• Journal of the Korean Society of Safety
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• v.24 no.6
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• pp.72-78
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• 2009

Exposure to HDI(hexamethylene di-isocyanate) commonly used in vehicle crash repair workshops remains a leading cause of occupational asthma. Although skin and eye contamination are considered as absorption routes, there are no occupational exposure standards for skin and ocular exposure. This is the reason why there are more empirical data should be provided. Therefore this study was to determine contamination levels of HDI on the skin, eyes, work surfaces, respirators and eye protectors. There was evidence of contamination on a variety of work surfaces, for example, door handles, bench top and spray gun, etc. A high proportion(47~80%) of skin wipe samples from neck, forehead, back hand, palm and wrist was positive for HDI contamination, even though spray time was relatively brief. The contamination levels from spraying inside spray booth were generally higher than outside booth due to poor work practices and inappropriate personal protective use like safety gloves. Apprentices had higher exposure levels than the qualified painters, likely due to lack of the recognition of safety and hygiene. The extent of contamination inside the PPE might provide an indication of the potential for respiratory & skin exposure and ocular exposure. Eye fluid samples from 4 out of 14 workers had the positive detection of HDI contamination, due to poor work practices like no or inappropriate eye protection. Considering the potential for dermal & ocular exposure to contribute to possible health symptoms including respiratory sensitization, the empirical data point to a need for improving work practices and appropriate PPE selection, use and maintenance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.231-236
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• 2021

The Aphid, Myzus persicae, and the bean bug, Riptortus clavatus, are major insects in crops. This study examined the insecticide susceptibility and phytotoxicity of insecticides dispersed using an Unmanned Aerial Vehicle (UAV, multi-copter) against the insects. Sulfoxaflor suspension concentrate (SC, 16X) on potato fields and etofenprox, methoxyfenzide suspo-emulsion(SE, 8X) on soybean fields were dispersed after deploying water-sensitive paper within the field to measure the distribution pattern and coverage index of the falling insecticide. Both insecticides showed a controlled mortality of 76.4% against aphids and 97.5% and 94.4% against the 2nd nymphal, and 5th nymphal stage of the bugs, respectively. The droplet distribution was less than 0.5mm, and coverage analysis revealed an inside and outside coverage of 3.1 and 1.6, respectively. The surrounding area was affected by insecticide spraying using a multi-copter. This study is expected to help expand UAV control and use it safely in the future.

• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.35-40
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• 2022

In the agricultural environment, pesticide control requires a high risk of work and a high labor force for farmers. The effectiveness of pesticide control using unmanned aerial vehicles varies according to climate, land type, and characteristics of unmanned aerial vehicles. Therefore, an effective method for pesticide control by unmanned aerial vehicles considering the spraying conditions and environmental conditions is required. In this paper, we propose an efficient pesticide control system based on agricultural unmanned aerial vehicles considering the application conditions and environmental information for each crop. The effectiveness of the proposed model was demonstrated by measuring the drop uniformity of pesticides according to the change in altitude and speed after attaching the sensory paper and measuring the penetration rate of the drug inside the canopy according to the change in crop growth conditions. Experiment result, the closer the height of the UAV is to the ground, the more evenly the crops are sprayed, but for safety reasons, 2m more is suitable, and on average a speed of 2m/s is most suitable for control. The proposed control system is expected to help develop intelligent services based on the use of various unmanned aerial vehicles in agricultural environments.