DEVELOPMENT OF A NEAR REAL-TIME WARNING AGRICULTURAL SYSTEM FOR DISASTER PREDICTION

Authors

  • Willbard Kamati Department of Computing, Mathematical & Statistical Sciences, University of Namibia, Namibia
  • Valerianus Hashiyana Department of Computing, Mathematical & Statistical Sciences, University of Namibia, Namibia
  • James Mutuku Department of Computing, Mathematical & Statistical Sciences, University of Namibia, Namibia

DOI:

https://doi.org/10.24191/mjoc.v9i1.24836

Keywords:

Agriculture, Disaster, Early Warning, Mitigation, Namibia

Abstract

The effects of disasters are not uniform across all individuals and communities. One’s preparedness and socioeconomic factors determine how much they will pay. Preparedness plays a crucial role in reducing the impact of disasters and aiding in their management and recovery. However, effectively preparing for unforeseen disasters becomes difficult when there is insufficient knowledge and expertise. Without accurate predictions and timely alerts about disasters, a community's level of readiness remains extremely low. Namibia has experienced various unavoidable climate-related dangers over time, making it vulnerable in the future. Inconsistencies in disseminating weather information and early disaster notifications are factors that obstruct the mitigation of climate-related disasters. Furthermore, disaster early warning system implementation has been slower in most African countries due to limited technical resources. Another notable challenge is upholding internationally standardized early warning systems in rural settings without overlooking the dynamics of the rural community, which leads to system ineffectiveness. Therefore, this study employed a mixed-methodology approach to gather qualitative and quantitative data from local farmers through the use of questionnaires to review the readiness to adopt early warning systems in northern Namibia, assess available technical resources, study the existing disaster mitigation practices in Namibia. Subsequently, historic and near real time weather data was collected from weather agencies, which ultimately designed and developed an early warning system to enhance resilience and preparedness for hazards and risks in farming communities by issuing comprehensive and timely alerts. The study confirmed the dire need for disaster prediction systems in Namibia, although it also highlighted pressing accessibility concerns that future researchers could study, especially under-resourced potential users.

References

Amadhila, E., Shaamhula, L., Rooy, G. v., & Siyambango, N. (2013). Disaster risk reduction in the Omusati and Oshana regions of Namibia. Retrieved from http://dx.doi.org/10.4102/jamba.v5i1.65

Baba-Adamu, M., & Jajere, I. A. (2021). Environmental determinant of rural households’ vulnerability to water scarcity in semi-arid Nigeria. Malaysian Journal of Computing, 6(2), 778-797.

Dhanalakshmi, S., Poongothai, M., & Sharma, K. (2020). IoT Based Indoor Air Quality and Smart Energy Management for HVAC System. Retrieved from https://doi.org/10.1016/j.procs.2020.04.193

Magomelo, M., Chikwiriro, H., & Gurure, C. (2014). An Implementation of Early Warning of Floods along Zambezi Basin Throughthe Use of Context Awareness. Retrieved from https://isindexing.com/papers/1409669609.pdf

Mbewe, M., Phiri, A., & Siyambango, N. (2019). Indigenous Knowledge Systems for Local Weather Predictions: A Case of Mukonchi Chiefdom in Zambia. Retrieved from https://doi.org/10.5539/enrr.v9n2p16

Moises, D. J., & Kunguma, O. (2023). Improving flood early warning systems in Kabbe, Namibia: A situational analysis approach. Retrieved from https://doi.org/10.1016/j.ijdrr.2023.103765

Mtega, W. P. (2017). Strengthening agricultural knowledge systems for improved rural livelihoods in Morogoro region of Tanzania. Retrieved from http://hdl.handle.net/10500/22964

Munywoki, M. N. (2020). Integrating a web-based GIS in the optimization of the customer connection process for utility company: A case of Kenya Power & Lighting Company, Ltd. Retrieved from https://open.uct.ac.za/bitstream/handle/11427/36035/thesis_ebe_2021_munywoki%20margaret%20ngeli.pdf?sequence=1

Muvhali, P. S. (2013). Using sensor web technologies to help predict and monitor floods in urban areas. Retrieved from https://open.uct.ac.za/bitstream/handle/11427/5590/thesis_ebe_2013_peter_muvhali_thesis.pdf?sequence=1&isAllowed=y

Muzuwa, T. (2017). Towards developing a prediction model for managing river flood disasters in the SADC-region. Retrieved from https://repository.nwu.ac.za/handle/10394/25590

Nashandi, N. T. (2020). A Persuasive Souvenir System (PSS) to increase Namibian museums turnout using RFID Technology. Retrieved from https://ir.nust.na/bitstream/10628/772/1/Master%20of%20Computer%20Science%20ThesisNashandi.pdf

Nawa, E.-L. T. (2021). Developing a cybersecurity framework for the banking sector of Namibia. Retrieved from https://ir.nust.na/bitstream/10628/817/1/DEVELOPING 20A%20CYBERSECURITY%20 FRAMEWORK%20FOR%20THE%20BANKING%20SECTOR 20OF%20NAMIBIA.pdf

Somses, S., Bopape, M.-J. M., Ndarana, T., Fridlind, A., Matsui, T., Phaduli, E., . . . Rakate, E. (2020). Convection Parametrization and Multi-Nesting Dependence of a Heavy Rainfall Event over Namibia with Weather Research and Forecasting (WRF) Model. Retrieved from https://doi.org/10.3390/cli8100112

Taapopi, M., Kamwi, J. M., & Siyambango, N. (2018). Perception of Farmers on Conservation Agriculture for Climate Change Adaptation in Namibia. Retrieved from https://doi.org/10.5539/enrr.v8n3p33

Taufik, S. N., Ishak, S. Z., Yusoff, Z. M., Jaafar, M. N., & Somenahalli, S. (2023, October 10). Methodological framework in applying geographic information system (GIS) for parking spaces data. Malaysian Journal of Computing, 8(2), 1639 1651.

UNDP. (2020). Climate Information and Early Warning Systems. Retrieved from https://www.undp.org/sites/g/files/zskgke326/files/publications/UNDP-Issues-BriefClimate-Information-and-Early-Warning-Systems-EN.pdf

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Published

2024-04-01

How to Cite

Kamati, W. ., Hashiyana, . V. ., & Mutuku, J. . (2024). DEVELOPMENT OF A NEAR REAL-TIME WARNING AGRICULTURAL SYSTEM FOR DISASTER PREDICTION . Malaysian Journal of Computing, 9(1), 1706–1721. https://doi.org/10.24191/mjoc.v9i1.24836