation, we
reveal the advantages of the proposed models and describe the outcomes
results while comparing them with a deterministic framework.