Real-Time Risk Management in Digital Agriculture: Preventive Approach with Dynamic Risk Analysis
DOI:
https://doi.org/10.24925/turjaf.v13i6.1562-1570.7690Keywords:
Digital Agriculture, Occupational Health and Safety, Dynamic Risk Analysis, SWOT Analysis, Real-Time Risk ManagementAbstract
This study explores the implementation of DRA in high-risk sectors, with a particular focus on the agricultural industry, where environmental variables, mechanized operations, and chemical exposure pose significant threats. The integration of sensor networks, UAV (enthusiast piloted his camera-equippedes), weather monitoring stations, and AI-driven analytics ensures that risk assessments are consistently updated, providing actionable insights for occupational safety and productivity enhancement. In a case study in an off-grid orchard, the application of DRA is demonstrated by theoretically combining satellite-based internet, GPS modules and automatic data processing systems to optimize risk monitoring and intervention strategies. The findings underscore the advantages of DRA, including real-time hazard detection, improved worker safety, and enhanced resilience against unforeseen environmental changes. The study also presents a comparative SWOT analysis between traditional risk assessment methods and DRA, highlighting their strengths and weaknesses in predictive analysis and adaptive risk management. This study is the first in Turkish literature to be written on the subject of dynamic risk analysis, a new concept, in the field of technology use in agriculture, occupational health and safety. Within the scope of the study, it is a theoretically based study that identifies and defines risks suitable for agriculture, determines regulatory activities in accordance with DRA, compares them with traditional risk monitoring methods, and examines them in terms of conceptuality and applicability with SWOT analysis.
References
Aby, G., ve Issa, S. (2023). Safety of Automated Agricultural Machineries: A Systematic Literature Review. Safety. https://doi.org/10.3390/safety9010013.
Adedigba, S., Khan, F., ve Yang, M. (2018a). An integrated approach for dynamic economic risk assessment of process systems. Process Safety and Environmental Protection, 116, 312-323. https://doi.org/10.1016/j.psep.2018.01.013.
Adedigba, S., Oloruntobi, O., Khan, F., ve Butt, S. (2018b). Data-driven dynamic risk analysis of offshore drilling operations. Journal of Petroleum Science and Engineering. https://doi.org/10.1016/j.petrol.2018.02.049.
Alessandroni V. (2023). Information and Communication Technologies. In P. Vurchio & A. Işıtan (Eds.), Digital Traineeship in Agriculture (pp. 24–62). Duvar Yayınları. https://www.duvaryayinlari.com/Webkontrol/IcerikYonetimi/Dosyalar/digital-traineeship-in-agriculture-e-yayin_icerik_g3981_6bAwpDUL.pdf
Arcury, T., Quandt, S., ve Russell, G. (2001). Pesticide safety among farmworkers: perceived risk and perceived control as factors reflecting environmental justice. Environmental Health Perspectives, 110, 233- 240. https://doi.org/10.1289/ehp.02110s2233.
Arıcak, F. (2025). İHAe Use in Agricultural Spraying: An Examination in Terms of Occupational Health and Safety. Turkish Journal of Agriculture- Food Science and Technology, 13(3), 664–668. https://doi.org/10.24925/turjaf.v13i3.664-668.7230.
Bijay, B., George, P., Renjith, V., ve Kurian, A. (2020). Application of dynamic risk analysis in offshore drilling processes. Journal of Loss Prevention in The Process Industries, 68, 104326. https://doi.org/10.1016/j.jlp.2020.104326.
Carvalho, F. (2017). Pesticides, environment, and food safety. Food and Energy Security, 6, 48-60. https://doi.org/10.1002/fes3.108.
Cheimonidis, P., ve Rantos, K. (2023). Dynamic Risk Assessment in Cybersecurity: A Systematic Literature Review. Future Internet, 15, 324. https://doi.org/10.3390/fi15100324.
