The Internet of Things (IoT) paradigm is establishing itself as a technology to improve data acquisition and information management in the construction field. It is consolidating as an emerging technology in all phases of the life cycle of projects and specifically in the execution phase of a construction project. One of the fundamental tasks in this phase is related to Health and Safety Management since the accident rate in this sector is very high compared to other phases or even sectors. For example, one of the most critical risks is falling objects due to the peculiarities of the construction process. Therefore, the integration of both technology and safety expert knowledge in this task is a key issue including ubiquitous computing, real-time decision capacity and expert knowledge management from risks with imprecise data. Starting from this vision, the goal of this paper is to introduce an IoT infrastructure integrated with JFML, an open-source library for Fuzzy Logic Systems according to the IEEE Std 1855-2016, to support imprecise experts' decision making in facing the risk of falling objects. The system advises the worker of the risk level of accidents in real-time employing a smart wristband. The proposed IoT infrastructure has been tested in three different scenarios involving habitual working situations and characterized by different levels of falling objects risk. As assessed by an expert panel, the proposed system shows suitable results.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8511994 | PMC |
| http://dx.doi.org/10.3390/s21196461 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Fall rates in bifocal, trifocal, and progressive addition lens glasses wearers.
Optom Vis Sci
January 2025
Department of Aged Care and Rehabilitation, Royal North Shore Hospital, Sydney, New South Wales, Australia.
Purpose: There is evidence that wearing multifocal glasses increases the risk of falls in older people, especially when walking on stairs and in unfamiliar settings. However, it is not clear whether all types of multifocal glasses are equally associated with falls. This study comprised a secondary analysis of data from the VISIBLE randomized controlled trial to determine whether fall rates differ among older bifocal, trifocal, and progressive addition lens glasses wearers.
View Article and Find Full Text PDFDenseSeg: joint learning for semantic segmentation and landmark detection using dense image-to-shape representation.
Int J Comput Assist Radiol Surg
January 2025
Medical Informatics, University of Lübeck, Ratzeburger Allee 160, 23562, Lübeck, Germany.
Purpose: Semantic segmentation and landmark detection are fundamental tasks of medical image processing, facilitating further analysis of anatomical objects. Although deep learning-based pixel-wise classification has set a new-state-of-the-art for segmentation, it falls short in landmark detection, a strength of shape-based approaches.
Methods: In this work, we propose a dense image-to-shape representation that enables the joint learning of landmarks and semantic segmentation by employing a fully convolutional architecture.
A hybrid human fall detection method based on modified YOLOv8s and AlphaPose.
Sci Rep
January 2025
Human-Computer Collaborative Robot Joint Laboratory of Anhui Province, Huainan, China.
To address the challenges of low detection accuracy of small objects and weak applicability of the multi-person fall action recognition applications, we propose a hybrid fall detection method based on modified YOLOv8s and AlphaPose called HFDMIA-Pose. Firstly, we use the modified Yolov8s as object detector. It uses SPD-Conv to preserve small object features and adds a small object detection layer, while using BCIOU as the loss function.
View Article and Find Full Text PDFFunctional neurological disorder treated with psychoeducation: A case report.
Medicine (Baltimore)
January 2025
Psychiatry Section, Department of Medicine, King Abdulaziz Medical City, Ministry of the National Guard Health Affairs, King Abdullah International Medical Research Center, College of Medicine, King Saud Bin Abdulaziz University for Health Sciences, Jeddah, Saudi Arabia.
Rationale: Psychogenic tremor (PT) is the most common subtype of psychogenic movement disorder, characterized by involuntary movement, and is usually related to occupational injuries or accidents. Psychogenic movement disorder falls under the category of functional neurological disorders, which are diagnosed based on the criteria outlined in the Diagnostic and Statistical Manual of Mental Disorders.
Patient Concerns: A 25-year-old Saudi male with a history of recurrent superior ventricular tachycardia presented to the emergency department with tremors affecting all his extremities for 8 days.
SDES-YOLO: A high-precision and lightweight model for fall detection in complex environments.
Sci Rep
January 2025
College of Intelligence and Computing, Tianjin University, Tianjin, 300000, China.
Falling is an emergency situation that can result in serious injury or even death, especially in the absence of immediate assistance. Therefore, developing a model that can accurately and promptly detect falls is crucial for enhancing quality of life and safety. In the field of object detection, while YOLOv8 has recently made notable strides in detection accuracy and speed, it still faces challenges in detecting falls due to variations in lighting, occlusions, and complex human postures.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!