Technology & Management Review

Peer Reviewed Article

Vol. 5 (2020)

Unveiling the Influence of Artificial Intelligence on Resource Management and Sustainable Development: A Comprehensive Investigation

Submitted
2024 July 24
Published
2020-03-13

Abstract

This in-depth study, titled "Revealing the Impact of Artificial Intelligence on Resource Management and Sustainable Development," delves into the potential of AI technologies to revolutionize resource utilization, improve efficiency, and foster sustainability. The study aims to explore the use of AI in different resource sectors, analyze the obstacles and advantages of integrating AI, and suggest strategic methods for successful implementation. By employing a methodology that relies on secondary data, this study combines existing research, case studies, and expert analyses to offer a comprehensive insight into the effects of AI on resource management. The major findings underscore the significant advantages of AI in streamlining processes, minimizing environmental footprints, and improving predictive capabilities. Nevertheless, certain obstacles need to be overcome, including issues related to data quality, ethical considerations, and the need for interdisciplinary collaboration. Policy implications involve solid data infrastructure, establishing ethical guidelines and regulatory frameworks, and promoting AI literacy and capacity-building initiatives. The study emphasizes the importance of a collective effort involving policymakers, industry leaders, researchers, and community members to fully utilize AI's potential in promoting sustainable development. It highlights the necessity for continuous commitment, innovation, and adaptability.

