[
Adebiyi-Abiola, B.., Assefa, S., Sheikh, K., García, J. M. (2019). Cleaning up plastic pollution in Africa. Science 365 (6459), 1249–1251. doi: 10.1126/science.aax3539
]Search in Google Scholar
[
Ahmad, T., Zhang, D., Huang, C., Zhang, H., Dai, N., Song, Y., & Chen, H. (2021). Artificial Intelligence in sustainable energy industry: Status quo, challenges and opportunities. Journal of Cleaner Production. https://www.sciencedirect.com/science/article/pii/S0959652621000548
]Search in Google Scholar
[
Akter, S., Wamba, S. F., Mariani, M., & Hani, U. (2021). How to Build an AI Climate-Driven Service Analytics Capability for Innovation and Performance in Industrial Markets? Industrial Marketing Management, 97, 258–273.
]Search in Google Scholar
[
Ameer, S. & Alkhafaji, M., & Jaffer, Z., Al-Farouni, M. (2024). Empowering Farmers with IoT, UAVs, and Deep Learning in Smart Agriculture. E3S Web of Conferences. 491. 10.1051/e3sconf/202449104007.
]Search in Google Scholar
[
Ang, T.Z., Salem, M., Kamarol, M., Das, H., Puia, A., Natarajan, P. (2022). A comprehensive study of renewable energy sources: Classifications, challenges and suggestions. Energy Strategy Reviews. 43. 100939. 10.1016/j.esr.2022.100939.
]Search in Google Scholar
[
Arrieta, B., Alejandro, N.-R., Del Ser, J., Bennetot, A., Tabik, S., Barbado, A., Garcia, S., Gil-Lopez, S., Molina, D., Benjamins, R., Chatila, R., & Herrera, F. (2020). Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI. Information Fusion, 58, 82–115.
]Search in Google Scholar
[
Bracarense, N., Bawack, R.E., Fosso Wamba, S., Carillo, K.D.A. (2022). Artificial Intelligence and Sustainability: A Bibliometric Analysis and Future Research Directions. Pacific Asia Journal of the Association for Information Systems: Vol. 14: Iss. 2, Article 9. DOI: 10.17705/1pais.14209
]Search in Google Scholar
[
Chaterji, S., DeLay, N.D., Evans, J.V., Mosier, N., Engel, B.A., Buckmaster, D.R., & Chandra, R. (2020). Artificial Intelligence for Digital Agriculture at Scale: Techniques, Policies, and Challenges. ArXiv, abs/2001.09786.
]Search in Google Scholar
[
Chen, P.; Gao, J.; Ji, Z.; Liang, H.; Peng, Y. (2022) Do Artificial Intelligence Applications Affect Carbon Emission Performance?—Evidence from Panel Data Analysis of Chinese Cities. Energies, 15, 5730. https://doi.org/10.3390/en15155730
]Search in Google Scholar
[
Chen, L., Chen, Z., Zhang, Y. et al (2023). Artificial intelligence-based solutions for climate change: a review. Environ Chem Lett 21, 2525–2557 (2023). https://doi.org/10.1007/s10311-023-01617-y
]Search in Google Scholar
[
Davis, B., (2021). AI and the energy transition.Technology, Petroleum Review.
]Search in Google Scholar
[
Das, U.K., Tey, K.S.,Seyedmahmoudian, M., Mekhilef, S., Idris, M.Y.I., Van Deventer, W.H.B., Stojcevski, A. (2018). "Forecasting of photovoltaic power generation and model optimization: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 912-928.
]Search in Google Scholar
[
Dewitte, S., Cornelis, J.P., Müller, R., Munteanu, A. (2021). Artificial Intelligence Revolutionises Weather Forecast, Climate Monitoring and Decadal Prediction. Remote Sens. 2021, 13, 3209. https://doi.org/10.3390/rs13163209
]Search in Google Scholar
[
Dhamija, P., Bag, S. (2020). Role of artificial intelligence in operations environment: a review and bibliometric analysis. The TQM Journal. ahead-of-print. 10.1108/TQM-10-2019-0243.
