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Special Issue "Sensors Application on Early Warning System"

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

Deadline for manuscript submissions: 15 September 2019

Special Issue Editors

Guest Editor
Dr. Stefan Poslad

IoT2US Lab Director, Queen Mary University of London Mile End Road, London, E1 4NS, UK
Website | E-Mail
Interests: internet of things, Ubiquitous Computing, Sensors, Location-Awareness, GIS, AI, Distributed Systems, (including security privacy and resilience) and Data Science
Guest Editor
Dr. Stuart E. Middleton

University of Southampton, Electronics and Computer Science. IT Innovation Centre, Gamma House, Enterprise Road, Southampton, SO16 7NS, UK
Website | E-Mail
Interests: computational linguistics, information extraction, social media analytics, user-generated content, volunteer geographic information, semantics, sensor fusion, decision support systems
Guest Editor
Dr. Öcal Necmioğlu

Regional Earthquake and Tsunami Monitoring Center, Kandilli Observatory and Earthquake Research Institute, Boğaziçi University, Istanbul-Turkey
Website | E-Mail
Interests: tsunami and earthquake early warning, tsunami hazard-risk assessment, tsunami preparedness-mitigation

Special Issue Information

Dear Colleagues,

The focus and scope of this Special Issue (SI) is on advances in sensor applications for Early Warning Systems (EWS).

EWS are a core type of information system used for a wide range of applications including environmental disaster risk management, command and control centres for emergency responses, intelligence analysis during criminal and terrorist events and prediction, and warning or infrastructure failures of critical infrastructure such as transport systems.

EWS help prevent loss of life and/or reduces the economic and material impact of events such as disasters or major infrastructure failures.

A complete EWS is distinct from other types of ICT monitoring systems in that it supports four main functions: (1) risk analysis of predefined hazards and vulnerabilities, (2) monitoring and warning by means of relevant parameters used for forecasts to generate accurate and timely warnings, (3) dissemination, sensemaking, and communication of risk information and warnings to those at risk, and (4) response capability built upon response plans that leverage local capabilities and preparation with regard to warnings.

This SI targets innovations that support any of these four EWS functions. It concerns new system algorithms, models, and designs to integrate these four functions based upon Internet of Things, web and semantic web, cyber physical systems, autonomous distributed systems, user-generated content and citizen science, etc.It includes new methods and designs for EWS processes including risk analysis and security, Web simulation, sensor data acquisition, user-generated content acting as a data feed, EWS data fusion, data analytics, and data science and data visualisation for decision support. Although early warning systems have been traditionally targeted to physical environment disaster applications, they are increasingly being deployed to detect and warn people about a wider range of events, such as vehicular collisions, train track failures, disease outbreaks, and security threats at critical sites such as airports. Such applications are also applicable to this SI.

Dr. Stefan Poslad
Dr. Stuart E. Middleton
Dr. Öcal Necmioğlu
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 papers will be 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 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.

Keywords

  • Early warning system
  • Internet of Things
  • Cyber physical system
  • Distributed system
  • Risk management
  • Environment sensing
  • User generated content
  • Citizen Science

Published Papers (1 paper)

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Research

Open AccessArticle Robust Construction Safety System (RCSS) for Collision Accidents Prevention on Construction Sites
Sensors 2019, 19(4), 932; https://doi.org/10.3390/s19040932
Received: 15 January 2019 / Revised: 13 February 2019 / Accepted: 19 February 2019 / Published: 22 February 2019
PDF Full-text (11434 KB) | HTML Full-text | XML Full-text
Abstract
A proximity warning system to detect the presence of a worker/workers and to warn heavy equipment operators is highly needed to prevent collision accidents at construction sites. In this paper, we developed a robust construction safety system (RCSS), which can activate warning devices [...] Read more.
A proximity warning system to detect the presence of a worker/workers and to warn heavy equipment operators is highly needed to prevent collision accidents at construction sites. In this paper, we developed a robust construction safety system (RCSS), which can activate warning devices and automatically halt heavy equipment, simultaneously, to prevent possible collision accidents. The proximity detection of this proposed system mainly relies on ultra-wideband (UWB) sensing technologies, which enable instantaneous and simultaneous alarms on (a) a worker’s personal safety (personal protection unit (PPU)) device and (b) hazard area device (zone alert unit (ZAU)). This system also communicates with electronic control sensors (ECSs) installed on the heavy equipment to stop its maneuvering. Moreover, the RCSS has been interfaced with a global positioning system communication unit (GCU) to acquire real-time information of construction site resources and warning events. This enables effective management of construction site resources using an online user interface. The performance and effectiveness of the RCSS have been validated at laboratory scale as well as at real field (construction site and steel factory). Conclusively, the RCSS can significantly enhance construction site safety by pro-actively preventing collision of a worker/workers with heavy equipment. Full article
(This article belongs to the Special Issue Sensors Application on Early Warning System)
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