Curl, C., Spivak, M., Phinney, R., ve Montrose, L. (2020). Synthetic Pesticides and Health in Vulnerable Populations: Agricultural Workers. Current Environmental Health Reports, 7, 13- 29. https://doi.org/10.1007/s40572-020-00266-5.
Damalas, C., ve Koutroubas, S. (2016). Farmers’ Exposure to Pesticides: Toxicity Types and Ways of Prevention. Toxics, 4. https://doi.org/10.3390/toxics4010001.
Dhananjayan, V., ve Ravichandran, B. (2018). Occupational health risk of farmers exposed to pesticides in agricultural activities. Current Opinion in Environmental Science ve Health. https://doi.org/10.1016/j.coesh.2018.07.005.
Elahi, E., Khalid, Z., Tauni, M., Zhang, H., ve Xing, L. (2021). Extreme weather events risk to crop-production and the adaptation of innovative management strategies to mitigate the risk: A retrospective survey of rural Punjab, Pakistan. Technovation, 102255. https://doi.org/10.1016/j.technovatıon.2021.102255.
Gerberich, S., Gibson, R., French, L., Lee, T., Carr, W., Kochevar, L., Renier, C., ve Shutske, J. (1998). Machinery-related injuries: regional rural injury study--I (RRIS--I). Accident; analysis and prevention, 30 6, 793-804. https://doi.org/10.1016/s0001-4575(98)00032-3.
Gobin, A., Tarquis, A., ve Dalezios, N. (2013). Weather-related hazards and risks in agriculture”.
Gürel, E., ve Tat, M. (2017). SWOT analysis: A theoretical review. Journal of International Social Research, 10(51), 994–1006.
Haro-Monteagudo, D., Knox, J., ve Holman, I. (2019). D-Risk: A decision-support webtool for improving drought risk management in irrigated agriculture. Computers and Electronics in Agriculture. https://doi.org/10.1016/j.compag.2019.05.029.
Ilbahar, E., Karaşan, A., Çebi, S., ve Kahraman, C. (2018). A novel approach to risk assessment for occupational health and safety using Pythagorean fuzzy AHP ve fuzzy inference system. Safety Science, 103, 124-136. https://doi.org/10.1016/j.sscı.2017.10.025.
Khayat, M., Halwani, D., Hneiny, L., Alameddine, I., Haidar, M., ve Habib, R. (2022). Impacts of Climate Change and Heat Stress on Farmworkers' Health: A Scoping Review. Frontiers in Public Health, 10. https://doi.org/10.3389/fpubh.2022.782811.
Kim, J., Shah, A., ve Kang, H. (2020). Dynamic risk assessment with bayesian network and clustering analysis. Reliab. Eng. Syst. Saf., 201, 106959. https://doi.org/10.1016/j.ress.2020.106959.
Kim, K., Kabir, E., ve Jahan, S. (2017). Exposure to pesticides and the associated human health effects.. The Science of the total environment, 575, 525-535. https://doi.org/10.1016/j.scitotenv.2016.09.009.
Kim, K., Kim, H., Lee, M., Jung, W., ve Choi, D. (2022). Incidence Rates of Agricultural Machine-Related Injuries in South Korea. International Journal of Environmental Research and Public Health, 19. https://doi.org/10.3390/ijerph192315588.
Kumar, M., ve Motha, R. (2007). Managing weather and climate risks in agriculture. . https://doi.org/10.1007/978-3-540-72746-0.
Layde, P., Nordstrom, D., Stueland, D., Stueland, D., Brand, L., ve Olson, K. (1995). Machine-related occupational injuries in farm residents. Annals of epidemiology, 5 6, 419-26 . https://doi.org/10.1016/1047-2797(95)00056-9.