]Search in Google Scholar
[
Dubois, G., Sovacool, B., Aall, C., Nilsson, M., Barbier, C. (2019) A. Herrmann, et al., It starts at home? Climate policies targeting household consumption and behavioral decisions are key to low-carbon futures. Energy Research & Social Science, 52 (2019), pp. 144-158, 10.1016/j.erss.2019.02.001
]Search in Google Scholar
[
Ghaleb, H.; Alhajlah, H.H.; Bin Abdullah, A.A.; Kassem, M.A.; Al-Sharafi, M.A., (2022). A Scientometric Analysis and Systematic Literature Review for Construction Project Complexity. Buildings, 12, 482. https://doi.org/10.3390/buildings12040482
]Search in Google Scholar
[
Gaffin, S.R., Rosenzweig, C., Kong, A.Y. (2012) Adapting to climate change through urban green infrastructure, Nature Climate Change, 2 (10) (2012), p. 704, 10.1038/nclimate1685
]Search in Google Scholar
[
Guo Q, Ren M, Wu S, Sun Y, Wang J, Wang Q, Ma Y, Song X and Chen Y (2022) Applications of artificial intelligence in the field of air pollution: A bibliometric analysis. Front. Public Health 10:933665. doi: 10.3389/fpubh.2022.933665
]Search in Google Scholar
[
Huntingford, C., Jeffers, E. S., Bonsall, M. B., Christensen, H. M., Lees, T., Yang, H., (2019). Machine learning and artificial intelligence to aid climate change research and preparedness. Environmental Research Letters, vol. 14, no. 12, IOP. doi:10.1088/1748-9326/ab4e55.
]Search in Google Scholar
[
Issa, H., Jabbouri, R., & Palmer, M. (2022). An artificial intelligence (AI)-readiness and adoption framework for AgriTech firms. Technological Forecasting and Social Change, 182, 121874.2.
]Search in Google Scholar
[
Jain, H., Dhupper, R., Shrivastava, A. et al. (2023). AI-enabled strategies for climate change adaptation: protecting communities, infrastructure, and businesses from the impacts of climate change. Comput.Urban Sci. 3, 25 (2023). https://doi.org/10.1007/s43762-023-00100-2
]Search in Google Scholar
[
Jrad, M. (2023). A Role of Artificial Intelligence in the Context of Economy: Bibliometric Analysis and Systematic Literature Review. International Journal of Membrane Science and Technology. 10. 1563-1586. 10.15379/ijmst.v10i3.1756.
]Search in Google Scholar
[
Kamyab, H., Khademi, T., Chelliapan, S., Saberi Kamarposhti, M., Rezania, M., Yusuf, M., Farajnezhad, M., Abbas M., Hun Jeon, B., Ahn, Y.(2023). The latest innovative avenues for the utilization of artificial Intelligence and big data analytics in water resource management. Results in Engineering.
]Search in Google Scholar
[
Kaplan, A., Haenlein, M. (2019). Rulers of the world, unite! The challenges and opportunities of artificial intelligence. Business Horizons. 63. 10.1016/j.bushor.2019.09.003.
]Search in Google Scholar
[
Karanth S, Benefo EO, Patra D, Pradhan AK (2022) Importance of artificial intelligence in evaluating climate change and food safety risk. J Agric Food Res. https://doi.org/10.1016/j.jafr.2022.100485
]Search in Google Scholar
[
Kouhizadeh, M.; Sarkis, J. (2018). Blockchain Practices, Potentials, and Perspectives in Greening Supply Chains. Sustainability 2018, 10, 3652. https://doi.org/10.3390/su10103652
]Search in Google Scholar
[
Kumar, P., Singh. A., Rajput, V & Yadav, A., Kumar, P., Singh, A.K., Minkina, T. (2022). Role of artificial intelligence, sensor technology, big data in agriculture: next-generation farming. 10.1016/B978-0-323-89778-5.00035-0.
]Search in Google Scholar
[
Feng, Y., Wang, X., Du, W., Wu, H., Wang, J., (2019) Effects of environmental regulation and FDI on urban innovation in China: A spatial Durbin econometric analysis, Journal of Cleaner Production. Retrieved from: https://www.sciencedirect.com/science/article/pii/S0959652619321468
]Search in Google Scholar
[
Filho, W., Wall, T., Mucova, S., Nagy, G., Balogun, A.l., Luetz, J., Ng, A., Kovaleva, M., Azam, F.M., Alves, F., Guevara, Z., Matandirotya, N., Skouloudis, A., Tzachor, A., Malakar, K., Gandhi, O. (2022). Deploying artificial intelligence for climate change adaptation. Technological Forecasting and Social Change. 180. 121662. 10.1016/j.techfore.2022.121662.
]Search in Google Scholar
[
Lakatos, E.S., Yong, G., Szilagyi, A., Clinci, D.S., Georgescu, L., Iticescu, C., Cioca, L.-I. (2021), Conceptualizing Core Aspects on Circular Economy in Cities. Sustainability, 13, 7549. Retrieved from: https://doi.org/10.3390/su13147549
]Search in Google Scholar
[
Lyu, W., Liu, J., (2021). Artificial Intelligence and emerging digital technologies in the energy sector. Applied Energy, Volume 303, https://doi.org/10.1016/j.apenergy.2021.117615.
