Decision support in a remote health monitoring system for shift workers on an offshore oil platform
Keywords:
Offshore oil platforms, Internet of things, distributed intelligent health management system, expert assessment, decision makingSynopsis
This chapter proposes a methodological approach for the decision synthesis in a geographically distributed intelligent health management system for oil workers working in offshore industry. The decision-making methodology is based on the concept of a person-centered approach to managing the health and safety of personnel, which implies the inclusion of employees as the main component in the control loop. In this chapter, a functional model of the health management system for workers employed on offshore oil platforms id developed and implemented through three phased operations that is monitoring and assessing the health indicators and environmental parameters of each employee, and making decisions. These interacting operations combine the levels of a distributed intelligent health management system. The paper offers the general principles of functioning of a distributed intelligent system for managing the health of workers in the context of structural components and computing platforms. It presents appropriate approaches to the implementation of decision support processes and describes one of the possible methods for evaluating the generated data and making decisions using fuzzy pattern recognition. The models of a fuzzy ideal image and fuzzy real images of the health status of an employee are developed and an algorithm is described for expert assessment of the deviation of generated medical parameters from the norm. The chapter also compiles the rules to form the knowledge bases of a distributed intelligent system for remote continuous monitoring. It is assumed that embedding this base into the intelligent system architecture will objectively assess the trends in the health status of workers and make informed decisions to eliminate certain problems.
References
John, A., Igimoh, J. (2017). The Design of Wireless Sensor Network for Real Time Remote Monitoring of Oil & Gas Flow Rate Metering Infrastructure. International Journal of Science and Research, 6 (2), 425–429.
Khan, W. Z., Aalsalem, M. Y., Khan, M. K., Hossain, Md. S., Atiquzzaman, M. (2017). A reliable Internet of Things based architecture for oil and gas industry. 2017 19th International Conference on Advanced Communication Technology (ICACT), 705–710. doi: https://doi.org/10.23919/icact.2017.7890184
Wanasinghe, T. R., Gosine, R. G., James, L. A., Mann, G. K. I., de Silva, O., Warrian, P. J. (2020). The Internet of Things in the Oil and Gas Industry: A Systematic Review. IEEE Internet of Things Journal, 7 (9), 8654–8673. doi: https://doi.org/10.1109/jiot.2020.2995617
Lalitha, K., Balakumar, V., Yogesh, S., Sriram, K. M., Mithilesh, V. (2020). IoT Enabled Pipeline Leakage Detection and Real Time Alert System in Oil and Gas Industry. International Journal of Recent Technology and Engineering, 8 (1), 2582–2586. Available at: https://www.ijrte.org/wp-content/uploads/papers/v8i5/E6380018520.pdf
Silva, V. L., Kovaleski, J. L., Pagani, R. N., Corsi, A., Gomes, M. A. S. (2020). Human Factor in Smart Industry: A Literature Review. Future Studies Research Journal: Trends and Strategies, 12 (1), 87–111. doi: https://doi.org/10.24023/futurejournal/2175-5825/2020.v12i1.473
Antonovsky, A., Pollock, C., Straker, L. (2013). Identification of the Human Factors Contributing to Maintenance Failures in a Petroleum Operation. Human Factors: The Journal of the Human Factors and Ergonomics Society, 56(2), 306–321. doi: https://doi.org/10.1177/0018720813491424
Riazul Islam, S. M., Daehan Kwak, Humaun Kabir, M., Hossain, M., Kyung-Sup Kwak. (2015). The Internet of Things for Health Care: A Comprehensive Survey. IEEE Access, 3, 678–708. doi: https://doi.org/10.1109/access.2015.2437951
Majumder, S., Mondal, T., Deen, M. (2017). Wearable Sensors for Remote Health Monitoring. Sensors, 17 (12), 130. doi: https://doi.org/10.3390/s17010130
Castillejo, P., Martinez, J.-F., Rodriguez-Molina, J., Cuerva, A. (2013). Integration of wearable devices in a wireless sensor network for an E-health application. IEEE Wireless Communications, 20 (4), 38–49. doi: https://doi.org/10.1109/mwc.2013.6590049
Thibaud, M., Chi, H., Zhou, W., Piramuthu, S. (2018). Internet of Things (IoT) in high-risk Environment, Health and Safety (EHS) industries: A comprehensive review. Decision Support Systems, 108, 79–95. doi: https://doi.org/10.1016/j.dss.2018.02.005
Mammadova, M. H., Jabrayilova, Z. G. (2020). Human factor of a health management system for shift workers in offshore oil and gas industry. Problems of information technology, 2, 13–31. doi: https://doi.org/10.25045/jpit.v11.i2.02
Mammadova, M. H., Jabrayilova, Z. G. (2021). Conceptual approaches to intelligent human factor management on offshore oil and gas platforms. ARCTIC Journal 74 (2), 19–40.
