• 제목/요약/키워드: Falling Accidents

검색결과 177건 처리시간 0.028초

합성곱 신경망 기반 물체 인식과 탑승 감지 센서를 이용한 개인형 이동수단 주행 안전 보조 시스템 개발 (Development of Personal Mobility Safety Driving Assistance System Using CNN-Based Object Detection and Boarding Detection Sensor)

  • 손권중;배성훈;이현준
    • 한국융합학회논문지
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    • 제12권10호
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    • pp.211-218
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    • 2021
  • 최근에 전동킥보드와 같은 개인형 이동수단의 보급이 급격히 확대되면서 교통사고 발생 건수도 크게 늘고있다. 개인형 모빌리티가 자세 안정성이 낮고 탑승자가 외부로 노출되어 전도 사고나 낙상 사고의 위험이 크기 때문이다. 전동킥보드 사고 방지를 위해 본 논문은 주행 보조 장치로써 자동긴급제동시스템과 안전시동시스템을 제안하였다. 인공지능 기반 물체 인식 기술을 이용하여 주변 위험 요소를 탐지하고 자동으로 제동을 걸 수 있는 시스템을 개발하였다. 또한 운전자의 탑승이 확인되기 전까지 장치의 시동을 보류하는 안전시동시스템도 개발하였다. 상용차와 주행 조건이 매우 다른 개인형 이동 수단에 특화된 첨단 운전자 보조 시스템 융합 기술을 제안한다는 점에서 본 연구의 의의가 있다.

2017년도 법의부검에 대한 통계적 고찰 (A Statistical Analysis on Forensic Autopsies Performed in Korea in 2017)

  • 박지혜;나주영;이봉우;양경무;최영식
    • The Korean Journal of Legal Medicine
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    • 제42권4호
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    • pp.111-125
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    • 2018
  • Statistical analysis was performed on national forensic autopsy data collected in the Republic of Korea, with the exception of Ulsan, during 2017. A total of 8,777 cases were categorized based on the region; information was provided by the Police Agency and the Coast Guard regarding sex, age, manner of death, and cause of death. Analysis of the manner of death revealed that 3,971 cases (45.2%) were unnatural deaths, 3,679 cases (41.9%) were natural deaths, and 1,127 cases (12.8%) were unknown deaths. Among the unnatural deaths, the majority of the cases (1,740 cases, 43.8%) were accidents, 1,316 cases (33.1%) were suicide, 385 cases (9.7%) were homicide, and 530 cases (13.3%) were undetermined deaths. Among the unnatural deaths, the majority of the cases (1,575 cases, 39.7%) were trauma, followed by 793 cases (20.0%) of poisoning and 689 cases (17.4%) of asphyxia. Falling down was the major cause of death by trauma (737 cases, 46.8%). As a result of the classification of asphyxia based on previous study, strangulation was the major cause, with 538 cases (78.1%). Among the natural deaths, heart disease was the major cause (1,790 cases, 48.7%), followed by vascular disease (697 cases, 18.9%).

독거노인 케어를 위한 개선된 YOLO-KCF 기반 낙상감지 알고리즘 (The Modified Fall Detection Algorithm based on YOLO-KCF for Elderly Living Alone Care)

  • 강경원;박수영
    • 융합신호처리학회논문지
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    • 제21권2호
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    • pp.86-91
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    • 2020
  • 독거노인이 증가하면서 낙상 사고 빈도도 높아지고 있다. 낙상은 노인들의 건강을 위협할 뿐만 아니라, 독립적인 생활을 위협할 수 있다. 이 문제를 해결하기 위해서는 독거노인의 위급한 상태를 인식하고 대응할 수 있는 실시간 기술이 필요하다. 따라서 본 논문은 독거노인을 위해 긴급 상황 중 하나인 낙상을 실시간으로 확인할 수 있는 YOLO-KCF를 기반 개선된 낙상 감지 알고리즘을 제안한다. YOLO는 물체의 검출뿐 아니라 서 있는 행동과 쓰러지는 행동 유행을 감지할 수 있다. 따라서 본 논문은 서 있는 행동 유형과 쓰러지는 행동 유형간의 경계 박스의 형태 변화를 이용하여 낙하를 검출할 수 있으며, KCF의 단점을 개선할 수 있다.