]Search in Google Scholar
[
McCarthy, J., Minsky, M.L., Rochester, N. and Shannon, C.E. (2006). A proposal for the dartmouth summer research project on artificial intelligence, august 31, 1955. AI magazine, 27(4), pp.12-12
]Search in Google Scholar
[
Mehmood, M.U., Chun, D., Zeeshan, Han, H., Jeon, G., & Chen, K. (2019). A review of the applications of artificial intelligence and big data to buildings for energy-efficiency and a comfortable indoor living environment. Energy and Buildings.
]Search in Google Scholar
[
Nishant, R., Kennedy, M,, Corbett, J. (2020). Artificial intelligence for sustainability: Challenges, opportunities, and a research agenda. International Journal of Information Management, Elsevier, vol. 53(C).
]Search in Google Scholar
[
Nost, E., Colven, E. (2022). Earth for AI: A Political Ecology of Data-Driven Climate Initiatives. Geoforum. 130. 23-34. 10.1016/j.geoforum.2022.01.016.
]Search in Google Scholar
[
Redhu, N., Thakur, Z., Yashveer, S., Mor, P. (2022). Artificial intelligence: a way forward for agricultural sciences. 10.1016/B978-0-323-89778-5.00007-6.
]Search in Google Scholar
[
Ristea, A.L., Popescu, C., Ioan-Franc, V., Belostecinic G., (2017), Scientometria și Evaluarea Rezultatelor Cercetării Ştiinţifice Economice. Journal „ECONOMICA” nr.4 (102) 2017, Retrieved from: https://irek.ase.md/xmlui/bitstream/handle/123456789/432/Ristea-AL_Popescu-C_Ioan-Franc-V_Belostecinic-G_Economica%20nr_4%20decembrie%202017.pdf?sequence=1&isAllowed=y
]Search in Google Scholar
[
Shaikh, T. A., Rasool, T., Lone, F. R., (2022). Towards leveraging the role of machine learning and artificial intelligence in precision agriculture and smart farming. Comput. Electron. Agric. 198, C (Jul 2022). https://doi.org/10.1016/j.compag.2022.107119
]Search in Google Scholar
[
Shrestha, A., Mahmood, A., (2019). Review of Deep Learning Algorithms and Architectures. IEEE Access. PP. 1-1. 10.1109/ACCESS.2019.2912200.
]Search in Google Scholar
[
Stecuła, K., Wolniak, R., Grebski, W.W., (2023). AI-Driven Urban Energy Solutions—From Individuals to Society: A Review. Energies.; 16(24):7988. https://doi.org/10.3390/en16247988
]Search in Google Scholar
[
Serban, A.C., Lytras, M. (2020). Artificial Intelligence for Smart Renewable Energy Sector in Europe—Smart Energy Infrastructures for Next Generation Smart Cities. IEEE Access. PP. 1-1. 10.1109/ACCESS.2020.2990123.
]Search in Google Scholar
[
Suman, A., (2021) Role of renewable energy technologies in climate change adaptation and mitigation: A brief review from Nepal, Renewable and Sustainable Energy Reviews. Retrieved from: https://www.sciencedirect.com/science/article/pii/S1364032121008029
]Search in Google Scholar
[
Torky, M., Gad, I., Darwish, A., Hassanien, A.E. (2023). Artificial Intelligence for Predicting Floods: A Climatic Change Phenomenon. In: Hassanien, A.E., Darwish, A. (eds) The Power of Data: Driving Climate Change with Data Science and Artificial Intelligence Innovations. Studies in Big Data, vol 118. Springer, Cham. https://doi.org/10.1007/978-3-031-22456-0_1
]Search in Google Scholar
[
Vinuesa, R., Azizpour, H., Leite, I. et al. (2020). The role of artificial intelligence in achieving the Sustainable Development Goals. Nat Commun 11, 233 (2020). https://doi.org/10.1038/s41467-019-14108-y
]Search in Google Scholar
[
Yang, T., Asanjan, A. A.,Welles, E., Gao, X., Sorooshian, S. and Liu X. (2017). Developing reservoir monthly inflow forecasts using artificial intelligence and climate phenomenon information. Water Resour. Res., 53, 2786–2812, doi:10.1002/2017WR020482.
]Search in Google Scholar