Browsing by Author "Fang, Yi-Cho"

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A feasibility study of using smartphone built-in accelerometers to detect fall portents
(2014-03-01)
Dzeng, Ren-Jye
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Fang, Yi-Cho
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Chen, I-Chung
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土木工程學系
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Department of Civil Engineering
Fall accidents contribute to nearly half of all fatalities in the construction industry in Taiwan. Detecting fall portents using a smartphone, which many people carry daily, may help reduce fall accidents if the accuracy is acceptable. We designed two experiments with three algorithms to evaluate how well a smartphone can detect both falls and fall portents in a tiling operation scenario. The experiments show that work-related motions barely affected the detection of falls, and the result had a sensitivity and specificity of 100% and 96.1%, respectively. However, for detecting portents, the work-related motions had quite a large impact on the gyroscope-based algorithm, which demonstrated an accuracy rate of only 4.3%, but had only limited impact on the accelerometer-based algorithm, which still show acceptable accuracy rates of 73.5% and 88.5%. We conclude that using a smartphone to detect falls and portents in a construction site is feasible. (C) 2013 Elsevier B.V. All rights reserved.
A smartphone-based detection of fall portents for construction workers
(2014-01-01)
Fang, Yi-Cho
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Dzeng, Ren-Jye
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土木工程學系
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Department of Civil Engineering
The construction industry accounts for nearly half of all industry-related fatalities in Taiwan. Identified as the leading cause of such fatalities for several decades, falls also contribute to almost half of work-related fatalities. Given the strenuous nature of construction work, workers are prone to loss of awareness and balance, increasing the safety risk and number of fall accidents. Previous studies have indicated that loss of awareness may be the major cause of occupational injuries or fatalities, and identified the strong correlation between falls and loss of balance. Thus, real-time monitoring of the mental and balance conditions of workers may help identify fall portents, and thus prevent falls from happening. This paper describes a framework for developing a personal safety monitoring system based on a smartphone, which receives external signals wirelessly from motion sensors and brain wave sensors attached to a vest and inside a helmet, and transmit these signals to a monitoring server for further analysis. This paper also presents an experiment with preliminary findings regarding the detection of fall portents, using the internal motion sensors of a smartphone. In the experiment, participants performed a tiling task on a scaffold under four physiological statuses. We identified the fall portents based on the self-awareness of the participants, hazardous actions performed by the participants, and outsider observations by experiment administrators. An accelerometer-based threshold algorithm was tested, and its performance was evaluated against the identified fall portents. The results indicated that the work-related motions had a limited impact on the detection algorithm. The accuracy for the sleepiness, fatigue, normal, and inebriation statuses were 92.3%, 90.4%, 77.3%, and 68.8%, respectively. The algorithm exhibited an overall accuracy of 86%, thus, we conclude that using a smartphone to detect fall portents in a working scenario is feasible, and deserves further investigation. (C) 2014 Published by Elsevier Ltd.
Accelerometer-based fall-portent detection algorithm for construction tiling operation
(2017-12-01)
Fang, Yi-Cho
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Dzeng, Ren-Jye
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土木工程學系
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Department of Civil Engineering
Fall accidents are a major safety issue and a perennial problem in the construction industry. However, few studies have focused on detecting fall portents, identification of which may prevent falls from occurring. This study developed an accelerometer-based fall portent detection system that employed a hierarchical threshold based algorithm. We designed tiling experiments to evaluate the performance of the proposed system. The participants performed the tasks under normal, inebriation, and sleepiness conditions on a scaffold while four accelerometers were attached to their chest, waist, arm, and hand. The results revealed that the traditional threshold-based algorithms had unacceptable accuracies of less than 30.66%. Most false warnings could be attributed to misidentifications of work-related motions. However, the work-related motions had a limited effect on the hierarchical threshold-based algorithm, which exhibited a satisfactory detection rate and accuracy of 76.86% and 79.13%, respectively.
Extracting Knowledge for Searching for and Identifying Hazards on Construction Site
(2015-01-01)
Dzeng, Ren-Jye
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Fang, Yi-Cho
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土木工程學系
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Department of Civil Engineering
The construction industry accounts for a high number of accidents. Although identifying hazards before construction starts or during construction is widely employed to prevent accidents, it typically fails because of insufficient safety experience. The experience helps in training novice inspectors, although extracting and describing tacit knowledge explicitly is difficult. This study created a 3-D virtual construction site, and designed a hazard-identification experiment involving 14 hazards (e.g., falls, collapses, and electric shocks), and an eye-tracker was used to compare the search patterns of the experienced and novice workers. The results indicated that experience assisted the experienced workers in assessing hazards significantly faster than the novice workers could; however, it did not improve the accuracy with which they identified hazards, indicating that general work experience is not equivalent to safety-specific experience, and may not necessarily improve workers' accuracy in identifying hazards. Nevertheless, the experienced workers were more confident in identifying hazards, they exhibited fewer fixations.
Quantitative evaluation of the impact of night shifts and alcohol consumption on construction tiling quality
(2015-09-01)
Dzeng, Ren-Jye
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Wang, Shih-Hsu
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Fang, Yi-Cho
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土木工程學系
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Department of Civil Engineering
The adverse effects of night-shift work and alcohol consumption on performance have received considerable attention. However, how night shifts and alcohol affect productivity in workers has not been quantified. This paper describes the experiments featuring multiple tiling tasks and patterns. The tiling quality performed by the graduate student participants in four different statuses was objectively evaluated by an edge-detection computer program. The results indicate that both night shift and alcohol significantly reduce the quality in general, and the effects of the factors on position and alignment-angle qualities were dissimilar in distinct areas due to tile patterns and size. Both night-shift and alcohol conditions affected the basic (-34.01% and -25.79%) and advanced tiling abilities (-40.14% and -26.16%), and night shift had a larger impact than alcohol. These results provide jobsite managers with usable information regarding how night shifts and alcohol affect workers\' abilities to execute basic and advanced tasks. (C) 2015 Elsevier Ltd and The Ergonomics Society. All rights reserved.
Using eye-tracker to compare search patterns between experienced and novice workers for site hazard identification
(2016-02-01)
Dzeng, Ren-Jye
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Lin, Chin-Teng
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Fang, Yi-Cho
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土木工程學系
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電機資訊學士班
The construction industry accounts for a high number of accidents. Although identifying hazards prior to commencing construction is widely employed to prevent accidents, it typically fails because of insufficient safety experience. The experience helps in training novice inspectors, although extracting and describing tacit knowledge explicitly is difficult. This study created a digital building construction site, and designed a hazard-identification experiment involving four workplaces featuring obvious and unobvious hazards (e.g., falls, collapses, and electric shocks), and an eye-tracker was used to compare the search patterns of the experienced and novice workers. The results indicated that experience assisted the experienced workers in assessing both obvious (p < 0.001) and unobvious hazards (p = 0.004) significantly faster than the novice workers could; however, it did not improve the accuracy with which they identified hazards, indicating that general work experience is not equivalent to safety-specific experience, and may not necessarily improve workers\' accuracy in identifying hazards. Nevertheless, the experienced workers were more confident in identifying hazards, they exhibited fewer fixations, and their scan paths for assessing hazards were more consistent. The experienced workers first assessed the high-risk targets-laborers working at heights-and subsequently assessed those working on the ground, followed by the equipment or environment. Furthermore, they typically inspected openings later than novice workers did. The search strategies identified may be incorporated into the training courses to improve the hazard awareness for novice workers. (C) 2015 Elsevier Ltd. All rights reserved.