Academic literature on the topic 'Green Artificial Intelligence'

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Journal articles on the topic "Green Artificial Intelligence"

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Debrah, Caleb, Albert P. C. Chan, and Amos Darko. "Artificial intelligence in green building." Automation in Construction 137 (May 2022): 104192. http://dx.doi.org/10.1016/j.autcon.2022.104192.

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Bhatnagar, Apoorva, and Megha Sharma. "Artificial Intelligence and Consumer’s Perception: A Research on Environmentally Conscious Consumer." Journal of Metaverse 4, no. 2 (2024): 105–15. http://dx.doi.org/10.57019/jmv.1488022.

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The purpose of this study is to explore the limited exploration of the simultaneous influence of beneficial artificial intelligence, destructive artificial intelligence, and risky artificial intelligence on green purchase intention and green purchase behaviour using the Technology Acceptance Model (TAM) and Innovation Resistance Theory (IRT). Further, it also checks the impact of green purchase intention on green purchase behaviour. Data was collected using a well-structured questionnaire from 124 consumers through online mode and analyzed using Confirmatory Factor Analysis (CFA) for reliabili
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ABD EL- MAKSOUD, NESMA, and Eman Ahmed. "Artificial Intelligence Applications in Green Architecture." Fayoum University Journal of Engineering 7, no. 2 (2024): 317–37. http://dx.doi.org/10.21608/fuje.2024.345049.

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Alzoubi, Yehia Ibrahim, and Alok Mishra. "Green artificial intelligence initiatives: Potentials and challenges." Journal of Cleaner Production 468 (August 2024): 143090. http://dx.doi.org/10.1016/j.jclepro.2024.143090.

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Swaminathan, Ramanathan. "The Emergent Artificial Intelligence of Green Spaces." Asiascape: Digital Asia 2, no. 3 (2015): 238–78. http://dx.doi.org/10.1163/22142312-12340032.

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The paper focuses on the digital logic that informs debates on urban ecology and green spaces in Asia. First, the paper builds a case regarding how pervasive digitalization is embedding everyday activities with artificial intelligence. This process, the paper argues, reconfigures existing social relationships of power and creates new modes of articulation, engagement, contestation, and negotiation. Second, the paper specifically looks at how this process informs material productions of space, spatiality, and territoriality of urban ecology. As case studies, the paper maps the narratives and di
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Dr., Anil Kumar Pandey. "DEVELOPMENT AND DEPLOYMENT OF GREEN ARTIFICIAL INTELLIGENCE." INTERNATIONAL JOURNAL OF MATHEMATICS AND COMPUTER RESEARCH 11, no. 04 (2023): 3328–32. https://doi.org/10.5281/zenodo.7836589.

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Green AI is an emerging field that aims to develop and deploy environmentally friendly and sustainable artificial intelligence (AI) systems. The potential benefits of Green AI to society are numerous, as it can help reduce the environmental impact of various sectors while improving their efficiency and effectiveness. This includes optimizing the operation of smart grids, reducing energy consumption in buildings, improving crop yields in agriculture, optimizing public transportation, monitoring and analyzing environmental data, managing waste, optimizing manufacturing processes, and modeling th
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Artha, Bhenu, Utami Tunjung Sari, Bahri Bahri, et al. "Artificial Intelligence and Sustainable Innovation: A Theoretical Review." Journal of Sustainable Innovation Engineering 1, no. 2 (2025): 39–43. https://doi.org/10.69693/sustainable.v1i2.12.

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Artificial intelligence (AI) has become universal across various sectors, permeating every aspect of our lives regardless of age or profession. In this era of AI, it's necessary to prioritize sustainable development and innovation in its application, while AI enables rapid completion of tasks alike human efficiency, it also raises concerns about increasing unemployment rates. A theoretical literature review is conducted in order to achieve the research's goals and objectives, and a conceptual framework for future study is offered. Authors conclude that artificial intelligence affects green pro
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Abbasova Sakina, Murtazalieva Zumrud, Abbasova Sakina, Murtazalieva Zumrud, and Medzhidova Sevinj, Leonyuk Irina Medzhidova Sevinj, Leonyuk Irina. "USING ARTIFICIAL INTELLIGENCE FOR A SUSTAINABLE GREEN FUTURE." PAHTEI-Procedings of Azerbaijan High Technical Educational Institutions 52, no. 04-02 (2025): 56–61. https://doi.org/10.36962/pahtei5204-022025-56.

