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Applied Sciences
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Emerging Technologies of Accident Analysis and Prevention in Safety Engineering
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Emerging Technologies of Accident Analysis and Prevention in Safety Engineering

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Civil Engineering".

Deadline for manuscript submissions: 20 August 2025 | Viewed by 3375

Special Issue Editors

Dr. Joana Duarte

E-Mail Website
Guest Editor
Associated Laboratory for Energy, Transports and Aeronautics (PROA-LAETA), Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal
Interests: accident analysis; accident prevention; occupational health and safety; safety engineering
Dr. Antonio José Carpio de los Pinos

E-Mail Website
Guest Editor
Departamento de Construcciones Arquitectónicas y su Control, Escuela Técnica Superior de Edificación, Universidad Politécnica de Madrid, 28040 Madrid, Spain
Interests: health and safety; risk assessment; building construction; work site; risk perception; emotional state
Dr. Fernanda Rodrigues

E-Mail Website
Guest Editor
RISCO, Civil Engineering Department, University of Aveiro, 3810-193 Aveiro, Portugal
Interests: energy efficiency; BIM; buildings degradation assessment; buildings conservation and maintenance
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

A safe and healthy working environment engages with the prevention of work-related injuries while promoting the health and safety of its workers. While new light was brought to the fundamental rights of workers, the World Health Organization (WHO) estimates that over 2 million workers die from occupational accidents and work-related diseases every year, whereas 374 million workers suffer from non-fatal occupational accidents. Recent technological advances have allowed industry to be reshaped and concepts such as Industry 4.0, Big Data and Artificial Intelligence to become part of our daily lives. However, how they can improve working conditions and contribute to reducing accidents is not fully addressed. This Special Issue aims to publish papers that study the emerging technologies of accident analysis and accident prevention in safety engineering. Topics of interest include, but are not limited to, the following:

  • Occupational risk assessment; 
  • Occupational risk management;
  • Occupational accidents analysis;
  • Occupational health and safety;
  • Cognitive ergonomics;
  • Mental and physical fatigue;
  • Training;
  • Sensors and monitoring.

Dr. Joana Duarte
Dr. Antonio José Carpio de los Pinos
Dr. Fernanda Rodrigues
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. Applied Sciences 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 2400 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

  • occupational accidents
  • occupational risks
  • occupational health and safety
  • risk assessment
  • risk management
  • cognitive ergonomics
  • safety training
  • monitoring
  • sensors
  • artificial intelligence
  • big data
  • virtual reality
  • augmented reality

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Published Papers (2 papers)

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17 pages, 5564 KiB  
Article
Internal Observation Method of Temporary Structures Covered with a Construction Safety Net Using Image Processing and Unmanned Aerial Vehicles (UAVs)
by Min-Guk Kang, Seung-Hyeon Shin, Hyeon-Ji Jeong and Jeong-Hun Won
Appl. Sci. 2025, 15(3), 1488; https://doi.org/10.3390/app15031488 - 31 Jan 2025
Viewed by 780
Abstract
This study proposes a method for observing the inside of a temporary structure covered with a construction safety net using an image processing technique and 3D modeling. Images of the temporary structures were obtained using unmanned aerial vehicles (UAVs). Observing the inside of [...] Read more.
This study proposes a method for observing the inside of a temporary structure covered with a construction safety net using an image processing technique and 3D modeling. Images of the temporary structures were obtained using unmanned aerial vehicles (UAVs). Observing the inside of temporary structures is limited to using UAVs due to construction safety nets that act as obstacles. To solve this problem, the histogram equalization and grayscale stretching techniques were used to visualize the inside of a temporary structure covered by safety nets. After verifying the proposed method with small scale specimens, the proposed method was applied to climbing formwork installed at a construction site. Three-dimensional modeling technique was combined with improved images that were processed using the proposed method. The results indicated that the proposed method could identify internal objects that were not visible owing to safety nets. By comparing the original and improved images obtained through applying the proposed method, four target objects located inside the climbing formwork that were not visible owing to safety nets were sufficiently identified in the improved images. Thus, the proposed method can be effectively applied to identify the internal objects of temporary structures covered with safety nets. Full article
(This article belongs to the Special Issue Emerging Technologies of Accident Analysis and Prevention in Safety Engineering)
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Other

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19 pages, 2961 KiB  
Systematic Review
BIM for Safety: Applying Real-Time Monitoring Technologies to Prevent Falls from Height in Construction
by Filipa Pereira, María de las Nieves González García and João Poças Martins
Appl. Sci. 2025, 15(4), 2218; https://doi.org/10.3390/app15042218 - 19 Feb 2025
Viewed by 1943
Abstract
There are significant risks in the construction sector, with falls from height identified a greater hazard than in most other industries. Efforts to improve working conditions and reduce accident rates have driven research into real-time monitoring technologies to reduce the risk of falls. [...] Read more.
There are significant risks in the construction sector, with falls from height identified a greater hazard than in most other industries. Efforts to improve working conditions and reduce accident rates have driven research into real-time monitoring technologies to reduce the risk of falls. The main objective of this research is to review existing real-time monitoring technologies, identify the most relevant, and analyse their benefits and impact on reducing workplace accidents in the construction sector. A systematic review was conducted using PRISMA methodology to investigate the use of real-time monitoring technologies in the construction industry. Only studies specifically investigating real-time fall risk assessment were included. Of the initial 446 articles reviewed, 39 were considered highly relevant to the research objectives. Various wireless and computer vision technologies were identified for real-time worker monitoring, often integrated with BIM to improve workplace safety. The findings suggest that a combination of technologies may produce more effective results for worker monitoring. However, further research is needed to verify the applicability of these technologies on construction sites. Full article
(This article belongs to the Special Issue Emerging Technologies of Accident Analysis and Prevention in Safety Engineering)
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