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Relevant bibliographies by topics / Artificial intelligence in industry

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Academic literature on the topic 'Artificial intelligence in industry'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

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Journal articles on the topic "Artificial intelligence in industry"

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M., N. O. Sadiku, R. Nelatury S., and Musa S.M. "Artificial Intelligence in Industry." Journal of Scientific and Engineering Research 8, no. 2 (2021): 45–52. https://doi.org/10.5281/zenodo.10574946.

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<strong>Abstract </strong>Artificial intelligence (AI) refers to computer systems that mimic human cognitive functions. AI-driven systems can discover trends, reveal inefficiencies, and predict future outcomes.  These characteristics enable informed decision-making and AI to be potentially beneficial for many industries. Industrial AI deals with the application of AI technologies to address industrial issues such customer value creation, productivity improvement, cost reduction, site optimization, predictive analysis, and insight discovery.  This paper provides different applications

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Dooner, Mike. "Artificial intelligence in industry." Computer Integrated Manufacturing Systems 2, no. 1 (1989): 58. http://dx.doi.org/10.1016/0951-5240(89)90042-6.

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Bohra, Mrs Jyoti M., and Ms Bhagyashri G. Joshi. "Artificial Intelligence and its Role in Industry." International Journal of Trend in Scientific Research and Development Special Issue, Special Issue-ICDEBI2018 (2018): 204–7. http://dx.doi.org/10.31142/ijtsrd18705.

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Konovalov, Yuriy, and Anton Vaygachev. "ARTIFICIAL INTELLIGENCE IN POWER INDUSTRY." Modern Technologies and Scientific and Technological Progress 1, no. 1 (2021): 225–26. http://dx.doi.org/10.36629/2686-9896-2021-1-1-225-226.

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Trends in the development of artificial intelligence and the use of neural networks as  applied to the power industry are considered. It is revealed that the well-known forecasting systems  based on artificial neural networks are difficult to formalize and get an unambiguous solution. There fore, this problem must be solved using a systematic approach that combines the capabilities of artifi cial neural networks and fuzzy logic under conditions of partial uncertainty of parameters

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Gadde, Sai Sruthi. "Artificial Intelligence at Healthcare Industry." International Journal for Research in Applied Science and Engineering Technology 9, no. 2 (2021): 311–14. http://dx.doi.org/10.22214/ijraset.2021.32996.

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Sheshadri, Thejasvi. "Artificial Intelligence in Industry 4.0." African Journal of Biological Sciences 6, no. 6 (2024): 2316–26. http://dx.doi.org/10.48047/afjbs.6.6.2024.2316-2326.

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Many industry sectors have been pursuing the adoption of Industry 4.0 (I4.0) ideas and technologies, which promise to realize lean and just-in-time production through digitization and the use of smart machines. This shift is driven by technological advances, including Artificial Intelligence (AI) and machine learning, sensor networks and Internet of Things technologies, cloud computing, additive manufacturing, and the availability of large amounts of data that can be exploited by these technologies. However, the adoption of AI technologies for I4.0 varies considerably among industry sectors. T

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Sadiku, Matthew N. O., OmobayodeI Fagbohungbe, and Sarhan M. Musa. "Artificial Intelligence in Food Industry." International Journal of Engineering Research and Advanced Technology 06, no. 10 (2020): 12–19. http://dx.doi.org/10.31695/ijerat.2020.3649.

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Kashiripoor, M. M., and V. A. Nikolyuk. "Artificial intelligence in construction industry." Vestnik Tomskogo gosudarstvennogo arkhitekturno-stroitel'nogo universiteta. JOURNAL of Construction and Architecture 26, no. 1 (2024): 163–78. http://dx.doi.org/10.31675/1607-1859-2024-26-1-163-178.

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Purpose: The aim of this work is to study new trends in construction, their advantages and disadvantages, application of innovations, analysis of operability and efficiency of new technologies in the global construction industry.Methodology/approach: The literature review and systematization, study the expert opinion on open access resources, portals of private enthusiasts involved in seeking for ways to introduce and implement modern technologies in the construction industry.Research findings: The paper presents methods and conditions of using modern technologies in the world practice, disadv

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Ebert, Christof, and Xuya Wang. "China Artificial Intelligence Industry Insights." Computer 57, no. 6 (2024): 97–101. http://dx.doi.org/10.1109/mc.2024.3382422.

