sensors-logo

Journal Browser

Journal Browser

Smart City Alert: Systems for Prevention and Detection of Disasters

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: closed (30 September 2024) | Viewed by 833

Special Issue Editors


E-Mail Website
Guest Editor
Department of Information Engineering (DII), Università Politecnica delle Marche, 60131 Ancona, Italy
Interests: embedded device development; electronic devices; embedded AI; Internet of Things
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Institute of High Performance Computing and Networking, National Research Council of Italy, 80131 Naples, Italy
Interests: predicted models based on machine learning and deep learning; training of deep-learning-based models; training of intelligent agents based on reinforcement learning methods
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The most vulnerable elements influencing both human life and the environment are disasters. Smart cities are mainly affected by disasters. This demonstrates the need for effective disaster management systems in urban areas.

Smart city alert systems integrate cutting-edge technologies to track a variety of variables, including weather conditions, environmental factors, and the condition of the infrastructure, in order to forecast and avoid possible disasters.

These novel platforms utilize machine learning and artificial intelligence (AI) to analyze prior data and predict disaster patterns.

With the ability to process vast amounts of data collected from sensors, satellites, and other sources, machine learning algorithms are increasingly becoming a powerful tool for smart city alert systems to identify potential vulnerabilities and predict failures in real time.

In addition, a smart city can provide city authorities with a comprehensive view of potential risks, enabling them to make informed decisions and take proactive measures to protect residents and infrastructure.

They represent a critical step in developing resilient, flexible, and sustainable urban environments, where technology plays a significant role in enhancing disaster preparedness and response, eventually ensuring the safety and well-being of urban populations.

For this Special Issue, we aim to present a collection of review and original research articles related to the latest technologies on the most recent developments in disaster detection and prevention systems, such as smart sensors, artificial intelligence-based damage identification, infrastructure disaster prediction, and early warnings for infrastructure safety.

Dr. Lorenzo Palma
Dr. Giovanni Paragliola
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. Sensors 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 2600 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 cities
  • smart sensors
  • disaster prediction
  • disaster prevention
  • structural health monitoring
  • sensor signal processing
  • intelligent systems
  • machine learning and deep learning

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

12 pages, 848 KiB  
Article
R-RDSP: Reliable and Rapidly Deployable Wireless Ad Hoc System for Post-Disaster Management over DDS
by Baber Jan, Adnan Munir, Ayaz H. Khan, Ajmal Khan and Basem Al-Madani
Sensors 2024, 24(22), 7259; https://doi.org/10.3390/s24227259 - 13 Nov 2024
Viewed by 457
Abstract
After natural disasters such as earthquakes, floods, or wars occur, cellular communication networks often sustain significant damage or become impaired. In these critical situations, first responders must coordinate with other rescue teams to communicate essential information to central command and survivors. To address [...] Read more.
After natural disasters such as earthquakes, floods, or wars occur, cellular communication networks often sustain significant damage or become impaired. In these critical situations, first responders must coordinate with other rescue teams to communicate essential information to central command and survivors. To address this challenge, we have developed a reliable and rapidly deployable wireless ad hoc system for post-disaster management using Data Distribution Service (DDS) middleware, specifically RTI-DDS, named R-RDSP. The R-RDSP further enhances these metrics, achieving a 14.5% improvement in end-to-end delay and a 20.24% improvement in round-trip delay over the RDSP scheme. The R-RDSP system consists of three main modules: client, relay, and server. Each module connects to others via an ad hoc network, ensuring direct device-to-device communication without relying on existing infrastructure. The client module collects and sends the victim’s location and emergency messages. The relay modules forward these messages across the ad hoc networks, ensuring minimal delay and high reliability. Finally, the server module receives the messages, processes them, and coordinates the response. Leveraging RTI-DDS for reliable message distribution, the system demonstrates robust performance even under challenging network conditions. Full article
(This article belongs to the Special Issue Smart City Alert: Systems for Prevention and Detection of Disasters)
Show Figures

Figure 1

Back to TopTop