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The article is devoted to the problems of using artificial intelligence in projects of a sustainable green future. First, the main goals (standards) of the development area of a sustainable green future approved by the UN General Assembly are explained. These standards also serve as a mechanism for implementing the main goals of "green" design and regulators for the creation of environmentally friendly objects. Then, a number of aspects of using artificial intelligence in green technologies, as well as in the creation of "smart" objects, are considered Keywords: Sustainable future, green techn
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Lu, Guanyan, and Bingxiang Li. "Artificial Intelligence and Green Collaborative Innovation: An Empirical Investigation Based on a High-Dimensional Fixed Effects Model." Sustainability 17, no. 9 (2025): 4141. https://doi.org/10.3390/su17094141.

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This study focuses on the intrinsic mechanisms and sustainable value of artificial intelligence (AI)-driven green collaborative innovation in enterprises amid the global green low-carbon transition, revealing new pathways for digital technology-enabled green development. Based on the data of China’s A-share listed companies jointly applying for green patents with other entities from 2010 to 2023, this study used a high-dimensional fixed effect model to empirically find that artificial intelligence significantly promotes green collaborative innovation. This promoting effect proved more pronounc
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Du, Jiaxing, Han Cai, and Xiu Jin. "Exploring the Association Between Artificial Intelligence Management and Green Innovation: Expanding the Research Field for Sustainable Outcomes." Sustainability 16, no. 21 (2024): 9315. http://dx.doi.org/10.3390/su16219315.

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Green innovation is essential for achieving sustainable development goals (SDGs), particularly SDG 9 (Industry, Innovation, and Infrastructure) and SDG 12 (Responsible Consumption and Production), as it fosters environmental and social benefits while also creating new economic opportunities. Despite previous studies actively conducting empirical analyses on green innovation, research on guiding the green innovation process through artificial intelligence remains scarce. This study aims to explore key variables that affect green innovation, thereby promoting the sustainable development of organ
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Dissertations / Theses on the topic "Green Artificial Intelligence"

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PATEL, SHARMILA, and MARIAM RABIZADEGAN. "Moving Toward Green Production Systems in the Pharmaceutical Industry : Implementing Artificial Intelligence to Increase Environmental Efforts in SMEs." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-300124.

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The pharmaceutical sector is important for human health due to the increasing demand for medical products but is also a pollution and waste intensive industry. There is an urgent need for the industry to review its environmental footprints and simultaneously consider the industrial transformation called Industry 4.0. This is especially true for small and medium sized enterprises (SMEs). To achieve these objectives, it is presumed that artificial intelligence (AI) will have an important role.  This thesis sets out to identify barriers that pharmaceutical SMEs may encounter when implementing AI
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Lakshminarayanan, Srivathsan. "Nature Inspired Grey Wolf Optimizer Algorithm for Minimizing Operating Cost in Green Smart Home." University of Toledo / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1438102173.

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Lu, Lu. "Literature Exploration on the Correlation between Value, Business Model and AI Technology : A Case Study on Urban Green." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279416.

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Value has received an increasing focus in business, meanwhile, under the background of industry 4.0, where the intelligent technologies are significantly reshaping the development of business model and accelerating the innovation. Understanding the correlations between value, business model, and intelligent technology can guide practitioners to create new competitiveness. There’re numerous articles concerning business and technology in recent years. However, few studies touch upon the value’s utilization and impact. The primary purpose of this paper is to explore the value concept adoption in
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Berthelot, Adrien. "L'empreinte environnementale complète d'un usage numérique : contribution à l'analyse de cycle de vie de services numériques." Electronic Thesis or Diss., Lyon, École normale supérieure, 2024. https://theses.hal.science/tel-04874694.