Mammadova, M. H., Jabrayilova, Z. G. (2020). Conceptual approaches to IoT-based personnel health management in offshore oil and gas industry. Proceedings of the7th International Conference on Control and Optimization with Industrial Applications (COIA 2020). Baku, 1, 257–259. Available at: http://coia-conf.org/upload/editor/files/COIA2020_V1.pdf
Mammadova, M., Jabrayilova, Z. (2022). Synthesis of decision making in a distributed intelligent personnel health management system on offshore oil platform. EUREKA: Physics and Engineering, 4, 179–192. doi: https://doi.org/10.21303/2461-4262.2022.002520
Mammadova, M. H., Jabrayilova, Z. G. (2022). An algorithm for the decision synthesis in the remote monitoring system of physiological state of workers employed at high-risk facilities. Proceedings of the 8th Conference on Control and Optimization with Industrial Applications-COIA’2022. Baku, 315–317.
Ljoså, C. H., Tyssen, R., Lau, B. (2011). Mental distress among shift workers in Norwegian offshore petroleum industry – relative influence of individual and psychosocial work factors. Scandinavian Journal of Work, Environment & Health, 37 (6), 551–555. doi: https://doi.org/10.5271/sjweh.3191
Chauhan, N. (2013). Safety and health management system in Oil and Gas industry. WIRPO, 12. Available at: http://www.hpaf.co.uk/wp-content/uploads/2018/01/Safety-and-Health-Management-System-in-Oil-and-Gas-Industry.pdf
Directive 2013//30/EU on the safety of offshore oil and gas operations (2013). Official Journal of the European Union Available at: https://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2013:178:0066:0106:EN:PDF
Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning – I. Information Sciences, 8 (3), 199–249. doi: https://doi.org/10.1016/0020-0255(75)90036-5
Melikhov, A. N., Bernshtein L. S., Korovin, S. Ya. (1990). Situatcionnye sovetuiushchie sistemy s nechetkoi logikoi. Moscow: Nauka, 272.
Bellman, R. E., Zadeh, L. A. (1970). Decision-Making in a Fuzzy Environment. Management Science, 17 (4), B-141-B-164. doi: https://doi.org/10.1287/mnsc.17.4.b141
Levin, V. I. (2001). A new generalization of operations on fuzzy sets. Journal of Computer and Systems Sciences International, 40 (1), 138–141. Available at: https://elibrary.ru/item.asp?id=14956908
Ganina, Ia. O., Laptev, V. V. (2016). Fuzzy productive model for evaluation of professional qualities of sea experts. Vestnik Astrakhanskogo gosudarstvennogo tekhnicheskogo universiteta. Seriia: Upravlenie, vychislitelnaia tekhnika i informatika, 3, 101–108.
Mammadova, M. H., Jabrayilova, Z. G. (2021). The intelligent monitoring and evaluation of the psychophysiological state of the ship crew in maritime transport. International Conference on Problems of Logistics, Management and Operation in the East-West Transport Corridor. Baku, 242–247.