Lee, C., Yoon, J., ve Schaar, M. (2020). Dynamic-DeepHit: A Deep Learning Approach for Dynamic Survival Analysis With Competing Risks Based on Longitudinal Data. IEEE Transactions on Biomedical Engineering, 67, 122-133. https://doi.org/10.1109/tbme.2019.2909027.
Lee, S., Landucci, G., Reniers, G., ve Paltrinieri, N. (2019). Validation of Dynamic Risk Analysis Supporting Integrated Operations Across Systems. Sustainability, 11, 6745. https://doi.org/10.3390/su11236745.
Liu, H., Wang, J., Zhang, L., ve Chen, Q. (2023). An integrated model for occupational health and safety risk assessment based on probabilistic linguistic information and social network consensus analysis. Journal of the Operational Research Society, 75, 1308- 1324. https://doi.org/10.1080/01605682.2023.2242371.
Liu, R., Zhu, Y., Chen, Y., ve Liu, H. (2021). Occupational health and safety risk assessment using an integrated TODIM‐PROMETHEE model under linguistic spherical fuzzy environment. International Journal of Intelligent Systems, 36, 6814- 6836. https://doi.org/10.1002/int.22570.
Mamudu, A., Khan, F., Zendehboudi, S., ve Adedigba, S. (2021). Dynamic risk modeling of complex hydrocarbon production systems. Process Safety and Environmental Protection. https://doi.org/10.1016/j.psep.2021.04.046.
Marcelino, A., Wachtel, C., ve Ghisi, N. (2019). Are Our Farm Workers in Danger? Genetic Damage in Farmers Exposed to Pesticides. International Journal of Environmental Research and Public Health, 16. https://doi.org/10.3390/ijerph16030358.
Mohan, S.S., Ajay, A. and Jayan, P.R. 2021. GPS and Sensor Based Technologies in Variable Rate Fertilizer Application. IJAEB, 14(1): 21-27.
Moreira, A., ve Da Silva, M. (2023). Pesticide Application as a Risk Factor/Behaviour for Workers’ Health: A Systematic Review. Environments. https://doi.org/10.20944/preprints202308.1406.v1
Mubiru, D., Radeny, M., Kyazze, F., Zziwa, A., Lwasa, J., Kinyangi, J., ve Mungai, C. (2018). Climate trends, risks and coping strategies in smallholder farming systems in Uganda. Climate Risk Management, 22, 4-21. https://doi.org/10.1016/j.crm.2018.08.004.
Mutlu, N., ve Altuntas, S. (2021). Developing an integrated conceptual framework for monitoring and controlling risks related to occupational health and safety. Journal of Engineering Research. https://doi.org/10.36909/jer.9959.
Noerrung, B., Collins, D., Budka, H., ve Hugas, M. (2012). Risk assessment of biological hazards for consumer protection. EFSA Journal, 10, 1-8. https://doi.org/10.2903/j.efsa.2012.s1003.
Paltrinieri, N., ve Khan, F. (2020). Dynamic risk analysis—Fundamentals. Advanced Methods of Risk Assessment and Management. https://doi.org/10.1016/bs.mcps.2020.04.001.
Ramos-García, V., López-Leyva, J., Balderrama-Carmona, A., Ochoa-Vázquez, I., García-Ochoa, J., ve De Jesús Espinoza-Espino, M. (2024). An Analysis of Occupational Hazards Based on the Physical Ergonomics Dimension to Improve the Occupational Health of Agricultural Workers: The Case in Mayo Valley, Mexico. Safety. https://doi.org/10.3390/safety10030061
Rani, L., Thapa, K., Kanojia, N., Sharma, N., Singh, S., Grewal, A., Srivastav, A., ve Kaushal, J. (2020). An extensive review on the consequences of chemical pesticides on human health and environment. Journal of Cleaner Production, 124657. https://doi.org/10.1016/j.jclepro.2020.124657
Raza, M., Li, S., ve Issa, S. (2024). Global Patterns of Agricultural Machine and Equipment Injuries- A Systematic Literature Review. Journal of Agromedicine, 29, 214 - 234. https://doi.org/10.1080/1059924x.2024.2304704.