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Dans un contexte de prise en compte des enjeux environnementaux, la réduction des impacts environnementaux du numérique s’est imposée comme une question de recherche en informatique. Cependant, une telle démarche nécessite rapidement une connaissance plus exhaustive de l’empreinte du numérique que la consommation d’électricité d'un serveur ou d'un ordinateur. Déjà présente dans d’autres industries, l’analyse de cycle de vie (ACV), semble être l’outil adéquat pour mieux connaître, contrôler et, in fine, réduire, l’empreinte environnementale du numérique. Cette thèse étudiera l'empreinte en ques
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Elahi, Behin. "Integrated Optimization Models and Strategies for Green Supply Chain Planning." University of Toledo / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1467266039.

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Karathanasopoulos, Andreas. "Modeling and trading the Greek stock market with artificial intelligence models." Thesis, Liverpool John Moores University, 2011. http://researchonline.ljmu.ac.uk/6106/.

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The main motivation for this thesis is to introduce some new methodologies for the prediction of the directional movement of financial assets with an application to the ASE20 Greek stock index. Specifically, we use some alternative computational methodologies named Evolutionary Support Vector Machine (ESVM), Gene Expression programming, Genetic Programming Algorithms and 2 hybrid combinations of linear and no linear models for modeling and trading the ASE20 Greek stock index using as inputs previous values of the ASE20 index and of four other financial indices. For comparison purposes, the tra
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Piloidis, Loukas. "Ethics in Artificial Intelligence : How Relativism is Still Relevant." Thesis, Södertörns högskola, Medie- och kommunikationsvetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:sh:diva-41760.

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This essay tries to demarcate and analyse Artificial Intelligence ethics. Going away from the traditional distinction in normative, meta, and applied ethics, a different split is executed, inspired by the three most prominent schools of thought: deontology, consequentialism, and Aristotelian virtue ethics. The reason behind this alternative approach is to connect all three schools back to ancient Greek philosophy. Having proven that the majority of arguments derive from some ancient Greek scholars (Socrates, Plato, Aristotle), a new voice is initiated into the discussion, Protagoras the Sophis
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Riffelli, Stefano. "Sustainable comfort in indoor environments: global comfort indices and virtual sensors." Doctoral thesis, Urbino, 2022. http://hdl.handle.net/11576/2700929.

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Balestri, Roberto. "Intelligenza artificiale e industrie culturali storia, tecnologie e potenzialità dell’ia nella produzione cinematografica." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2022. http://amslaurea.unibo.it/25176/.

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Negli ultimi anni stiamo assistendo, in svariati campi, a un sempre più vasto utilizzo di tecnologie che utilizzano quella che viene comunemente chiamata “intelligenza artificiale”. Anche il settore audiovisivo, da sempre recettore di novità e incline a evolversi continuamente, sta già vivendo quei processi che lo porteranno a essere rivoluzionato da questo tipo di tecnologie. In un periodo di frenetico progresso scientifico è difficile riuscire a fissare nel tempo e su carta lo stato attuale dello sviluppo tecnologico, dato che ciò che oggi viene considerato come novità domani potrebbe già
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Bag, S., S. Gupta, S. Kumar, and Uthayasankar Sivarajah. "Role of technological dimensions of green supply chain management practices on firm performance." 2020. http://hdl.handle.net/10454/17875.

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yes<br>Purpose The research study aims to investigate green supply chain management (GSCM) elements as part of a complete system. It aims to understand the special properties of the GSCM system under the moderating effects of product complexity and purchasing structure. Design/methodology/approach A thorough literature review led to the building of the conceptual framework. Six constructs were identified using systems theory. These constructs include green supply chain technological dimensions (particularly, Artificial Intelligence (AI) based), green supply chain strategy, green supply ch
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Books on the topic "Green Artificial Intelligence"

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Idrissi, Najlae, Abdellatif Hair, Mohamed Lazaar, Youssef Saadi, Mohammed Erritali, and Said El Kafhali, eds. Artificial Intelligence and Green Computing. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-46584-0.

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Hassanien, Aboul Ella, Ashraf Darwish, and Sally M. Elghamrawy, eds. Artificial Intelligence for Environmental Sustainability and Green Initiatives. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-63451-2.

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Radev, Dragomir. Puzzles in Logic, Languages and Computation: The Green Book. Springer Berlin Heidelberg, 2013.

