Advanced Geospatial Applications for Smart Cities and Knowledge Discovery from Urban Data

A special issue of Smart Cities (ISSN 2624-6511). This special issue belongs to the section "Applied Science and Humanities for Smart Cities".

Deadline for manuscript submissions: closed (30 November 2021) | Viewed by 6343

Special Issue Editors


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Guest Editor
Head of Department of Cartography, Warsaw University of Technology, 00-661 Warszawa, Poland
Interests: smart city; spatial data mining; machine learning; cartographic modeling; social geoparticipation; GIS; serious games

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Guest Editor
Center for Sensing Solutions, Eurac Research, Bolzano, 39100, Italy
Interests: visual analytics; spatial data mining; predictive analysis; IoT; data ecosystems; spatio-temporal uncertainty

Special Issue Information

Dear Colleagues,

The concept of a Smart City plays an essential role in various aspects of socioeconomic life. It has become an “effective integration of physical, digital and human systems in the built environment to deliver a sustainable, prosperous and inclusive future for its citizens” (BSI, 2014). Rapid urbanization and advanced sensing techniques provide a unique opportunity for the urban population to transform the traditional ways of decision-making by adopting geospatial IoT infrastructure, cloud computing, machine learning-based analytics, and cloud storage. In a smart city, public issues are solved using information and communication technologies (ICT) with the engagement of various stakeholders who act in partnership with the city authorities (Manville et al., 2014).

The purpose of this Special Issue is an in-depth discussion on the process of transforming “raw” urban data into valuable knowledge that supports progress in shaping smart cities and improves living standards. The monograph aims to present state-of-the-art development and use of advanced geospatial methods for smart city applications and spatial knowledge extractions based on urban data collected from various sources. The Special Edition will publish both innovative concepts of geoinformation applications and recent developments in geospatial knowledge extraction obtained from different Smart City data sources, including urban sensor networks and social sensing (VGI).

The editors call for papers focused on the methods and applications of knowledge discovery from data (KDD) for Smart Cities in such sectors as transportation, health, energy, and social interaction. We welcome submissions that embrace smart city ideas and contribute to improving citizens’ well-being through geospatial data-driven solutions. We are particularly interested in papers focused on developing and using Big Data analytics, spatial data mining, fuzzy inference systems, Artificial Intelligence methods, deep learning, MAS, and other knowledge acquisition methods.

Topics of interest include but are not limited to:

  • Spatial and spatiotemporal data analysis;
  • Spatial data mining methods and algorithms;
  • Spatial data infrustructure for Smart City services;
  • Visual analytics solutions for Smart Cities;
  • Statistical data analysis and characterization;
  • Large-scale data management and analysis applied to Smart Cities;
  • IoT data analytics for Smart Cities.

Dr. Robert Olszewski
Dr. Ekaterina Chuprikova
Guest Editors

Manuscript Submission Information

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. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short 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 thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Smart Cities is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Smart City
  • geospatial application
  • spatial data mining
  • machine learning
  • spatial knowledge acquisition
  • social geoparticipation
  • IoT

Published Papers (2 papers)

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Research

13 pages, 495 KiB  
Article
Bauhaus.MobilityLab: A Living Lab for the Development and Evaluation of AI-Assisted Services
by Carsten Frey, Philipp Hertweck, Lucas Richter and Oliver Warweg
Smart Cities 2022, 5(1), 133-145; https://0-doi-org.brum.beds.ac.uk/10.3390/smartcities5010009 - 07 Feb 2022
Cited by 4 | Viewed by 2746
Abstract
With the vision “Innovation by experiment” the Bauhaus.MobilityLab started in July 2020 as a living lab in the district Brühl of the city Erfurt, Thuringia, Germany. As a unique project, it is coupling the sectors mobility, logistics and energy into a unified living [...] Read more.
With the vision “Innovation by experiment” the Bauhaus.MobilityLab started in July 2020 as a living lab in the district Brühl of the city Erfurt, Thuringia, Germany. As a unique project, it is coupling the sectors mobility, logistics and energy into a unified living lab. It allows to design, develop and evaluate innovative services to increase the quality of life in the city. Bauhaus.MobilityLab offers access to live smart city data of different domains and provides a set of powerful artificial intelligence (AI) algorithms for data processing, analytics and forecasting. In contrast to existing platforms, its uniqueness is the available and integrated living lab. It allows directly rolling out new smart city services and to evaluate the impact in the real world. This paper describes the implementation of the technical platform supporting the Bauhaus.MobilityLab, realized according to the DIN SPEC 91357 as an open urban platform. It focuses on data sharing based on the concepts of the International Data Spaces and the integration of AI algorithms. The concepts are presented based on examples in the energy domain. Full article
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17 pages, 4162 KiB  
Article
Fixed and Mobile Low-Cost Sensing Approaches for Microclimate Monitoring in Urban Areas: A Preliminary Study in the City of Bolzano (Italy)
by Silvia Croce and Stefano Tondini
Smart Cities 2022, 5(1), 54-70; https://0-doi-org.brum.beds.ac.uk/10.3390/smartcities5010004 - 08 Jan 2022
Cited by 7 | Viewed by 2989
Abstract
In the current scenario of massive urbanization and global climate change, an intelligent monitoring of the environmental variables is becoming fundamental to ensure good living conditions in cities. Indeed, the acquisition of data with high spatiotemporal resolution can enable the assessment of environmental [...] Read more.
In the current scenario of massive urbanization and global climate change, an intelligent monitoring of the environmental variables is becoming fundamental to ensure good living conditions in cities. Indeed, the acquisition of data with high spatiotemporal resolution can enable the assessment of environmental vulnerabilities in urban areas towards the definition of responsive adaptation and mitigation strategies. In this context, the current work presents a two-fold approach based on low-cost cloud-connected sensors for (i) fixed and (ii) mobile monitoring of several environmental parameters. This paper, which focuses on the measurement aspects of the urban micro-climate, describes in detail the hardware and software components of both approaches, and how to exploit them for setting up a field campaign. The methods were tested in the city of Bolzano (Italy), demonstrating their suitability for identifying the spatial variability of the microclimate in relation to the urban morphology, and for highlighting the presence of the urban heat island and estimating its intensity. Full article
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