Epidemiology and patterns of nasal bone fracture in elderly patients in comparison to other age groups: an 8-year single-center retrospective analysis

  • Jung, Seil;Yoon, Sihyun;Kim, Youngjun
    • 대한두개안면성형외과학회지
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    • 제23권5호
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    • pp.205-210
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    • 2022
  • Background: Nasal bone fractures are the most common type of facial bone fracture, but are under-studied in adults above 65 years of age. Therefore, we investigated the epidemiology and patterns of nasal bone fractures among older adults in comparison to different age groups. Methods: This retrospective study included 2,321 nasal bone fracture patients who underwent surgery at our hospital from January 2010 to December 2017. The patients were classified by age as preschoolers, school-age children, young and middle-aged adults, and the elderly. We performed pairwise comparisons between elderly patients and each other age group in terms of sex, cause of injury, and fracture type. Results: The 2,321 nasal bone fracture patients included 76 elderly patients (50 men [65.8%] and 26 women [34.2%]). In these patients, the two most common injury causes were falling or slipping down (n= 39; 51.3%) and road traffic accidents (n= 19; 25.0%). According to the Stranc and Robertson classification, the most common force vector was lateral, and plane 2 fractures with lateral forces predominated. Conclusion: The elderly showed similar patterns of nasal bone fractures to those observed in young and middle-aged adults, but significant differences from preschoolers (in the injury vector and plane of fracture) and from school-age children (in the sex ratio and plane of fracture). However, elderly patients presented significantly different epidemiological characteristics compared to the other three groups. Therefore, it is necessary to improve the quality of life of the elderly and prepare for the upcoming super-aged society by taking steps to reduce the incidence and severity of fractures. Possible options for doing so include strengthening individual-level safety factors and expanding the social safety net for the elderly.

차량 단말기 기반 돌발상황 검지 알고리즘 개발 (Development of a Emergency Situation Detection Algorithm Using a Vehicle Dash Cam)

  • 이상현;김진영;노종민;이환필;이수목;윤일수
    • 한국ITS학회 논문지
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    • 제22권4호
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    • pp.97-113
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    • 2023
  • 전방 낙하물과 같은 돌발상황이 발생했을 때 신속하고 적절한 정보 제공은 도로 위 이용자들의 편의를 가져다주고 2차 교통사고 또한 효과적으로 줄일 수 있다. 도로 상의 돌발상황은 현재 국내에서 루프 검지기나 CCTV 등 ITS 기반 검지 체계를 사용하여 주로 검지하고 있다. 이러한 방식은 검지기의 검지 구간에서의 도로 위 데이터만을 얻을 수 있다. 때문에, 기존 ITS 기반 검지체계의 공간적 음영구간에서 돌발상황을 찾아내기 위하여 새로운 검지 수단이 필요하다. 이에 본 연구에서는 차량 내 설치된 단말기에서 촬영된 영상으로부터 돌발상황을 검지 및 분류하는 ResNet 기반 알고리즘을 제안한다. 국내 고속도로 전방 주행영상을 수집하였고, 돌발상황 유형을 클래스로 정의하여 각 데이터를 라벨링한 후, 제안한 알고리즘으로 데이터를 학습시켰다. 학습 결과, 개발한 알고리즘은 데이터 수가 상대적으로 적었던 일부 클래스를 제외하고 정의한 돌발상황 클래스에 대하여 높은 검지율을 보였다.

TRACKING LIFT-PATHS OF A ROBOTIC TOWERCRANE WITH ENCODER SENSORS

  • Suyeul Park;Ghang, Lee;Joonbeom cho;Sungil Hham;Ahram Han;Taekwan Lee
    • 국제학술발표논문집
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    • The 3th International Conference on Construction Engineering and Project Management
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    • pp.250-256
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    • 2009
  • This paper presents a robotic tower-crane system using encoder and gyroscope sensors as path tracking devices. Tower crane work is often associated with falling accidents and industrial disasters. Such problems often incur a loss of time and money for the contractor. For this reason, many studies have been done on an automatic tower crane. As a part of 5-year 23-million-dollar research project in Korea, we are developing a robotic tower crane which aims to improve the safety level and productivity. We selected a luffing tower crane, which is commonly used in urban construction projects today, as a platform for the robotic tower crane system. This system comprises two modules: the automated path planning module and the path tracking module. The automated path planning system uses the 3D Cartesian coordinates. When the robotic tower crane lifts construction material, the algorithm creates a line, which represents a lifting path, in virtual space. This algorithm seeks and generates the best route to lift construction material while avoiding known obstacles from real construction site. The path tracking system detects the location of a lifted material in terms of the 3D coordinate values using various types of sensors including adopts encoder and gyroscope sensors. We are testing various sensors as a candidate for the path tracking device. This specific study focuses on how to employ encoder and gyroscope sensors in the robotic crane These sensors measure a movement and rotary motion of the robotic tower crane. Finally, the movement of the robotic tower crane is displayed in a virtual space that synthesizes the data from two modules: the automatically planned path and the tracked paths. We are currently field-testing the feasibility of the proposed system using an actual tower crane. In the next step, the robotic tower crane will be applied to actual construction sites with a following analysis of the crane's productivity in order to ascertain its economic efficiency.