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El Himer, Sarah, Mariyam Ouaissa, Abdulrahman A. A. Emhemed, Mariya Ouaissa, and Zakaria Boulouard, eds. Artificial Intelligence of Things for Smart Green Energy Management. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-04851-7.

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Khang, Alex, ed. Driving Green Transportation System Through Artificial Intelligence and Automation. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-72617-0.

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Coimbatore, India) International Conference on Intelligent Systems and Control (7th 2013. 7th International Conference on Intelligent Systems and Control (ISCO 2013), January 04-05, 2013, Coimbatore, Tamilnadu, India. Allied Publishers, 2013.

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Cho, Hyun-seob. Green and Smart Technology with Sensor Applications: International Conferences, GST and SIA 2012, Jeju Island, Korea, November 28-December 2, 2012. Proceedings. Springer Berlin Heidelberg, 2012.

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Aris, Dimeas, Tomtsi Thomai, Weidlich Anke, and SpringerLink (Online service), eds. Energy-Efficient Computing and Networking: First International Conference, E-Energy 2010, Athens, Greece, October 14-15, 2010, Revised Selected Papers. Springer Berlin Heidelberg, 2011.

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Beránková, Eva Voldřichová. Učiňme člověka ke svému obrazu: Pygmalion, Golem a automat jako tři verze mýtu o umělém stvoření (nejen) v Budoucí Evě Villierse de l'Isle-Adam. Nakladatelství Karolinum, 2012.

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Heudin, Jean-Claude. Robots & avatars: Le rêve de Pygmalion. O. Jacob, 2009.

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Book chapters on the topic "Green Artificial Intelligence"

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Hamid, Kanchan Bhatt, Naseer Ahmed, and Priyanka Chauhan. "Green Artificial Intelligence." In Artificial Intelligence Techniques for Sustainable Development. CRC Press, 2024. http://dx.doi.org/10.1201/9781003546382-15.

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Yigitcanlar, Tan. "Green Artificial Intelligence." In Smart City Blueprint. Chapman and Hall/CRC, 2023. http://dx.doi.org/10.1201/9781003403630-9.

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Banafa, Ahmed. "Green Artificial Intelligence." In Artificial Intelligence in Action. River Publishers, 2025. https://doi.org/10.1201/9788770046213-14.

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Halsey, Mike. "Artificial Intelligence and Climate Change." In The Green IT Guide. Apress, 2025. https://doi.org/10.1007/979-8-8688-1233-0_5.

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Abdulmuhsin, Amir A., Hayder DH Hussein, Ramadan Mahmood Ramo, Ra’ed Masa’deh, and Abeer F. Alkhwaldi. "Artificial Intelligence and Green Innovation." In Studies in Computational Intelligence. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-89175-5_37.

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Sejana, Jose V., H. Sandhya, and Bindi Varghese. "Artificial Intelligence in Green Transportation." In AI, Blockchain, and Metaverse in Hospitality and Tourism Industry 4.0. Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9781032706474-20.

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Purthi, Annu. "Artificial Intelligence in Green Accounting." In Applications of Artificial Intelligence in Business and Finance. Apple Academic Press, 2021. http://dx.doi.org/10.1201/9781003129639-10.

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Singh, Jaswinder Pal, and Shivani Inder. "Green Finance and Artificial Intelligence." In Green Engineering for Optimizing Firm Performance. Chapman and Hall/CRC, 2025. https://doi.org/10.1201/9781003626527-13.

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Fouzdar, Akanksha Singh, Ankit Saxena, and Sujit Kumar Jha. "Harnessing Artificial Intelligence for Sustainable Financial Planning." In Green Horizons. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-6495-5_15.

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Hassanein, Ahmed, and Hana Tharwat. "Artificial Intelligence (AI) and Green Finance." In Palgrave Studies in Impact Finance. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-65756-6_32.

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Conference papers on the topic "Green Artificial Intelligence"

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Lawati, Essam Hussain Al, Musab A. M. Ali, and Nooritawati Md Tahir. "The Importance of Artificial Intelligence in Green Innovation." In 2024 IEEE 14th International Conference on Control System, Computing and Engineering (ICCSCE). IEEE, 2024. http://dx.doi.org/10.1109/iccsce61582.2024.10696270.

