REDECA: A Novel Framework to Review Artificial Intelligence and Its Applications in Occupational Safety and Health

被引:30
作者
Pishgar, Maryam [1 ]
Issa, Salah Fuad [2 ]
Sietsema, Margaret [3 ]
Pratap, Preethi [3 ]
Darabi, Houshang [1 ]
机构
[1] Univ Illinois, Mech & Ind Engn, Chicago, IL 60609 USA
[2] Univ Illinois, Agr & Biol Engn, Urbana, IL 61801 USA
[3] Univ Illinois, Environm & Occupat Hlth Sci, Chicago, IL 60612 USA
关键词
artificial intelligence; worker health and safety; occupational safety and health; sensor devices; robotic devices; machine learning algorithms; future of work; WIRELESS SENSOR NETWORKS; FALL DETECTION SYSTEM; DRIVER DROWSINESS DETECTION; HUMAN-ROBOT INTERACTION; MONITORING-SYSTEM; LEAKAGE DETECTION; FATIGUE; OIL; DISORDERS; DESIGN;
D O I
10.3390/ijerph18136705
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Introduction: The field of artificial intelligence (AI) is rapidly expanding, with many applications seen routinely in health care, industry, and education, and increasingly in workplaces. Although there is growing evidence of applications of AI in workplaces across all industries to simplify and/or automate tasks there is a limited understanding of the role that AI contributes in addressing occupational safety and health (OSH) concerns. Methods: This paper introduces a new framework called Risk Evolution, Detection, Evaluation, and Control of Accidents (REDECA) that highlights the role that AI plays in the anticipation and control of exposure risks in a worker's immediate environment. Two hundred and sixty AI papers across five sectors (oil and gas, mining, transportation, construction, and agriculture) were reviewed using the REDECA framework to highlight current applications and gaps in OSH and AI fields. Results: The REDECA framework highlighted the unique attributes and research focus of each of the five industrial sectors. The majority of evidence of AI in OSH research within the oil/gas and transportation sectors focused on the development of sensors to detect hazardous situations. In construction the focus was on the use of sensors to detect incidents. The research in the agriculture sector focused on sensors and actuators that removed workers from hazardous conditions. Application of the REDECA framework highlighted AI/OSH strengths and opportunities in various industries and potential areas for collaboration. Conclusions: As AI applications across industries continue to increase, further exploration of the benefits and challenges of AI applications in OSH is needed to optimally protect worker health, safety and well-being.
引用
收藏
页数:42
相关论文
共 259 条
[1]   Wireless Sensor Networks in oil and gas industry: Recent advances, taxonomy, requirements, and open challenges [J].
Aalsalem, Mohammed Y. ;
Khan, Wazir Zada ;
Gharibi, Wajeb ;
Khan, Muhammad Khurram ;
Arshad, Quratulain .
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2018, 113 :87-97
[2]   Adopting BIM Technology in Fall Prevention Plans [J].
Abed, Hayder R. ;
Hatem, Wadhah A. ;
Jasim, Nidal A. .
CIVIL ENGINEERING JOURNAL-TEHRAN, 2019, 5 (10) :2270-2281
[3]   Design and development of a semi-autonomous agricultural vineyard sprayer: Human-robot interaction aspects [J].
Adamides, George ;
Katsanos, Christos ;
Constantinou, Ioannis ;
Christou, Georgios ;
Xenos, Michalis ;
Hadzilacos, Thanasis ;
Edan, Yael .
JOURNAL OF FIELD ROBOTICS, 2017, 34 (08) :1407-1426
[4]   HRI usability evaluation of interaction modes for a teleoperated agricultural robotic sprayer [J].
Adamides, George ;
Katsanos, Christos ;
Parmet, Yisrael ;
Christou, Georgios ;
Xenos, Michalis ;
Hadzilacos, Thanasis ;
Edan, Yael .
APPLIED ERGONOMICS, 2017, 62 :237-246
[5]   Usability Guidelines for the Design of Robot Teleoperation: A Taxonomy [J].
Adamides, George ;
Christou, Georgios ;
Katsanos, Christos ;
Xenos, Michalis ;
Hadzilacos, Thanasis .
IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS, 2015, 45 (02) :256-262
[6]   User interface considerations for telerobotics: The case of an agricultural robot sprayer [J].
Adamides, George ;
Katsanos, Christos ;
Christou, Georgios ;
Xenos, Michalis ;
Papadavid, Giorgos ;
Hadzilacos, Thanasis .
SECOND INTERNATIONAL CONFERENCE ON REMOTE SENSING AND GEOINFORMATION OF THE ENVIRONMENT (RSCY2014), 2014, 9229
[7]   System architecture to bring smart personal protective equipment wearables and sensors to transform safety at work in the underground mining industry [J].
Adjiski, Vancho ;
Despodov, Zoran ;
Mirakovski, Dejan ;
Serafimovski, Dalibor .
RUDARSKO-GEOLOSKO-NAFTNI ZBORNIK, 2019, 34 (01) :37-44
[8]   A Novel Benchmark RGBD Dataset for Dormant Apple Trees and its Application to Automatic Pruning [J].
Akbar, Shayan A. ;
Chattopadhyay, Somrita ;
Elfiky, Noha M. ;
Kak, Avinash .
PROCEEDINGS OF 29TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, (CVPRW 2016), 2016, :347-354
[9]   A comparative study of remote sensing classification methods for monitoring and assessing desert vegetation using a UAV-based multispectral sensor [J].
Al-Ali, Z. M. ;
Abdullah, M. M. ;
Asadalla, N. B. ;
Gholoum, M. .
ENVIRONMENTAL MONITORING AND ASSESSMENT, 2020, 192 (06)
[10]  
Al-Jaroodi J., 2010, 12 IEEE INT C HIGH P, DOI [10.1109/HPCC.2010.98, DOI 10.1109/HPCC.2010.98]