scholarly journals Using Synthetic Data to Improve and Evaluate the Tracking Performance of Construction Workers on Site

2020 ◽  
Vol 10 (14) ◽  
pp. 4948
Author(s):  
Marcel Neuhausen ◽  
Patrick Herbers ◽  
Markus König
Keyword(s):  
Real World ◽  
Safety Management ◽  
Tracking System ◽  
Synthetic Data ◽  
Tracking Systems ◽  
Construction Sites ◽  
Virtual Construction ◽  
Percentage Points ◽  
Video Frames ◽  
Graphics Software

Vision-based tracking systems enable the optimization of the productivity and safety management on construction sites by monitoring the workers’ movements. However, training and evaluation of such a system requires a vast amount of data. Sufficient datasets rarely exist for this purpose. We investigate the use of synthetic data to overcome this issue. Using 3D computer graphics software, we model virtual construction site scenarios. These are rendered for the use as a synthetic dataset which augments a self-recorded real world dataset. Our approach is verified by means of a tracking system. For this, we train a YOLOv3 detector identifying pedestrian workers. Kalman filtering is applied to the detections to track them over consecutive video frames. First, the detector’s performance is examined when using synthetic data of various environmental conditions for training. Second, we compare the evaluation results of our tracking system on real world and synthetic scenarios. With an increase of about 7.5 percentage points in mean average precision, our findings show that a synthetic extension is beneficial for otherwise small datasets. The similarity of synthetic and real world results allow for the conclusion that 3D scenes are an alternative to evaluate vision-based tracking systems on hazardous scenes without exposing workers to risks.

Cyber physical system for safety management in smart construction site

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Weiguang Jiang ◽  
Lieyun Ding ◽  
Cheng Zhou
Keyword(s):  
Construction Industry ◽  
Physical System ◽  
Safety Management ◽  
Data Communication ◽  
Cyber Physical System ◽  
Construction Site ◽  
Construction Sites ◽  
Design Data ◽  
Content Type ◽  
Virtual Construction

PurposeConstruction safety has been a long-term problem in the development of the construction industry. An increasing number of smart construction sites have been designed using different techniques to reduce injuries caused by construction accidents and achieve proactive risk control. However, comprehensive smart construction site safety management solutions and applications have yet to be developed. Thus, this study proposes a smart construction site framework for safety management.Design/methodology/approachA safety management system based on a cyber-physical system is proposed. The system establishes risk data synchronization mapping between the virtual construction and physical construction sites through scene reconstruction design, data awareness, data communication and data processing modules. Personnel, mechanical and other risks on site will be warned and controlled.FindingsThe results of the case study have proved the management benefits of the system. On-site workers gradually realized that they should enter the construction site based on the standard process. And the number of people close to the construction hazard areas decreased.Research limitations/implicationsThere are some limitations in the technology of smart construction site. The modeling speed can be faster, the data collection can be timelier, and the identification of unsafe behavior can be integrated into the system. Construction quality and efficiency issues in a virtual construction site will also be solved in further research.Practical implicationsIn this paper, this system is actually applied in the mega project management process. More practical projects can use the management ideas and method of this paper to ensure on-site safety.Originality/valueThis study is among the first attempts to build a complete smart construction site based on CPS and apply it in practice. Personnel, mechanical, components, environment information will be displayed on the virtual construction site. It will greatly promote the development of the intellectualized construction industry in the future.

GPS and GSM Based Tracking System for Objects Moving over Wide Geographical Areas

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Fatima Ameen ◽  
Ziad Mohammed ◽  
Abdulrahman Siddiq
Keyword(s):  
Global Positioning System ◽  
Mobile Communications ◽  
Moving Objects ◽  
Tracking System ◽  
Geographical Area ◽  
Tracking Systems ◽  
Acceptable Result ◽  
Internet Service ◽  
Global Positioning ◽  
Tracking Objects

Tracking systems of moving objects provide a useful means to better control, manage and secure them. Tracking systems are used in different scales of applications such as indoors, outdoors and even used to track vehicles, ships and air planes moving over the globe. This paper presents the design and implementation of a system for tracking objects moving over a wide geographical area. The system depends on the Global Positioning System (GPS) and Global System for Mobile Communications (GSM) technologies without requiring the Internet service. The implemented system uses the freely available GPS service to determine the position of the moving objects. The tests of the implemented system in different regions and conditions show that the maximum uncertainty in the obtained positions is a circle with radius of about 16 m, which is an acceptable result for tracking the movement of objects in wide and open environments.

scholarly journals Development of a Safety Management System Tracking the Weight of Heavy Objects Carried by Construction Workers Using FSR Sensors

2021 ◽  
Vol 11 (4) ◽  
pp. 1378
Author(s):  
Seung Hyun Lee ◽  
Jaeho Son
Keyword(s):  
Random Forest ◽  
Decision Tree ◽  
Safety Management ◽  
Tracking System ◽  
Construction Workers ◽  
Gradient Boosting ◽  
Prototype System ◽  
Construction Site ◽  
Average Accuracy ◽  
Smart Safety