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Kırat, Oğuz, and Alper Çiçek. "Artificial Intelligence Based Optimal Operation of Green Hydrogen Refueling." In 2024 32nd Telecommunications Forum (TELFOR). IEEE, 2024. https://doi.org/10.1109/telfor63250.2024.10819143.

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Basha, Thippaluri Yahid, Barma Kalyani, and Yelisetti Sandeep. "Generative Artificial Intelligence in Legal Drafting." In 2024 International Conference on Computational Intelligence for Green and Sustainable Technologies (ICCIGST). IEEE, 2024. http://dx.doi.org/10.1109/iccigst60741.2024.10717541.

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Periola, A. A., A. A. Alonge, and K. A. Ogudo. "Green Intelligent Content Rendering Paradigm." In 2024 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems (icABCD). IEEE, 2024. http://dx.doi.org/10.1109/icabcd62167.2024.10645257.

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Acharya, Himanshu, Sweta Tripathi, and Manoj Pandey. "Amipi: Artificial Intelligence Based Interactive Humanoid Interface." In 2024 2nd International Conference on Advancements and Key Challenges in Green Energy and Computing (AKGEC). IEEE, 2024. https://doi.org/10.1109/akgec62572.2024.10868458.

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Mnassri, Hamza, Riadh Bchir, Mohamed Amine Zayane, and Taoufik Ladhari. "Sign Language Detection Based on Artificial Intelligence from Images." In 2024 IEEE International Conference on Artificial Intelligence & Green Energy (ICAIGE). IEEE, 2024. https://doi.org/10.1109/icaige62696.2024.10776617.

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Jabin, Shagufta, Sadiqa Abbas, Anupama Chadha, and Jyoti Chawla. "Application of Artificial Intelligence in Soil Contamination Analysis: Green Sustainable Practices." In 2024 2nd International Conference on Advances in Computation, Communication and Information Technology (ICAICCIT). IEEE, 2024. https://doi.org/10.1109/icaiccit64383.2024.10912319.

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Saksupapchon, Punyapat. "Tracing the Evolution of Artificial Intelligence Patent Trends in Green Transportation." In 2024 IEEE International Smart Cities Conference (ISC2). IEEE, 2024. https://doi.org/10.1109/isc260477.2024.11004287.

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Balushi, Nasim Al. "Innovating Economic Models for Smart Green Cities Through Artificial Intelligence Techniques." In 2025 International Conference for Artificial Intelligence, Applications, Innovation and Ethics (AI2E). IEEE, 2025. https://doi.org/10.1109/ai2e64943.2025.10982723.

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Yu, Yao. "Research on the application of artificial intelligence in green building design optimization." In The International Conference Optoelectronic Information and Optical Engineering (OIOE2024), edited by Yang Yue and Lu Leng. SPIE, 2025. https://doi.org/10.1117/12.3045836.

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Reports on the topic "Green Artificial Intelligence"

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Prins, Herbert H. T. Preserving nature: Artificial Intelligence against Green Violence. Wageningen University & Research, 2019. http://dx.doi.org/10.18174/514745.

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van Rooij, S. A. M., W. M. L. Meijninger, M. van Eupen, S. Los, and U. Bairam. Flower richness green veining : Monitoring flower richness using remote sensing & artificial intelligence. Wageningen University & Research, 2022. http://dx.doi.org/10.18174/586185.

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Brian, Dominikus. Next-Generation Smart-City Energy and Resource Management Powered by Exascale Green Computing Infrastructure and Artificial Intelligence System. ResearchHub Technologies, Inc., 2024. http://dx.doi.org/10.55277/researchhub.rv1s6td0.

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Latorre, Lucia, Carlo Magno Rivera Picado, and Emeli Florencia Ozcoidi. Green IT Strategies: Innovating for a Sustainable Digital Future. Inter-American Development Bank, 2025. https://doi.org/10.18235/0013611.

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This report explores the main areas of intervention of Green IT, such as the mapping of carbon emissions throughout the value chain, the virtualization of physical resources, the adoption of cloud computing services, and the design of green data centers that include sustainability criteria. Risks and consequences associated with greater digitalization are also identified, such as the rebound effect and the growth in the volume of data stored, even those without real use (“dark data”), as well as the ambivalent role of emerging technologies such as artificial intelligence and blockchain, whose
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Quimba, Francis Mark, Ramonette Serafica, Connie Bayudan-Dacuycuy, Abigail Andrada, and Neil Irwin Moreno. Green and Digital: Managing the Twin Transition toward Sustainable Development. Philippine Institute for Development Studies, 2023. http://dx.doi.org/10.62986/dp2023.21.