References

  1. Aliyari, H., Kholghi, M., Zahedi, S., Momeni, M. (2018). Providing Decision Support System in Groundwater Resources Management for the Purpose of Sustainable Development. Journal of Water Supply: Research and Technology – AQUA, 67(5), 423-437. https://doi.org/10.2166/aqua.2018.130
  2. Anumandla, S. K. R. (2018). AI-enabled Decision Support Systems and Reciprocal Symmetry: Empowering Managers for Better Business Outcomes. International Journal of Reciprocal Symmetry and Theoretical Physics, 5, 33-41. https://upright.pub/index.php/ijrstp/article/view/129
  3. Couto, C., Vicente, H., Machado, J., Abelha, A., Neves, J. (2012). Water Quality Modeling using Artificial Intelligence-based Tools. International Journal of Design & Nature and Ecodynamics, 7(3), 300-309. https://doi.org/10.2495/DNE-V7-N3-300-309
  4. Fu, T., Wang, C. (2018). A Hybrid Wind Speed Forecasting Method and Wind Energy Resource Analysis Based on a Swarm Intelligence Optimization Algorithm and an Artificial Intelligence Model. Sustainability, 10(11), 3913. https://doi.org/10.3390/su10113913
  5. Jovanovic, M., Dlacic, J., Okanovic, M. (2018). Digitalization and Society's Sustainable Development – Measures and Implications *1. Zbornik Radova Ekonomski Fakultet u Rijeka, 36(2), 905-928. https://doi.org/10.18045/zbefri.2018.2.905
  6. Khakurel, J., Penzenstadler, B., Porras, J., Knutas, A., Zhang, W. (2018). The Rise of Artificial Intelligence under the Lens of Sustainability. Technologies, 6(4), 100. https://doi.org/10.3390/technologies6040100
  7. Koehler, S., Dhameliya, N., Patel, B., & Anumandla, S. K. R. (2018). AI-Enhanced Cryptocurrency Trading Algorithm for Optimal Investment Strategies. Asian Accounting and Auditing Advancement, 9(1), 101–114. https://4ajournal.com/article/view/91
  8. Liang, X., Si, D., Xu, J. (2018). Quantitative Evaluation of the Sustainable Development Capacity of Hydropower in China Based on Information Entropy. Sustainability, 10(2), 529.n https://doi.org/10.3390/su10020529
  9. Mamedov, O., Tumanyan, Y., Ishchenko-Padukova, O., Movchan, I. (2018). Sustainable Economic Development and Post-economy of Artificial Intelligence. Entrepreneurship and Sustainability Issues, 6(2), 1028-1040. https://doi.org/10.9770/jesi.2018.6.2(37)
  10. Masciopinto, C., Vurro, M., Palmisano, V. N., Liso, I. S. (2017). A Suitable Tool for Sustainable Groundwater Management. Water Resources Management, 31(13), 4133-4147. https://doi.org/10.1007/s11269-017-1736-0
  11. Mohammed, M. A., Kothapalli, K. R. V., Mohammed, R., Pasam, P., Sachani, D. K., & Richardson, N. (2017). Machine Learning-Based Real-Time Fraud Detection in Financial Transactions. Asian Accounting and Auditing Advancement, 8(1), 67–76. https://4ajournal.com/article/view/93
  12. Mohammed, M. A., Mohammed, R., Pasam, P., Addimulam, S. (2018). Robot-Assisted Quality Control in the United States Rubber Industry: Challenges and Opportunities. ABC Journal of Advanced Research, 7(2), 151-162.
  13. Mohammed, R., Addimulam, S., Mohammed, M. A., Karanam, R. K., Maddula, S. S., Pasam, P., & Natakam, V. M. (2017a). Optimizing Web Performance: Front End Development Strategies for the Aviation Sector. International Journal of Reciprocal Symmetry and Theoretical Physics, 4, 38-45. https://upright.pub/index.php/ijrstp/article/view/142
  14. Mullangi, K. (2017). Enhancing Financial Performance through AI-driven Predictive Analytics and Reciprocal Symmetry. Asian Accounting and Auditing Advancement, 8(1), 57–66. https://4ajournal.com/article/view/89
  15. Mullangi, K., Anumandla, S. K. R., Maddula, S. S., Vennapusa, S. C. R., & Mohammed, M. A. (2018). Accelerated Testing Methods for Ensuring Secure and Efficient Payment Processing Systems. ABC Research Alert, 6(3), 202–213. https://doi.org/10.18034/ra.v6i3.662
  16. Mullangi, K., Maddula, S. S., Shajahan, M. A., & Sandu, A. K. (2018a). Artificial Intelligence, Reciprocal Symmetry, and Customer Relationship Management: A Paradigm Shift in Business. Asian Business Review, 8(3), 183–190. https://doi.org/10.18034/abr.v8i3.704
  17. Mullangi, K., Yarlagadda, V. K., Dhameliya, N., & Rodriguez, M. (2018). Integrating AI and Reciprocal Symmetry in Financial Management: A Pathway to Enhanced Decision-Making. International Journal of Reciprocal Symmetry and Theoretical Physics, 5, 42-52. https://upright.pub/index.php/ijrstp/article/view/134
  18. Nabavi-pelesaraei, A., Abdi, R., Rafiee, S., Shamshirband, S., Yousefinejad-ostadkelayeh, M. (2016). Resource Management in Cropping Systems using Artificial Intelligence Techniques: A Case Study of Orange Orchards in North of Iran. Stochastic Environmental Research and Risk Assessment, 30(1), 413-427. https://doi.org/10.1007/s00477-015-1152-z
  19. Nizamuddin, M., Natakam, V. M., Sachani, D. K., Vennapusa, S. C. R., Addimulam, S., & Mullangi, K. (2019). The Paradox of Retail Automation: How Self-Checkout Convenience Contrasts with Loyalty to Human Cashiers. Asian Journal of Humanity, Art and Literature, 6(2), 219-232. https://doi.org/10.18034/ajhal.v6i2.751
  20. Patel, B., Mullangi, K., Roberts, C., Dhameliya, N., & Maddula, S. S. (2019). Blockchain-Based Auditing Platform for Transparent Financial Transactions. Asian Accounting and Auditing Advancement, 10(1), 65–80. https://4ajournal.com/article/view/92
  21. Reddy, M. J., Kumar, D. N. (2009). Performance Evaluation of Elitist-mutated Multi-objective Particle Swarm Optimization for Integrated Water Resources Management. Journal of Hydroinformatics, 11(1), 79-88. https://doi.org/10.2166/hydro.2009.042
  22. Richardson, N., Pydipalli, R., Maddula, S. S., Anumandla, S. K. R., & Vamsi Krishna Yarlagadda. (2019). Role-Based Access Control in SAS Programming: Enhancing Security and Authorization. International Journal of Reciprocal Symmetry and Theoretical Physics, 6, 31-42. https://upright.pub/index.php/ijrstp/article/view/133
  23. Sachani, D. K. (2018). Technological Advancements in Retail Kiosks: Enhancing Operational Efficiency and Consumer Engagement. American Journal of Trade and Policy, 5(3), 161–168. https://doi.org/10.18034/ajtp.v5i3.714
  24. Sachani, D. K., & Vennapusa, S. C. R. (2017). Destination Marketing Strategies: Promoting Southeast Asia as a Premier Tourism Hub. ABC Journal of Advanced Research, 6(2), 127-138. https://doi.org/10.18034/abcjar.v6i2.746
  25. Shajahan, M. A., Richardson, N., Dhameliya, N., Patel, B., Anumandla, S. K. R., & Yarlagadda, V. K. (2019). AUTOSAR Classic vs. AUTOSAR Adaptive: A Comparative Analysis in Stack Development. Engineering International, 7(2), 161–178. https://doi.org/10.18034/ei.v7i2.711
  26. Vennapusa, S. C. R., Fadziso, T., Sachani, D. K., Yarlagadda, V. K., & Anumandla, S. K. R. (2018). Cryptocurrency-Based Loyalty Programs for Enhanced Customer Engagement. Technology & Management Review, 3, 46-62. https://upright.pub/index.php/tmr/article/view/137
  27. Wang, Q., Li, P., Sun, Q. (2013). The Sustainable Island Development Evaluation Model and Its Application Based on the Nonstructural Decision Fuzzy Set. Abstract and Applied Analysis, 2013. https://doi.org/10.1155/2013/631717
  28. Yarlagadda, V. K., & Pydipalli, R. (2018). Secure Programming with SAS: Mitigating Risks and Protecting Data Integrity. Engineering International, 6(2), 211–222. https://doi.org/10.18034/ei.v6i2.709
  29. Yarlagadda, V. K., Maddula, S. S., Sachani, D. K., Mullangi, K., Anumandla, S. K. R., & Patel, B. (2020). Unlocking Business Insights with XBRL: Leveraging Digital Tools for Financial Transparency and Efficiency. Asian Accounting and Auditing Advancement, 11(1), 101–116. https://4ajournal.com/article/view/94
  30. Ying, D., Patel, B., & Dhameliya, N. (2017). Managing Digital Transformation: The Role of Artificial Intelligence and Reciprocal Symmetry in Business. ABC Research Alert, 5(3), 67–77. https://doi.org/10.18034/ra.v5i3.659
  31. Zaini, N., Malek, M. A., Yusoff, M., Mardi, N. H., Norhisham, S. (2018). Daily River Flow Forecasting with Hybrid Support Vector Machine – Particle Swarm Optimization. IOP Conference Series. Earth and Environmental Science, 140(1). https://doi.org/10.1088/1755-1315/140/1/012035

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