Ryan, M., Isakhanyan, G., ve Tekinerdogan, B. (2023). An interdisciplinary approach to artificial intelligence in agriculture. NJAS: Impact in Agricultural and Life Sciences, 95(1). https://doi.org/10.1080/27685241.2023.2168568
Sanderson, M., Stanton, N., ve Plant, K. (2020). Individual Dynamic Risk Analysis (iDRA): A systematic review and network model development. Safety Science, 128, 104769. https://doi.org/10.1016/j.ssci.2020.104769.
Shemyakin, A., Lyashchuk, Y., Martynushkin, A., Ivanishchev, K., Strokova, E., ve Krasnikov, A. (2021). Analysis and assessment of the level of biological risks of activities of enterprises of the agro-industrial complex at the regional level. E3S Web of Conferences. https://doi.org/10.1051/e3sconf/202125806057.
Shutske, J., Sandner, K., ve Jamieson, Z. (2023). Risk Assessment Methods for Autonomous Agricultural Machines: A Review of Current Practices and Future Needs. Applied Engineering in Agriculture. https://doi.org/10.13031/aea.15281.
Tang, F., Lenzen, M., McBratney, A., ve Maggi, F. (2021). Risk of pesticide pollution at the global scale. Nature Geoscience, 14, 206 - 210. https://doi.org/10.1038/s41561-021-00712-5.
Tsopa, V., Cheberiachko, S., Yavorska, O., Deryugin, O., ve Borovytskyi, О. (2023). Improving a process of managing dynamic occupational risks. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. https://doi.org/10.33271/nvngu/2023-4/110.
Tudi, M., Li, H., Li, H., Wang, L., Lyu, J., Yang, L., Tong, S., Yu, Q., Ruan, H., Atabila, A., Phung, D., Sadler, R., ve Connell, D. (2022). Exposure Routes and Health Risks Associated with Pesticide Application. Toxics, 10. https://doi.org/10.3390/toxics10060335.
Tudi, M., Ruan, H., Wang, L., Lyu, J., Sadler, R., Connell, D., Chu, C., ve Phung, D. (2021). Agriculture Development, Pesticide Application and Its Impact on the Environment. International Journal of Environmental Research and Public Health, 18. https://doi.org/10.3390/ijerph18031112.
Vantarakis, A., ve Dimitrakopoulou, M. (2022). Risk analysis of biological hazards in food industry in terms of Public Health. The European Journal of Public Health, 32. https://doi.org/10.1093/eurpub/ckac131.231.
Villa, V., Paltrinieri, N., Khan, F., ve Cozzani, V. (2016). Towards dynamic risk analysis: A review of the risk assessment approach and its limitations in the chemical process industry. Safety Science, 89, 77-93. https://doi.org/10.1016/j.sscı.2016.06.002.
Vroege, W., ve Finger, R. (2020). Insuring Weather Risks in European Agriculture. EuroChoices. https://doi.org/10.1111/1746-692x.12285.
Wang, Q., ve Mu, Z. (2022). Risk monitoring model of intelligent agriculture Internet of Things based on big data. Sustainable Energy Technologies and Assessments, 53, 102654.
Zeng, Z., ve Zio, E. (2018). Dynamic Risk Assessment Based on Statistical Failure Data and Condition-Monitoring Degradation Data. IEEE Transactions on Reliability, 67, 609-622. https://doi.org/10.1109/tr.2017.2778804.
Zheng, L., Zhao, N., Chen, D., Hu, M., Fu, X., Stallones, L., Xiang, H., ve Wang, Z. (2014). Nonfatal work-related injuries among agricultural machinery operators in northern China: a cross-sectional study.. Injury, 45 3, 599-604 . https://doi.org/10.1016/j.injury.2013.07.004.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