Mammadova, M. H., Jabrayilova, Z. G. (2019). Methods Managing for Matching of Supply and Demand on the IT Specialists. Automatic Control and Computer Sciences, 53 (2), 148–158. doi: https://doi.org/10.3103/s0146411619020044
Mammadova, M. H., Jabrayilova, Z. G., Mammadzada, F. R. (2016). Fuzzy Multi-scenario Approach to Decision-Making Support in Human Resource Management. Recent Developments and New Direction in Soft-Computing Foundations and Applications. Vol. 342. Springer International Publishing Switzerland, 19–36. doi: https://doi.org/10.1007/978-3-319-32229-2_3
Mammadova, M. H., Jabrayilova, Z. G. (2018). Fuzzy multi-criteria method to support group decision making in human resource management. Recent Developments and New Direction in Soft-Computing Foundations and Applications. Vol. 361. Springer International Publishing Switzerland, 223–232. doi: https://doi.org/10.1007/978-3-319-75408-6_17
Khan, W. Z., Aalsalem, M. Y., Khan, M. K., Hossain, Md. S., Atiquzzaman, M. (2017). A reliable Internet of Things based architecture for oil and gas industry. 2017 19th International Conference on Advanced Communication Technology (ICACT), 705–710. doi: https://doi.org/10.23919/icact.2017.7890184
Wanasinghe, T. R., Gosine, R. G., James, L. A., Mann, G. K. I., de Silva, O., Warrian, P. J. (2020). The Internet of Things in the Oil and Gas Industry: A Systematic Review. IEEE Internet of Things Journal, 7 (9), 8654–8673. doi: https://doi.org/10.1109/jiot.2020.2995617
Lalitha, K., Balakumar, V., Yogesh, S., Sriram, K. M., Mithilesh, V. (2020). IoT Enabled Pipeline Leakage Detection and Real Time Alert System in Oil and Gas Industry. International Journal of Recent Technology and Engineering, 8 (1), 2582–2586. Available at: https://www.ijrte.org/wp-content/uploads/papers/v8i5/E6380018520.pdf
Silva, V. L., Kovaleski, J. L., Pagani, R. N., Corsi, A., Gomes, M. A. S. (2020). Human Factor in Smart Industry: A Literature Review. Future Studies Research Journal: Trends and Strategies, 12 (1), 87–111. doi: https://doi.org/10.24023/futurejournal/2175-5825/2020.v12i1.473
Antonovsky, A., Pollock, C., Straker, L. (2013). Identification of the Human Factors Contributing to Maintenance Failures in a Petroleum Operation. Human Factors: The Journal of the Human Factors and Ergonomics Society, 56(2), 306–321. doi: https://doi.org/10.1177/0018720813491424
Riazul Islam, S. M., Daehan Kwak, Humaun Kabir, M., Hossain, M., Kyung-Sup Kwak. (2015). The Internet of Things for Health Care: A Comprehensive Survey. IEEE Access, 3, 678–708. doi: https://doi.org/10.1109/access.2015.2437951
Majumder, S., Mondal, T., Deen, M. (2017). Wearable Sensors for Remote Health Monitoring. Sensors, 17 (12), 130. doi: https://doi.org/10.3390/s17010130
Castillejo, P., Martinez, J.-F., Rodriguez-Molina, J., Cuerva, A. (2013). Integration of wearable devices in a wireless sensor network for an E-health application. IEEE Wireless Communications, 20 (4), 38–49. doi: https://doi.org/10.1109/mwc.2013.6590049
Thibaud, M., Chi, H., Zhou, W., Piramuthu, S. (2018). Internet of Things (IoT) in high-risk Environment, Health and Safety (EHS) industries: A comprehensive review. Decision Support Systems, 108, 79–95. doi: https://doi.org/10.1016/j.dss.2018.02.005
Mammadova, M. H., Jabrayilova, Z. G. (2020). Human factor of a health management system for shift workers in offshore oil and gas industry. Problems of information technology, 2, 13–31. doi: https://doi.org/10.25045/jpit.v11.i2.02
Mammadova, M. H., Jabrayilova, Z. G. (2021). Conceptual approaches to intelligent human factor management on offshore oil and gas platforms. ARCTIC Journal 74 (2), 19–40.
Mammadova, M. H., Jabrayilova, Z. G. (2020). Conceptual approaches to IoT-based personnel health management in offshore oil and gas industry. Proceedings of the7th International Conference on Control and Optimization with Industrial Applications (COIA 2020). Baku, 1, 257–259. Available at: http://coia-conf.org/upload/editor/files/COIA2020_V1.pdf
Mammadova, M., Jabrayilova, Z. (2022). Synthesis of decision making in a distributed intelligent personnel health management system on offshore oil platform. EUREKA: Physics and Engineering, 4, 179–192. doi: https://doi.org/10.21303/2461-4262.2022.002520
Mammadova, M. H., Jabrayilova, Z. G. (2022). An algorithm for the decision synthesis in the remote monitoring system of physiological state of workers employed at high-risk facilities. Proceedings of the 8th Conference on Control and Optimization with Industrial Applications-COIA’2022. Baku, 315–317.