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A Worker-Driven Approach for Opening Detection by Integrating Computer Vision and Built-in Inertia Sensors on Embedded Devices

  • Anjum, Sharjeel;Sibtain, Muhammad;Khalid, Rabia;Khan, Muhammad;Lee, Doyeop;Park, Chansik
    • 국제학술발표논문집
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    • The 9th International Conference on Construction Engineering and Project Management
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    • pp.353-360
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    • 2022
  • Due to the dense and complicated working environment, the construction industry is susceptible to many accidents. Worker's fall is a severe problem at the construction site, including falling into holes or openings because of the inadequate coverings as per the safety rules. During the construction or demolition of a building, openings and holes are formed in the floors and roofs. Many workers neglect to cover openings for ease of work while being aware of the risks of holes, openings, and gaps at heights. However, there are safety rules for worker safety; the holes and openings must be covered to prevent falls. The safety inspector typically examines it by visiting the construction site, which is time-consuming and requires safety manager efforts. Therefore, this study presented a worker-driven approach (the worker is involved in the reporting process) to facilitate safety managers by developing integrated computer vision and inertia sensors-based mobile applications to identify openings. The TensorFlow framework is used to design Convolutional Neural Network (CNN); the designed CNN is trained on a custom dataset for binary class openings and covered and deployed on an android smartphone. When an application captures an image, the device also extracts the accelerometer values to determine the inclination in parallel with the classification task of the device to predict the final output as floor (openings/ covered), wall (openings/covered), and roof (openings / covered). The proposed worker-driven approach will be extended with other case scenarios at the construction site.

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세종시 스마트시티 구상 및 수립 방안 (Planning and Establishment of Sejong City Smart City)

  • 박정수;정한민
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2021년도 추계학술대회
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    • pp.161-163
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    • 2021
  • 산업혁명 이후 일자리를 찾기 위해 수많은 사람이 도시로 모여들어, 현재 세계 인구 50% 이상이 도시에 살고 있다. 이러한 도시 집중화는 앞으로도 급속히 전개되어 2035년에는 75% 인구가 도시에 살 것으로 전망된다. 대도시는 점점 높아지는 인구 밀도로 인하여 환경 오염, 심각한 교통 체증, 지나치게 빠른 에너지 고갈 및 자연 생태계 파괴 등 부작용이 발생하면서 지속가능성이 떨어지고 있다. 또한, 높은 범죄율과 안전사고, 불평등과 양극화로 인한 일과 삶의 불균형, 지나치게 경쟁적인 교육 등으로 대도시 시민들의 행복 지수 역시 떨어지고 있다. 이러한 문제를 해결하기 위하여 공급자, 관리자 중심이 아닌 사용자와 시민 중심으로 설계, 운영, 관리되는 IT 기술 기반 미래형 도시 모델인 스마트시티가 탄생하게 되었다. 우리나라도 국가 중점 사업으로 스마트시티의 효율적인 건설 및 운영을 통해 도시 경쟁력을 향상하고 지속 가능한 발전을 촉진하려는 시도를 적극적으로 하고 있다. 이를 뒷받침하기 위해 본 연구는 국토종합계획 및 스마트도시 종합계획, 스마트시티 전략계획 등을 기반으로 세종시의 스마트도시서비스 기반 시설 등의 기본 방향 및 추진 전략을 검토하고, 관련 계획의 연관 관계를 조사하여 세종시 스마트시티 관련 사업 검토와 스마트도시 조성을 위한 추진 체계 및 정책을 제언하고자 한다.

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안전성 강화를 위한 ESP32-CAM을 활용한 시각장애인용 스마트지팡이에 대한 연구 (Study on a Smart Cane for the Visually Impaired utilizing ESP32-CAM for Enhanced Safety)

  • 홍두현;임종환;유준선;백승협;김재욱
    • 한국전자통신학회논문지
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    • 제18권6호
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    • pp.1379-1386
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    • 2023
  • 본 논문에서는 시각장애인을 위한 스마트 지팡이의 설계와 개발에 대해 다루고 있다. 스마트 지팡이는 초음파 거리 센서, 피에조부조, 조도 센서, LED선, 블루투스 모듈, 카메라 모듈, 스위치, 배터리 등의 센서와 모듈을 내장하고 있으며, 사용자가 지팡이를 사용하는 동안 주변 환경을 카메라로 실시간 스트리밍할 수 있고 보호자에게 공유할 수 있다. 스마트 지팡이는 초음파 거리 센서를 사용하여 앞에 있는 장애물의 거리를 측정하여 사용자에게 경고음을 울려줍니다. 블루투스 모듈과 스마트폰 앱을 이용하여 보호자에게 자신의 위치를 알려준다. 이러한 스마트 지팡이는 시각장애인이 일상생활에서 자신의 이동을 보다 안전하게 할 수 있도록 돕는데 큰 도움이 될 수 있다.

