Citation:

Manoj Kumar, 2024. "AI For Climate Change: Predicting Environmental Impact and Developing Sustainable Solutions", ESP Journal of Engineering & Technology Advancements 4(3): 127-133.

Abstract:

Artificial Intelligence (AI) has now become a game-changing tool in the struggle with challenges related to climate change, offering very precise data-driven solutions and forecasts. The paper analyzes the use of AI models for predictions related to rising sea levels, changes in weather patterns, and ecosystem degradation. AI can analyze huge volumes of data and enable the creation of predictive power about a variety of future scenarios with precision for proactive mitigation and adaptation strategies. The studies investigates the optimization of renewable energy systems and wind power artificial intelligence through enhanced efficiency, reduced wastages, and increased grid stability. Apart from that, AI-powered technologies promote green living in agriculture with precise farming, minimizing the use of resources and enhancing the yields of crops. Similarly, AI helps in reducing emissions by route optimization in transport and generally improving the efficiency of vehicles. This paper demonstrates that AI integrated into various industrial areas can provide more sustainable and resilient systems to combat adverse climatic changes and further the interest of environmental stewardship.

References:

[1] Cowls, J., Tsamados, A., Taddeo, M. et al. The AI gambit: leveraging artificial intelligence to combat climate change—opportunities, challenges, and recommendations. AI & Soc 38, 283–307 (2023). doi:10.1007/s00146-021-01294-x

[2] Rohit Nishant, Mike Kennedy, Jacqueline Corbett, Artificial intelligence for sustainability: Challenges, opportunities, and a research agenda, International Journal of Information Management, Volume 53,2020,102104,ISSN 0268-4012,doi:10.1016/j.ijinfomgt.2020.102104.

[3] van Wynsberghe, A. Sustainable AI: AI for sustainability and the sustainability of AI. AI Ethics 1, 213–218 (2021). doi:10.1007/s43681-021-00043-6

[4] David Rolnick, Priya L. Donti, Lynn H. Kaack, Kelly Kochanski, Alexandre Lacoste, Kris Sankaran, Andrew Slavin Ross, Nikola Milojevic-Dupont, Natasha Jaques, Anna Waldman-Brown, Alexandra Sasha Luccioni, Tegan Maharaj, Evan D. Sherwin, S. Karthik Mukkavilli, Konrad P. Kording, Carla P. Gomes, Andrew Y. Ng, Demis Hassabis, John C. Platt, Felix Creutzig, Jennifer Chayes, and Yoshua Bengio. 2022. Tackling Climate Change with Machine Learning. ACM Comput. Surv. 55, 2, Article 42 (February 2023), 96 pages.doi:10.1145/3485128

[5] Ashkan Nabavi-Pelesaraei, Shahin Rafiee, Seyed Saeid Mohtasebi, Homa Hosseinzadeh-Bandbafha, Kwok-wing Chau,

[6] Integration of artificial intelligence methods and life cycle assessment to predict energy output and environmental impacts of paddy production, Science of The Total Environment, Volumes 631–632,2018,Pages 1279-1294,doi:10.1016/j.scitotenv.2018.03.088.

[7] Yogesh K. Dwivedi, Laurie Hughes, Arpan Kumar Kar, Abdullah M. Baabdullah, Purva Grover, Climate change and COP26: Are digital technologies and information management part of the problem or the solution? An editorial reflection and call to action ,International Journal of Information Management, Volume 63,2022,102456,doi:10.1016/j.ijinfomgt.2021.102456.

[8] Ali Kaab, Mohammad Sharifi, Hossein Mobli, Ashkan Nabavi-Pelesaraei, Kwok-wing Chau,Combined life cycle assessment and artificial intelligence for prediction of output energy and environmental impacts of sugarcane production,Science of The Total Environment,Volume 664,2019,Pages 1005-1019,doi:10.1016/j.scitotenv.2019.02.004.

[9] Abdul-Lateef Balogun, Danny Marks, Richa Sharma, Himanshu Shekhar, Chiden Balmes, Dikman Maheng, Adnan Arshad, Pourya Salehi,Assessing the Potentials of Digitalization as a Tool for Climate Change Adaptation and Sustainable Development in Urban Centres, Sustainable Cities and Society ,Volume 53,2020,101888,doi:10.1016/j.scs.2019.101888.

[10] Yigitcanlar, T.; Desouza, K.C.; Butler, L.; Roozkhosh, F. Contributions and Risks of Artificial Intelligence (AI) in Building Smarter Cities: Insights from a Systematic Review of the Literature. Energies 2020, 13, 1473. doi:10.3390/en13061473

[11] S. Y. Liu, Artificial Intelligence (AI) in Agriculture, in IT Professional, vol. 22, no. 3, pp. 14-15, 1 May-June 2020, doi: 10.1109/MITP.2020.2986121

[12] Nagarjuna Reddy Aturi, Navigating Legal and Regulatory Challenges for Global Non-Profit Ethical Leadership and Governance Leveraging Generative AI for Strategic Planning in Global Non-Profits, International Journal of Science and Research (IJSR), Volume 13 Issue 8, August 2024, pp. 1863-1867, https://www.ijsr.net/getabstract.php?paperid=SR240806112349. doi: 10.21275/SR240806112349

[13] Mohd Javaid, Abid Haleem, Ravi Pratap Singh, Rajiv Suman, Ernesto Santibañez Gonzalez,Understanding the adoption of Industry 4.0 technologies in improving environmental sustainability,Sustainable Operations and Computers,Volume 3,2022,Pages 203-217,doi:10.1016/j.susoc.2022.01.008.

[14] Yigitcanlar, T.; Cugurullo, F. The Sustainability of Artificial Intelligence: An Urbanistic Viewpoint from the Lens of Smart and Sustainable Cities. Sustainability 2020, 12, 8548. doi:10.3390/su12208548

[15] Surajit Bag, Jan Ham Christiaan Pretorius, Shivam Gupta, Yogesh K. Dwivedi,Role of institutional pressures and resources in the adoption of big data analytics powered artificial intelligence, sustainable manufacturing practices and circular economy capabilities, Technological Forecasting and Social Change, Volume 163,2021,120420,doi:10.1016/j.techfore.2020.120420.

Keywords:

AI For Climate Change: Predicting Environmental Impact and Developing Sustainable Solutions