Artificial Intelligence and Sensor Informatics: Exploring Smart City and Construction Business Implications

A special issue of Informatics (ISSN 2227-9709).

Deadline for manuscript submissions: closed (30 June 2020) | Viewed by 5680

Special Issue Editors


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Guest Editor
City Futures Research Centre, School of Built Environment, University of New South Wales, Sydney, Kensington, NSW 2052, Australia
Interests: sensing technologies; AI; machine learning; advanced GIS; BIM; digital twins; city analytics methods; digital construction; smart cities; smart construction
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Guest Editor
School of Computer Science and Engineering, University of New South Wales, Sydney, NSW 2052, Australia
Interests: artificial intelligence not elsewhere classified; computer vision; pattern recognition; machine learning; deep learning; image processing

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Guest Editor
School of Built Environment, UNSW Sydney, Sydney, NSW 1466, Australia
Interests: sustainability; energy efficiency; artificial intelligence; smart city; digital twin; applications of the internet of things; advanced GIS; LiDAR; BIM; digital technology in infrastructure; mixed reality applications; information and communication technology; spatial analysis and visualization; authentic education
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Artificial Intelligence and Sensor Informatics (AI&SI) are developing quickly and will become an essential part of smart cities and the construction industries and business. Current studies predict that the number of digital devices will increase from 25 billion in 2017 to 100 billion in 2025. However, the implications of AI&SI have not been fully examined in the context of smart cities, infrastructure, and construction (SCIC). SCIC needs to be managed, monitored, and maintained over time, so there is a need to develop the data infrastrucure to collect data, learn from the data, and identify patterns. In megacities, a wide range of technologies are being used, including water sensitivity monitoring sensors, surveillance cameras, smart traffic control systems, construction monitoring systems, and building sensors for post-occupancy management. Current studies predict that metropolitan populations will increase by 60% by 2050, and over 30 megacities will be developed in different countries, including Latin America, Russia, China, and India. This will provide an opportunity to utilise AI&SI widely to increase the productivity, liveability, and sustainability of cities, including infrastructure and construction projects.

AI&SI includes a wide range of technologies and methods that can be employed to understand the data, explore patterns, and predict events, properties, and features of any phenomenon and system at different scales such as a city, urban transportation, construction or project. This Special Issue welcomes submissions from diverse disciplines including research projects with different approaches, including quantitative, computational, visual analytics, data mining, analysis of spatial and morphological structure of cities, urban transportation and construction systems and activities. We encourage authors to develop or clarify the implications of the following topics and technologies in smart cities, infrastructure, and construction.

Topics:

  • Computer vision and image processing;
  • Knowledge representation and management;
  • Expert systems and knowledge-based systems;
  • Vision sensor system and Artificial Intelligence;
  • Geospatial Artificial Intelligence (GAI);
  • Data infrastructure;
  • Internet informatics and cloud-based Internet of Things (IoT) applications;
  • Deep learning and machine learning;
  • Robotics and information systems;
  • Digital infrastructure;
  • Spatial metadata;
  • Big Data analytics for data processing;
  • Intelligent real-time algorithms;
  • AI in security, privacy, and trust in smart systems;
  • Human–computer interaction;
  • Global sensor deployment case studies;
  • Applications and implications of all above topics in smart cities, infrastructure and construction, and case studies.

Dr. Sara Shirowzhan
Prof. Dr. Arcot Sowmya
Dr. Samad Sepasgozar
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. Informatics is an international peer-reviewed open access quarterly 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 1800 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.

Published Papers (1 paper)

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Research

17 pages, 3059 KiB  
Article
Improving Smart Cities Safety Using Sound Events Detection Based on Deep Neural Network Algorithms
by Giuseppe Ciaburro and Gino Iannace
Informatics 2020, 7(3), 23; https://0-doi-org.brum.beds.ac.uk/10.3390/informatics7030023 - 20 Jul 2020
Cited by 52 | Viewed by 4935
Abstract
In recent years, security in urban areas has gradually assumed a central position, focusing increasing attention on citizens, institutions and political forces. Security problems have a different nature—to name a few, we can think of the problems deriving from citizens’ mobility, then move [...] Read more.
In recent years, security in urban areas has gradually assumed a central position, focusing increasing attention on citizens, institutions and political forces. Security problems have a different nature—to name a few, we can think of the problems deriving from citizens’ mobility, then move on to microcrime, and end up with the ever-present risk of terrorism. Equipping a smart city with an infrastructure of sensors capable of alerting security managers about a possible risk becomes crucial for the safety of citizens. The use of unmanned aerial vehicles (UAVs) to manage citizens’ needs is now widespread, to highlight the possible risks to public safety. These risks were then increased using these devices to carry out terrorist attacks in various places around the world. Detecting the presence of drones is not a simple procedure given the small size and the presence of only rotating parts. This study presents the results of studies carried out on the detection of the presence of UAVs in outdoor/indoor urban sound environments. For the detection of UAVs, sensors capable of measuring the sound emitted by UAVs and algorithms based on deep neural networks capable of identifying their spectral signature that were used. The results obtained suggest the adoption of this methodology for improving the safety of smart cities. Full article
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