• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.2
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• pp.187-193
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• 2021

In February 2020, Gyeonggi-do paid the world's first Data Dividend to local residents of Gyeonggi Province who produced data using local currency. Currently, Data Dividend is being paid to consumers who have produced data, but this paper studied the expansion of Data Dividend qualifications according to the contribution to creating added value. First, it raised the question of whether it is right for the recipient of Data Dividend to have only the consumers who produced the data. Second, by analyzing the four elements of data valuation criteria that influenced the creation of added value identified the objects that influence the creation of added value. The 4 factors were divided into productivity, effectiveness, concreteness, and usability, and the objects corresponding to each factor were analyzed. Accordingly, it was determined whether platform workers contributed to the creation of added value. In conclusion, it was confirmed that not only consumers, who were the first data producers, but also platform workers who contributed to the concreteness of data valuation to create added value can qualify for Data Dividend. Since this paper focuses on the necessity of data allocation centered on platform workers among the objects, the validity of objects that influence added value other than platform workers are excluded.

• Journal of Preventive Medicine and Public Health
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• v.39 no.4
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• pp.325-330
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• 2006

Objectives: The aims of this study were to examine the level of airborne fungi and environmental factors in Seoul metropolitan subway stations and to provide fundamental data to protect the health of subway workers and passengers. Methods: The field survey was performed from November in 2004 to February in 2005. A total 22 subway stations located at Seoul subway lines 1-4 were randomly selected. The measurement points were subway workers' activity areas (station office, bedroom, ticket office and driver's seat) and the passengers' activity areas (station precincts, inside train and platform). Air sampling for collecting airborne fungi was carried out using a one-stage cascade impactor. The PM and CO2 were measured using an electronic direct recorder and detecting tube, respectively. Results: In the activity areas of the subway workers and passengers, the mean concentrations of airborne fungi were relatively higher in the workers' bedroom and station precinct whereas the concentration of particulate matter, $PM_{10}\;and\;PM_{2.5}$, were relatively higher in the platform, inside the train and driver's seat than in the other activity areas. There was no significant difference in the concentration of airborne fungi between the underground and ground activity areas of the subway. The mean $PM_{10}\;and\;PM_{2.5}$ concentration in the platform located at underground was significantly higher than that of the ground (p<0.05). Conclusions: The levels of airborne fungi in the Seoul subway line 1-4 were not serious enough to cause respiratory disease in subway workers and passengers. This indicates that there is little correlation between airborne fungi and particulate matter.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.171-176
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• 2020

This paper presents an implementation of a gesture recognition platform that can be used in a factory workplaces. The platform consists of signages that display worker's job orders and a control center that is used to manage work orders for factory workers. Each worker does not need to bring work order documents and can browse the assigned work orders on the signage at his/her workplace. The contents of signage can be controlled by worker's hand and arm gestures. Gestures are extracted from body movement tracked by 3D depth camera and converted to the commandsthat control displayed content of the signage. Using the control center, the factory manager can assign tasks to each worker, upload work order documents to the system, and see each worker's progress. The implementation has been applied experimentally to a machining factory workplace. This flatform provides convenience for factory workers when they are working at workplaces, improves security of techincal documents, but can also be used to build smart factories.

• Journal of KIBIM
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• v.11 no.2
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• pp.24-32
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• 2021

Recently, starting with smart construction research, interest in technology that automates construction site management using artificial intelligence technology is increasing. In order to automate construction site management, it is necessary to recognize objects such as construction equipment or workers, and automatically analyze the relationship between them. For example, if the relationship between workers and construction equipment at a construction site can be known, various use cases of site management such as work productivity, equipment operation status monitoring, and safety management can be implemented. This study derives a real-time object detection platform architecture that is required when performing construction site management using deep learning technology, which has recently been increasingly used. To this end, deep learning models that support real-time object detection are investigated and analyzed. Based on this, a deep learning model development process required for real-time construction site object detection is defined. Based on the defined process, a prototype that learns and detects construction site objects is developed, and then platform development considerations and architecture are derived from the results.