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The global shift toward sustainability and increased digitalization is evident. Nations are integrating renewable energy, carbon emission reduction, and advancements in green technologies into their development plans. Simultaneously, Industry 4.0 has revealed the diverse ways technology influences human life. Rather than separate factors, these dual forces are interconnected elements that countries must navigate for sustainable progress. As countries pursue development strategies, taking a closer look at this twin phenomenon is important. This study assesses how investments, labor, science, te
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Gidwani, Mohit, Narine Avetisyan, Yoonee Jeong, and Christine Apikul. The Emerging Data Center Market in Armenia and Opportunities for Sustainable Growth. Asian Development Bank, 2024. https://doi.org/10.22617/brf240515-2.

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This brief analyzes Armenia’s emerging data center market and shows why it needs to expand its green energy, adopt carbon-efficient technology, and accommodate the latest technology trends to maximize its growth potential. The brief highlights forecasts for Armenia to increase its data center racks from 550 to up to 2,000 by 2028 and explains how its location alongside government support and financing gives it a competitive advantage. It recommends Armenia look to enhance its resilient international connectivity, accommodate generative artificial intelligence and edge computing requirements, a
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Prada, María Fernanda, and Graciana Rucci. Skills for Work in Latin America and the Caribbean: Unlocking Talent for a Sustainable and Equitable Future. Inter-American Development Bank, 2023. http://dx.doi.org/10.18235/0005160.

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Skills for work are undoubtedly a transformative force for Latin America and the Caribbean. The developed countries' experience has shown that when a country's labor force responds efficiently to the human capital needs of companies and the economy, labor productivity is boosted leading to higher and sustainable economic growth. Through the TVET Fund, IDB is promoting innovative solutions and demonstrating how skills systems can take advantage of the opportunities presented by the fourth industrial revolution, gender and diversity, ageing, climate change and COVID-19, which will be essential i
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Pasupuleti, Murali Krishna. Sustainable and Affordable Global Housing via AI and Advanced Materials. National Education Services, 2025. https://doi.org/10.62311/nesx/rr425.

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Abstract: The global housing crisis demands innovative solutions that balance affordability, sustainability, and technological advancement. This research report explores the transformative role of Artificial Intelligence (AI) and advanced materials in addressing housing shortages, reducing environmental impact, and improving construction efficiency. AI-driven generative design, smart automation, and predictive analytics optimize resource allocation and enhance structural safety, while advanced materials such as 3D-printed composites, self-healing concrete, aerogels, and bio-based materials rev
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de Kemp, E. A., H. A. J. Russell, B. Brodaric, et al. Initiating transformative geoscience practice at the Geological Survey of Canada: Canada in 3D. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/331097.

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Application of 3D technologies to the wide range of Geosciences knowledge domains is well underway. These have been operationalized in workflows of the hydrocarbon sector for a half-century, and now in mining for over two decades. In Geosciences, algorithms, structured workflows and data integration strategies can support compelling Earth models, however challenges remain to meet the standards of geological plausibility required for most geoscientific studies. There is also missing links in the institutional information infrastructure supporting operational multi-scale 3D data and model develo
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de Kemp, E. A., H. A. J. Russell, B. Brodaric, et al. Initiating transformative geoscience practice at the Geological Survey of Canada: Canada in 3D. Natural Resources Canada/CMSS/Information Management, 2023. http://dx.doi.org/10.4095/331871.

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Abstract:
Application of 3D technologies to the wide range of Geosciences knowledge domains is well underway. These have been operationalized in workflows of the hydrocarbon sector for a half-century, and now in mining for over two decades. In Geosciences, algorithms, structured workflows and data integration strategies can support compelling Earth models, however challenges remain to meet the standards of geological plausibility required for most geoscientific studies. There is also missing links in the institutional information infrastructure supporting operational multi-scale 3D data and model develo
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