IIARD International Institute of Academic Research and Development

International Journal of Engineering and Modern Technology (IJEMT )

E-ISSN 2504-8848
P-ISSN 2695-2149
VOL. 10 NO. 11 2024
DOI: 10.56201/ijemt.v10.no11.2024.pg19.22

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Advancing Renewable Natural Resources Mnagement Through Computer-Based Technologies: A Comprehensive Review

Mansur M.A., Usman, H. & & Abdulrahman, A.

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Abstract

Forests, water, soil, biodiversity, and other renewable natural resources (RNR) are all crucial for preserving ecological balance and guaranteeing the sustainability of human lifestyles. But issues like deforestation, soil erosion, biodiversity loss, and water scarcity all of which are made worse by climate change call for creative solutions. Resource management has seen a revolution because to computer-based technologies including Geographic Information Systems (GIS), Remote Sensing (RS), Artificial Intelligence (AI), the Internet of Things (IoT), and Decision Support Systems (DSS). The uses, advantages, difficulties, and possibilities of various technologies in RNR management are systematically reviewed in this paper. The review demonstrates how these technologies may facilitate data analysis, monitoring, and decision-making for sustainable resource use by examining peer-reviewed research. The results highlight how crucial it is to include contemporary techniques into resource management while removing obstacles to their uptake.

keywords:

Renewable; Natural Resources; Computer-based; Technologies and GIS

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References:

Adeyemi, T., Bello, S., & Usman, H. (2021). GIS-based assessment of land use changes in Nigeria.
Journal of Environmental Studies, 15(3), 101-118.
Food and Agriculture Organization (FAO). (2022). The State of the World’s Forests 2022.
Retrieved from [http://www.fao.org](http://www.fao.org).
IPCC.
(2022).
Climate
Change
and
Land.
Retrieved
from
[https://www.ipcc.ch](https://www.ipcc.ch).
Mensah, P., & Agyeman, K. (2021). IoT applications in renewable resource monitoring.
Sustainability Journal, 7(2), 45-62.
Pham, T., & Hoang, L. (2021). Hydrological modeling in the Mekong River Basin. Journal of
Water Resource Management, 18(2), 134-152.



Rahman, M., Singh, A., & Sharma, R. (2022). Applications of RS and GIS in forest management.
Environmental Monitoring Journal, 10(3), 89-105.
Sharma, R., & Singh, A. (2021). AI applications in renewable resource conservation: A review.
Renewable Resource Journal, 8(1), 88-104.
UNEP. (2023). Technology for Sustainability: Applications in Natural Resource Management.
Retrieved from [https://www.unep.org](https://www.unep.org).
UNCCD. (2022). IoT technologies in sustainable water resource management. Environmental
Solutions Journal, 6(4), 55-70.
Zhang, X., Li, H., & Wang, J. (2020). Advancing IoT and AI in environmental monitoring.
Sustainability Science Journal, 5(4), 120-135.

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