일부지역 산업재해환자 실태 연구 -대구, 경북지역 일부 종합병원 중심으로- (A Study of Industrial Patients from Selected General Hospitals in the Kyung Pook and Taegu City Areas)

  • 허춘복;남철현
    • 한국환경보건학회지
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    • 제17권2호
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    • pp.78-94
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    • 1991
  • The purpose of this study is to research the actual conditions of industrial accident patients and to produce worker satisfaction and a rational and effective counter measure pain. Direct interviews with 179 cases (in and out patients) were carried out during a three month period from April to July 1990, at six hospitals two general hospitals Sun Lin and Sung Mo in Po Hang, and four general hospitals in Taegu Kyung Pook University Hospital, Dong San Medical Center, Young Nam Medical Center and Catholic Hospital. The results of this study are summarized as follows: 1. Among the 179 cases, 51.6 % were male and 48.4 % were female. The two largest age groups were 30~39, 31.8 % and 20~29, 27.4 %. Among the 179 cases, 51.6% were married, the largest family number was 2 to 3, 41.1% and 4 to 5, 25.6%. Educationally, graduation from high school was the largest group, 46.4% among the patients, followed by middle school and primary school. The largest group income level was from 40~69만원, 45.2%. The largest group of patients who worked over 50 hrs. a week was 52.0%. The largest group of patients who worked less than 1 year was 44.7%, of the patients in work places of less than 100 people, 60.3% were injured and in work places of 100~299 people, 20.1% were injured. In manufacturing, the lagest group injured was 55.3%, the next group was transport, stroage, communication. The largest group of production workers injured was 40.2%. 2. The cause of injury in the largest group was facility problems, 33.5%. The next group was unsafe habits, 30.2% a lack of safety knowledge, 17.9% and insufficient supervision, 12.3%. The 30~39 year age group was head the highest number of injuries, 40.4% work places with more than 10 yeras of work, 44.4% work palces with more than 1000 people, 56.3% and mining accidents, 80.0%. Among these groups the highest cause of injury was due to facility problems. 3. The accident pattern showed machinery injuries 28.5% as the largest group, followed by falls & falling objects 17.3%, fire & electric 15.1%, struke by an object 14.5%, followed by overaction and vehicular accidents. The accident pattern showed 46.4 % among workers over the 50 year age group, workers in the 5~10 year group, 50.0 % places employing more than 1000 workers, 35.3 % : construction 73.7%, and construction workers 57.1%, among these fall & falling objects caused the greatest number of injuries. 4. The largest group of injuries was fractures 54.8%, trauma 14.5%, amputation 11.7%, open wound, and burns. The largest number of fractures occurred in people in the 30~39 year age group, 63.2 % over 10 years of work, 55.6% in work places of 300~400 people, 63.6% construction 63.2% and general workers 57.2 %. 5. The largest group of injuries was upper extremity 45.3%, lower extremity 24.0%, trunk 18.5 % and head or neck 12.2%. Of these groups, upper extremity injuries were the highest in those less 20 years old 75.0%, less than 1 years of work 59.5%, in work places of 500~999 people 60.0%, manufacturing 56.6 % and production workers 55.6%. 6. Periods of injury showed 34 people injured in September, to be the largest followed by October, 32 August, 22 people July, 19 people and the lowest December, 2 people. During the week, Friday had the largest group injured, 35 people followed by Saturday, 26 people and the lowest was Wednesday, 17 people, During the day 1400 hours had the largest group injured, 38 people followed by 800 hours, 31 people. 7. On a basis of 5 as the highest mark, the average, according to worker satisfaction showed facility safety 3.55, work environment 3.47, income 3.44, job 3.21 and treatment 2.98. 8. The correlation between general characteristics and injury showed that age was directly correlated to the duration of work(r=.2591) p<0.01, age was directly correlated to industry (r=2311) p<0.01, and the duration was directly correlated to occupation(r =.4372) p<0.001.

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