Abstract
The utilization of renewable energy is becoming increasingly important in today's engineering development to address environmental challenges and energy sustainability. However, the full potential of renewable energy sources has yet to be fully explored. This study aims to explore the potential of renewable energy in the context of contemporary engineering development with a focus on identifying renewable energy sources that can be optimized and integrated in engineering infrastructure. The research methods used include literature survey, data analysis, and modeling to evaluate various renewable energy sources that can be applied in engineering development. An interdisciplinary approach was used to gain a holistic understanding of the potential and limitations of each energy source. The study identified that renewable energy, such as solar, wind, hydro, and biomass, has great potential in providing clean and sustainable energy sources for today's engineering development. In-depth analysis also shows that the integration of renewable energy systems can reduce dependence on fossil fuels and reduce greenhouse gas emissions. By tapping into the potential of renewable energy, today's engineering developments can become more sustainable and environmentally friendly. The integration of renewable energy in engineering infrastructure not only reduces negative environmental impacts but also creates new opportunities for innovation and sustainable economic growth.
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References
Akhter, R., & Sofi, S. A. (2022). Precision agriculture using IoT data analytics and machine learning. Journal of King Saud University - Computer and Information Sciences, 34(8), 5602–5618. https://doi.org/10.1016/j.jksuci.2021.05.013
Ali, H., Khan, E., & Ilahi, I. (2019). Environmental Chemistry and Ecotoxicology of Hazardous Heavy Metals: Environmental Persistence, Toxicity, and Bioaccumulation. Journal of Chemistry, 2019, 1–14. https://doi.org/10.1155/2019/6730305
Alkorta, I., Elguero, J., & Frontera, A. (2020). Not Only Hydrogen Bonds: Other Noncovalent Interactions. Crystals, 10(3), 180. https://doi.org/10.3390/cryst10030180
Ayd?n, Ö., & Karaarslan, E. (2022). OpenAI ChatGPT Generated Literature Review: Digital Twin in Healthcare. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4308687
Baji?, I. V., Saeedi-Baji?, T., & Saeedi-Baji?, K. (2023). Metaverse: A Young Gamer’s Perspective. 2023 IEEE 25th International Workshop on Multimedia Signal Processing (MMSP), 1–6. https://doi.org/10.1109/MMSP59012.2023.10337702
Cao, W., Fang, Z., Hou, G., Han, M., Xu, X., Dong, J., & Zheng, J. (2020). The psychological impact of the COVID-19 epidemic on college students in China. Psychiatry Research, 287, 112934. https://doi.org/10.1016/j.psychres.2020.112934
Caselli, D., & Aricò, M. (2020). 2019-nCoV: Polite with Children! Pediatric Reports, 12(1), 8495. https://doi.org/10.4081/pr.2020.8495
Chung, Y.-A., Zhang, Y., Han, W., Chiu, C.-C., Qin, J., Pang, R., & Wu, Y. (2021). w2v-BERT: Combining Contrastive Learning and Masked Language Modeling for Self-Supervised Speech Pre-Training. 2021 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), 244–250. https://doi.org/10.1109/ASRU51503.2021.9688253
D’Ancona, C., Haylen, B., Oelke, M., Abranches?Monteiro, L., Arnold, E., Goldman, H., Hamid, R., Homma, Y., Marcelissen, T., Rademakers, K., Schizas, A., Singla, A., Soto, I., Tse, V., De Wachter, S., Herschorn, S., & On behalf of the Standardisation Steering Committee ICS and the ICS Working Group on Terminology for Male Lower Urinary Tract & Pelvic Floor Symptoms and Dysfunction. (2019). The International Continence Society (ICS) report on the terminology for adult male lower urinary tract and pelvic floor symptoms and dysfunction. Neurourology and Urodynamics, 38(2), 433–477. https://doi.org/10.1002/nau.23897