It has been pointed out that the act of carrying a heavy object that exceeds a certain weight by a worker at a construction site is a major factor that puts physical burden on the worker’s musculoskeletal system. However, due to the nature of the construction site, where there are a large number of workers simultaneously working in an irregular space, it is difficult to figure out the weight of the object carried by the worker in real time or keep track of the worker who carries the excess weight. This paper proposes a prototype system to track the weight of heavy objects carried by construction workers by developing smart safety shoes with FSR (Force Sensitive Resistor) sensors. The system consists of smart safety shoes with sensors attached, a mobile device for collecting initial sensing data, and a web-based server computer for storing, preprocessing and analyzing such data. The effectiveness and accuracy of the weight tracking system was verified through the experiments where a weight was lifted by each experimenter from +0 kg to +20 kg in 5 kg increments. The results of the experiment were analyzed by a newly developed machine learning based model, which adopts effective classification algorithms such as decision tree, random forest, gradient boosting algorithm (GBM), and light GBM. The average accuracy classifying the weight by each classification algorithm showed similar, but high accuracy in the following order: random forest (90.9%), light GBM (90.5%), decision tree (90.3%), and GBM (89%). Overall, the proposed weight tracking system has a significant 90.2% average accuracy in classifying how much weight each experimenter carries.

scholarly journals Lightweight and Efficient Image Dehazing Network Guided by Transmission Estimation from Real-World Hazy Scenes

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 960
Author(s):  
Zhan Li ◽  
Jianhang Zhang ◽  
Ruibin Zhong ◽  
Bir Bhanu ◽  
Yuling Chen ◽  
...  
Keyword(s):  
Real World ◽  
Evaluation Criteria ◽  
Synthetic Data ◽  
Network Size ◽  
Image Dehazing ◽  
Depth Data ◽  
Network Training ◽  
Dark Channel ◽  
Processing Techniques ◽  
Transmission Estimation

In this paper, a transmission-guided lightweight neural network called TGL-Net is proposed for efficient image dehazing. Unlike most current dehazing methods that produce simulated transmission maps from depth data and haze-free images, in the proposed work, guided transmission maps are computed automatically using a filter-refined dark-channel-prior (F-DCP) method from real-world hazy images as a regularizer, which facilitates network training not only on synthetic data, but also on natural images. A double-error loss function that combines the errors of a transmission map with the errors of a dehazed image is used to guide network training. The method provides a feasible solution for introducing priors obtained from traditional non-learning-based image processing techniques as a guide for training deep neural networks. Extensive experimental results demonstrate that, in terms of several reference and non-reference evaluation criteria for real-world images, the proposed method can achieve state-of-the-art performance with a much smaller network size and with significant improvements in efficiency resulting from the training guidance.

Video surveillance and analytics technologies in the safety management system in construction projects realization

2020 ◽  
pp. 41-51
Author(s):  
Pavel Kurochkin
Keyword(s):  
Video Surveillance ◽  
Management System ◽  
Construction Projects ◽  
Safety Management ◽  
Industrial Safety ◽  
Processing Plant ◽  
Labor Protection ◽  
Construction Sites ◽  
Gas Processing ◽  
Design And Implementation

Pavel Kurochkin, manager of labor protection, industrial safety and ecology at NIPIGAS company, talks about the realization of the NIPIGAS project for the construction of the Amur gas processing plant for LLC Gazprom pererabotka Blagoveshchensk and about the design and implementation of preparatory works for the construction of the Amur gas-chemical plant for LLC SIBUR. New approaches to labor protection and safety, which are used at NIPIGAZ construction sites, make it possible to control the safety of work at heights and in inaccessible places and to monitor construction and installation works using video surveillance technologies and video analytics.

scholarly journals Sensor-Based Safety Performance Assessment of Individual Construction Workers

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3897 ◽  
Author(s):  
JeeWoong Park ◽  
Yong K. Cho ◽  
Ali Khodabandelu
Keyword(s):  
Risk Model ◽  
Tracking System ◽  
Field Tests ◽  
Safety Performance ◽  
Worker Safety ◽  
Well Test ◽  
Construction Sites ◽  
Monitoring Method ◽  
Safety Issues ◽  
Automated Method