Ljoså, C. H., Tyssen, R., Lau, B. (2011). Mental distress among shift workers in Norwegian offshore petroleum industry – relative influence of individual and psychosocial work factors. Scandinavian Journal of Work, Environment & Health, 37 (6), 551–555. doi: https://doi.org/10.5271/sjweh.3191
Chauhan, N. (2013). Safety and health management system in Oil and Gas industry. WIRPO, 12. Available at: http://www.hpaf.co.uk/wp-content/uploads/2018/01/Safety-and-Health-Management-System-in-Oil-and-Gas-Industry.pdf
Directive 2013//30/EU on the safety of offshore oil and gas operations (2013). Official Journal of the European Union Available at: https://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2013:178:0066:0106:EN:PDF
Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning – I. Information Sciences, 8 (3), 199–249. doi: https://doi.org/10.1016/0020-0255(75)90036-5
Melikhov, A. N., Bernshtein L. S., Korovin, S. Ya. (1990). Situatcionnye sovetuiushchie sistemy s nechetkoi logikoi. Moscow: Nauka, 272.
Bellman, R. E., Zadeh, L. A. (1970). Decision-Making in a Fuzzy Environment. Management Science, 17 (4), B-141-B-164. doi: https://doi.org/10.1287/mnsc.17.4.b141
Levin, V. I. (2001). A new generalization of operations on fuzzy sets. Journal of Computer and Systems Sciences International, 40 (1), 138–141. Available at: https://elibrary.ru/item.asp?id=14956908
Ganina, Ia. O., Laptev, V. V. (2016). Fuzzy productive model for evaluation of professional qualities of sea experts. Vestnik Astrakhanskogo gosudarstvennogo tekhnicheskogo universiteta. Seriia: Upravlenie, vychislitelnaia tekhnika i informatika, 3, 101–108.
Mammadova, M. H., Jabrayilova, Z. G. (2021). The intelligent monitoring and evaluation of the psychophysiological state of the ship crew in maritime transport. International Conference on Problems of Logistics, Management and Operation in the East-West Transport Corridor. Baku, 242–247.
Mammadova, M. H., Jabrayilova, Z. G. (2019). Methods Managing for Matching of Supply and Demand on the IT Specialists. Automatic Control and Computer Sciences, 53 (2), 148–158. doi: https://doi.org/10.3103/s0146411619020044
Mammadova, M. H., Jabrayilova, Z. G., Mammadzada, F. R. (2016). Fuzzy Multi-scenario Approach to Decision-Making Support in Human Resource Management. Recent Developments and New Direction in Soft-Computing Foundations and Applications. Vol. 342. Springer International Publishing Switzerland, 19–36. doi: https://doi.org/10.1007/978-3-319-32229-2_3
Mammadova, M. H., Jabrayilova, Z. G. (2018). Fuzzy multi-criteria method to support group decision making in human resource management. Recent Developments and New Direction in Soft-Computing Foundations and Applications. Vol. 361. Springer International Publishing Switzerland, 223–232. doi: https://doi.org/10.1007/978-3-319-75408-6_17
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Pages
130-153
Text Identifier of this Chapter
Chapter 5
Published
December 19, 2023
Categories
- COM016000 Artificial Intelligence / Computer Vision & Pattern Recognition
- COM044000 Data Science / Neural Networks
- COM095000 Internet of Things (IoT)
- COMPUTERS
- LAW
- LAW041000 Forensic Science
- MED003040 Allied Health Services / Medical Technology
- MED018000 Diagnosis
- MED037000 Health Risk Assessment
- MED062020 Oncology / Leukemia & Lymphoma
- MEDICAL
- POL017000 Public Affairs & Administration
- TEC009140 Civil / Highway & Traffic
- TEC009160 Civil / Transportation
- TEC047000 Petroleum
- TEC065000 Emergency Management
- TECHNOLOGY & ENGINEERING
Copyright (c) 2023 Masuma Mammadova, Zarifa Jabrayilova
How to Cite
Mammadova, M., & Jabrayilova, Z. (2023). Decision support in a remote health monitoring system for shift workers on an offshore oil platform. In D. Domin (Ed.), & N. Martynenko, A. Curtidor, M. Mammadova, G. Velasco Herrera, T. Baydyk, E. Kussul, Z. Jabrayilova, H. Gasimov, A. Ahmadova, V. Polishchuk, S. Yanishevskyi, O. Bilonoh, L. Nahrebelna, V. Trushevsky, A. Korchevskaya, O. Semenchenko, & I. Vyhovska, Expert assessments in decision making: risks and safety (pp. 130-153). Scientific Route OÜ®. https://doi.org/10.21303/978-9916-9850-2-1.ch5