Dong, H., & Liu, Y. (2023). Metaverse Meets Consumer Electronics. IEEE Consumer Electronics Magazine, 12(3), 17–19. https://doi.org/10.1109/MCE.2022.3229180
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., Albanna, H., Albashrawi, M. A., Al-Busaidi, A. S., Balakrishnan, J., Barlette, Y., Basu, S., Bose, I., Brooks, L., Buhalis, D., … Wright, R. (2023). Opinion Paper: “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642
Eckhardt, G. M., Houston, M. B., Jiang, B., Lamberton, C., Rindfleisch, A., & Zervas, G. (2019). Marketing in the Sharing Economy. Journal of Marketing, 83(5), 5–27. https://doi.org/10.1177/0022242919861929
Farrokhnia, M., Banihashem, S. K., Noroozi, O., & Wals, A. (2023). A SWOT analysis of ChatGPT: Implications for educational practice and research. Innovations in Education and Teaching International, 1–15. https://doi.org/10.1080/14703297.2023.2195846
Ferri, F., Grifoni, P., & Guzzo, T. (2020). Online Learning and Emergency Remote Teaching: Opportunities and Challenges in Emergency Situations. Societies, 10(4), 86. https://doi.org/10.3390/soc10040086
Groeninck, M. (2021). Islamic religious education at the heart of the secular problem-space in Belgium. Social Compass, 68(1), 25–41. https://doi.org/10.1177/0037768620974270
Gupta, R., Tanwar, S., Tyagi, S., & Kumar, N. (2020). Machine Learning Models for Secure Data Analytics: A taxonomy and threat model. Computer Communications, 153, 406–440. https://doi.org/10.1016/j.comcom.2020.02.008
Hao, J., & Ho, T. K. (2019). Machine Learning Made Easy: A Review of Scikit-learn Package in Python Programming Language. Journal of Educational and Behavioral Statistics, 44(3), 348–361. https://doi.org/10.3102/1076998619832248
Harris, C. R., Millman, K. J., Van Der Walt, S. J., Gommers, R., Virtanen, P., Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N. J., Kern, R., Picus, M., Hoyer, S., Van Kerkwijk, M. H., Brett, M., Haldane, A., Del Río, J. F., Wiebe, M., Peterson, P., … Oliphant, T. E. (2020). Array programming with NumPy. Nature, 585(7825), 357–362. https://doi.org/10.1038/s41586-020-2649-2
Jia, L., Du, Y., Chu, L., Zhang, Z., Li, F., Lyu, D., Li, Y., Li, Y., Zhu, M., Jiao, H., Song, Y., Shi, Y., Zhang, H., Gong, M., Wei, C., Tang, Y., Fang, B., Guo, D., Wang, F., … Qiu, Q. (2020). Prevalence, risk factors, and management of dementia and mild cognitive impairment in adults aged 60 years or older in China: A cross-sectional study. The Lancet Public Health, 5(12), e661–e671. https://doi.org/10.1016/S2468-2667(20)30185-7
Kim, J., & Bae, J. (2023). Influences of persona self on luxury brand attachment in the Metaverse context. Asia Pacific Journal of Marketing and Logistics. https://doi.org/10.1108/APJML-05-2022-0390
King, J., Fitton, D., & Cassidy, B. (2023). Investigating Players’ Perceptions of Deceptive Design Practices within a 3D Gameplay Context. Proceedings of the ACM on Human-Computer Interaction, 7(CHI PLAY), 876–892. https://doi.org/10.1145/3611053
Lipson, S. K., Lattie, E. G., & Eisenberg, D. (2019). Increased Rates of Mental Health Service Utilization by U.S. College Students: 10-Year Population-Level Trends (2007–2017). Psychiatric Services, 70(1), 60–63. https://doi.org/10.1176/appi.ps.201800332
Maican, M.-A., & Cocorad?, E. (2021). Online Foreign Language Learning in Higher Education and Its Correlates during the COVID-19 Pandemic. Sustainability, 13(2), 781. https://doi.org/10.3390/su13020781
Mancuso, I., Petruzzelli, A. M., Panniello, U., & Nespoli, C. (2024). A Microfoundation Perspective on Business Model Innovation: The Cases of Roblox and Meta in Metaverse. IEEE Transactions on Engineering Management, 1–14. https://doi.org/10.1109/TEM.2023.3275198
Mosco, V. (2023). Into the Metaverse: Technical Challenges, Social Problems, Utopian Visions, and Policy Principles. Javnost - The Public, 30(2), 161–173. https://doi.org/10.1080/13183222.2023.2200688