Over the last decade, researchers have explored various technologies and methodologies to enhance worker safety at construction sites. The use of advanced sensing technologies mainly has focused on detecting and warning about safety issues by directly relying on the detection capabilities of these technologies. Until now, very little research has explored methods to quantitatively assess individual workers’ safety performance. For this, this study uses a tracking system to collect and use individuals’ location data in the proposed safety framework. A computational and analytical procedure/model was developed to quantify the safety performance of individual workers beyond detection and warning. The framework defines parameters for zone-based safety risks and establishes a zone-based safety risk model to quantify potential risks to workers. To demonstrate the model of safety analysis, the study conducted field tests at different construction sites, using various interaction scenarios. Probabilistic evaluation showed a slight underestimation and overestimation in certain cases; however, the model represented the overall safety performance of a subject quite well. Test results showed clear evidence of the model’s ability to capture safety conditions of workers in pre-identified hazard zones. The developed approach presents a way to provide visualized and quantified information as a form of safety index, which has not been available in the industry. In addition, such an automated method may present a suitable safety monitoring method that can eliminate human deployment that is expensive, error-prone, and time-consuming.

scholarly journals Posture similarity index: a method to compare hand postures in synergy space

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e6078 ◽  
Author(s):  
Nayan Bhatt ◽  
Varadhan SKM
Keyword(s):  
Experimental Data ◽  
Tracking System ◽  
Synthetic Data ◽  
Similarity Index ◽  
Principal Component ◽  
Synthetic Dataset ◽  
Human Hand ◽  
Task Requirements ◽  
Kinematic Synergies ◽  
The Central Nervous System

Background The human hand can perform a range of manipulation tasks, from holding a pen to holding a hammer. The central nervous system (CNS) uses different strategies in different manipulation tasks based on task requirements. Attempts to compare postures of the hand have been made for use in robotics and animation industries. In this study, we developed an index called the posture similarity index to quantify the similarity between two human hand postures. Methods Twelve right-handed volunteers performed 70 postures, and lifted and held 30 objects (total of 100 different postures, each performed five times). A 16-sensor electromagnetic tracking system captured the kinematics of individual finger phalanges (segments). We modeled the hand as a 21-DoF system and computed the corresponding joint angles. We used principal component analysis to extract kinematic synergies from this 21-DoF data. We developed a posture similarity index (PSI), that represents the similarity between posture in the synergy (Principal component) space. First, we tested the performance of this index using a synthetic dataset. After confirming that it performs well with the synthetic dataset, we used it to analyze the experimental data. Further, we used PSI to identify postures that are “representative” in the sense that they have a greater overlap (in synergy space) with a large number of postures. Results Our results confirmed that PSI is a relatively accurate index of similarity in synergy space both with synthetic data and real experimental data. Also, more special postures than common postures were found among “representative” postures. Conclusion We developed an index for comparing posture similarity in synergy space and demonstrated its utility by using synthetic dataset and experimental dataset. Besides, we found that “special” postures are actually “special” in the sense that there are more of them in the “representative” postures as identified by our posture similarity index.

Reliable Communication Network for Emergency Response and Disaster Management in Underground Mines

2019 ◽  
pp. 195-239
Author(s):  
S. M. Kamruzzaman ◽  
Xavier Fernando ◽  
Muhammad Jaseemuddin ◽  
Wisam Farjow
Keyword(s):  
Communication Network ◽  
Disaster Management ◽  
Emergency Response ◽  
Safety Management ◽  
Emergency Situation ◽  
Underground Mines ◽  
Mine Safety ◽  
Tracking Systems ◽  
Reliable Communication ◽  
Backbone Networks

Emergency response and disaster management in underground mines are very challenging due to the hostile nature. Environment monitoring in mines has been an obligatory requirement to ensure safe working conditions for miners. Reliable communication network is essential to quickly detect the underground condition especially in emergency situation and to conduct proper rescue operations. This chapter presents an overview of reliable communication network needed for emergency response and disaster management in underground mines. The chapter begins by introducing the most common accidents occurring in the mining, underground mine environment and channel properties. Subsequently, communications in underground mines, existing underground communication and tracking systems, and disaster forecasting & mine safety management are discussed. The chapter also covers post-disaster mine communications & tracking systems and optimized backbone networks for underground mines. Finally, the chapter concludes by reporting relevant research at Ryerson Communications Lab and pointing out some open issues and possible research directions.

Intelligent Engineering Construction Management

2021 ◽  
pp. 140-161
Author(s):  
Min Hu ◽  
Huiming Wu ◽  
QianRu Chan ◽  
JiaQi Wu ◽  
Gang Chen ◽  
...  
Keyword(s):  
Information Management ◽  
Safety Management ◽  
Information Management System ◽  
Equipment Management ◽  
Construction Sites ◽  
Engineering Construction ◽  
Management Quality ◽  
Management Capacity ◽  
Intelligent Information ◽  
The City

Architecture is an important part of the city, and construction is an indispensable procedure of urban development. From the perspective of “smart construction sites,” this chapter describes the basic system architecture of intelligent information management system for engineering construction and introduces how to use information technology such as internet of things and artificial intelligence to improve the management capacity of engineering construction from the perspective of personnel management, quality management, safety management, equipment management, and environmental management. This chapter also analyzes the advantages and problems of intelligent construction sites in project management and gives specific measures and suggestions to realize smart construction sites.

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