• Safety and Health at Work
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• v.10 no.1
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• pp.1-2
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• 2019

• The Journal of Information Systems
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• v.31 no.2
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• pp.111-136
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• 2022

Purpose The purpose of this study is to examine the effect that insecurity and autonomy of platform work have an influence on work-life balance and psychological well-being in an era of platform economy based on two characteristics of online platform work and self-determination theory. Design/methodology/approach This study suggested the structural equation model integrating two antecedents, insecurity and autonomy, work-life balance, and psychological well-being and proposed five hypotheses driven from the research model. A total of 334 valid samples were collected from platform workers by employing questionnaire including 24 question items of four constructs. Findings Three hypotheses were supported and one hypothesis was not supported at the significance level of 0.05. Insecurity of platform work has a negative influence on work-life balance at the significance level of 0.01, whereas insecurity of platform work has no a significant influence on psychological well-being. Autonomy of platform work has a positive influence on both work-life balance and psychological well-being at the significance level of 0.01. Work-life balance has a positive impact on psychological well-being at the significance level of 0.001. Insecurity have an influence on psychological well-being indirectly through mediation of work-life balance. Implications for academicians and practitioners were suggested.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.669-670
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• 2015

Efficient management of the construction heavy equipment is required to reduce the rate of carbon emissions and on-site accidents. The intelligent excavation system (IES) will improve the construction quality and productivity through information technologies and efficient equipment operation, especially in large earthwork projects. Three-dimensional digitized ground data should be required for identifying the path of heavy equipment and work-site environment. Rapid development of terrain laser scanners (TLS) is more readily to acquire the digital data. This study suggests the '3D ground terrain processing platform (3DGTPP)' including data manipulating module and analyzing module of the scanned data for intelligent earthmoving equipment operation. The processing platform consists of six modules, including scanning, registering, manipulating, analyzing, transmitting, and storing. 3D ground terrain processing platform presented in this study will provide fundamental information for intelligent excavation system (IES), which will increase the efficiency of earthworks and safety of workers in significant.

• Journal of Platform Technology
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• v.10 no.1
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• pp.3-10
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• 2022

In high-risk workplaces where communication is not possible, such as deforestation, it is necessary to use equipment that monitors the worker's situation in real time and obtains information according to the worker's location in case of an emergency. This paper analyzes the development and demonstration experiments of smart hard hats for deforestation workers to maintain a safe working environment. The developed smart helmet identifies the location of the worker based on the UWB signal for location estimation, and it is necessary to keep the distance between the workers not too close. UWB, Gyro, and LoRa are used to communicate even in the communication shadow area. It is used to provide a safe working environment such as improved construction to reduce worker risks and risks in forest working environments.

• Journal of Information Processing Systems
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• v.14 no.3
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• pp.621-630
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• 2018

Selection of a suitable task from the extensively available large set of tasks is an intricate job for the developers in crowdsourcing software development (CSD). Besides, it is also a tiring and a time-consuming job for the platform to evaluate thousands of tasks submitted by developers. Previous studies stated that managerial and technical aspects have prime importance in bringing success for software development projects, however, these two aspects can be more effective and conducive if combined with human aspects. The main purpose of this paper is to present a conceptual framework for task assignment model for future research on the basis of personality types, that will provide a basic structure for CSD workers to find suitable tasks and also a platform to assign the task directly. This will also match their personality and task. Because personality is an internal force which whittles the behavior of developers. Consequently, this research presented a Task Assignment Model (TAM) from a developers point of view, moreover, it will also provide an opportunity to the platform to assign a task to CSD workers according to their personality types directly.

• Annals of Occupational and Environmental Medicine
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• v.35
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• pp.43.1-43.12
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• 2023

Background: Gig workers, also known as platform workers, are independent workers who are not employed by any particular company. The number of gig economy workers has rapidly increased worldwide in the past decade. There is a dearth of occupational health studies among gig economy workers. We aimed to investigate the association between exposure to violence and job stress in gig economy workers and depressive symptoms. Methods: A total of 955 individuals (521 gig workers and 434 general workers) participated in this study and variables were measured through self-report questionnaires. Depressive symptoms were evaluated by the Patient Health Questionnaire-9 when the score was greater than or equal to 10 points. The odds ratio with 95% confidence interval was calculated using multivariable logistic regression adjusted for age, sex, working hours, education level, exposure to violence and job stress. Results: 19% of gig economy workers reported depressive symptoms, while only 11% of general workers reported the depressive symptoms. In association to depressive symptoms among gig economy workers, the mainly result of odds ratios for depressive symptoms were as follows: 1.81 for workers type, 3.53 for humiliating treatment, 2.65 for sexual harassment, 3.55 for less than three meals per day, 3.69 for feeling too tired to do housework after leaving work. Conclusions: Gig economic workers are exposed to violence and job stress in the workplace more than general workers, and the proportion of workers reporting depressive symptoms is also high. These factors are associated to depressive symptoms. Furthermore, the gig workers associated between depressive symptoms and exposure to violence, job stress.