Njoku, J. N., Eneh, A. U., Nwakanma, C. I., Lee, J.-M., & Kim, D.-S. (2023). MetaHate: Text-based Hate Speech Detection for Metaverse Applications using Deep Learning. 2023 14th International Conference on Information and Communication Technology Convergence (ICTC), 979–984. https://doi.org/10.1109/ICTC58733.2023.10392437
Pal, D., & Vanijja, V. (2020). Perceived usability evaluation of Microsoft Teams as an online learning platform during COVID-19 using system usability scale and technology acceptance model in India. Children and Youth Services Review, 119, 105535. https://doi.org/10.1016/j.childyouth.2020.105535
Park, S.-M., & Kim, Y.-G. (2022). A Metaverse: Taxonomy, Components, Applications, and Open Challenges. IEEE Access, 10, 4209–4251. https://doi.org/10.1109/ACCESS.2021.3140175
Payal, R., Sharma, N., & Dwivedi, Y. K. (2024). Unlocking the impact of brand engagement in the metaverse on Real-World purchase intentions: Analyzing Pre-Adoption behavior in a futuristic technology platform. Electronic Commerce Research and Applications, 65, 101381. https://doi.org/10.1016/j.elerap.2024.101381
Putawa, R. A., Wardana, A. N. I., & Tenggara, A. P. (2023). Metaverse-based Water Level Simulator for the Festo MPS PA Workstation. Journal of Physics: Conference Series, 2673(1), 012008. https://doi.org/10.1088/1742-6596/2673/1/012008
Qiu, X., Liu, L., Chen, W., Hong, Z., & Zheng, Z. (2019). Online Deep Reinforcement Learning for Computation Offloading in Blockchain-Empowered Mobile Edge Computing. IEEE Transactions on Vehicular Technology, 68(8), 8050–8062. https://doi.org/10.1109/TVT.2019.2924015
Rahwan, I., Cebrian, M., Obradovich, N., Bongard, J., Bonnefon, J.-F., Breazeal, C., Crandall, J. W., Christakis, N. A., Couzin, I. D., Jackson, M. O., Jennings, N. R., Kamar, E., Kloumann, I. M., Larochelle, H., Lazer, D., McElreath, R., Mislove, A., Parkes, D. C., Pentland, A. ‘Sandy,’ … Wellman, M. (2019). Machine behaviour. Nature, 568(7753), 477–486. https://doi.org/10.1038/s41586-019-1138-y
Robinson, J., Barker, D. J., Georgiou, X., Cooper, M. A., Flicek, P., & Marsh, S. G. E. (2019). IPD-IMGT/HLA Database. Nucleic Acids Research, gkz950. https://doi.org/10.1093/nar/gkz950
Rodin, R., & Huda, M. (2021). Pemikiran Pendidikan Ki Hajar Dewantara dan Relevansinya Dengan Pendidikan Agama Islam Multikultural. Jurnal Al-Qiyam, 2(1), 110–119. https://doi.org/10.33648/alqiyam.v2i1.136
Rosa, J. (2019). Looking like a Language, Sounding like a Race: Raciolinguistic Ideologies and the Learning of Latinidad (1st ed.). Oxford University Press. https://doi.org/10.1093/oso/9780190634728.001.0001
Rospigliosi, P. ‘Asher.’ (2022). Metaverse or Simulacra? Roblox, Minecraft, Meta and the turn to virtual reality for education, socialisation and work. Interactive Learning Environments, 30(1), 1–3. https://doi.org/10.1080/10494820.2022.2022899
Ryan, R. M., & Deci, E. L. (2020). Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions. Contemporary Educational Psychology, 61, 101860. https://doi.org/10.1016/j.cedpsych.2020.101860
Shen, S., Sadoughi, M., Chen, X., Hong, M., & Hu, C. (2019). A deep learning method for online capacity estimation of lithium-ion batteries. Journal of Energy Storage, 25, 100817. https://doi.org/10.1016/j.est.2019.100817
Sholihah, D. A. (2021). Pendidikan Merdeka dalam Perspektif Ki Hadjar Dewantara dan Relevansinya Terhadap Merdeka Belajar di Indonesia. LITERASI (Jurnal Ilmu Pendidikan), 12(2), 115. https://doi.org/10.21927/literasi.2021.12(2).115-122
Stiker, H.-J. (2019). A History of Disability. University of Michigan Press. https://doi.org/10.3998/mpub.11575987
Zhang, Y., & Hu, W. (2023). In the Future Metaverse, What Kind of UGC do Users Need? 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), 901–902. https://doi.org/10.1109/VRW58643.2023.00293
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