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Ambica, Khurana. "Artificial Intelligence in Textile Industry." International Journal of Advance and Applied Research 10, no. 3 (2023): 207–9. https://doi.org/10.5281/zenodo.7623815.

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In this era of information technology, there are a lot of ongoing discoveries and developments. Artificial Intelligence research is one of the most exciting fields in technology. Artificial Intelligence  has revolutionized many fields. It is shaping the future of humanity across and has swept across various industries. One area artificial intelligence is seeing growth in is the textile industry. The automation with applications of artificial intelligence in textile production is becoming much popular due to the technical developments and the use of modeling and simulation.

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Dissertations / Theses on the topic "Artificial intelligence in industry"

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Каптюрова, Дарія Олександрівна. "Usage of artificial intelligence in footwear industry." Thesis, Київський національний університет технологій та дизайну, 2020. https://er.knutd.edu.ua/handle/123456789/15308.

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Han, Choong-Hee. "Artificial intelligence methodology for simulatron modeling." Diss., Georgia Institute of Technology, 1990. http://hdl.handle.net/1853/20285.

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Legkiy, Yaroslav, Ярослав Ярославович Легкий, Bohdan Dubchak, and Богдан Мстиславович Дубчак. "Machine learning &artificial intelligence in aerospace industry." Thesis, National Aviation University, 2021. https://er.nau.edu.ua/handle/NAU/50479.

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Machine Learning & Artificial Intelligence in Aerospace Industry URL: https://www.axiscades.com/blog-resources/whitepaper/Aerospacewhitepaper.pdf<br>It depicts the artіficіal іntelligence as a signіficant role іn cutting costs, reducing the design cycle tіme, simulation, prototyping, optimizatіon, maіntenance, manufacturіng and updatіng products.<br>Визначено штучний інтелект як значущу роль у скороченні витрат, зменшенні часу циклу проектування, моделюванні, прототипуванні, оптимізації, технічному обслуговуванні, виробництві та модернізації продукції.

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Jain, Chahat. "Artificial intelligence in venture capital industry : opportunities and risks." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/118544.

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Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, System Design and Management Program, 2018.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 70-74).<br>Artificial intelligence - making machines intelligent - is a methodology to build, train, and run machines that are capable of making decisions on its own. Artificial intelligence technologies are gaining significant adoption across a wide range of activities in an organization across different industries. This is fueled by increasing focus on data-driven decision-making m

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Abramovych, G. V., S. А. Ryndin, and Г. В. Абрамович. "Implementation of artificial intelligence in human life." Thesis, ВНТУ, 2019. http://ir.lib.vntu.edu.ua//handle/123456789/24131.

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The article considers the advantages and disadvantages of using artificial intelligence in human life. The risks of its usage and thoughts of prominent developers are presented.<br>В статті розглянуто переваги і недоліки використання штучного інтелекту у житті людини. Наводяться ризики його використання та думки відомих розробників.

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Shahini, Rei. "Business Intelligence in the Hotel Industry." Thesis, Linnéuniversitetet, Institutionen för informatik (IK), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-100845.

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Applications of artificial intelligence (AI) in hospitality and accommodation have taken an enormous percentage of service-provision, helping automate most of the processes involved such as booking and purchasing, improving the guest experience, tracking of guest preferences and interests, etc. The aim of the study is to understand the roles, benefits and issues with the improvement of business intelligence (BI) in hospitality. This research is purposed to discover the applications of BI in hotel booking and accommodation. The investigation focuses on hotel guest experience, business operation

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Guisiano, Jade Eva. "Dynamic Methane Inventory for Oil and Gas Industry based on Artificial Intelligence." Electronic Thesis or Diss., Sorbonne université, 2024. http://www.theses.fr/2024SORUS206.

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Le méthane atmosphérique est responsable d'environ la moitié du réchauffement climatique depuis l'époque préindustrielle, par rapport à l'influence humaine totale nette. Le secteur pétrolier et gazier se classe au deuxième rang des sources anthropiques de méthane malgré la possibilité d'une réduction de 39 % de ses émissions sans coût net. Cependant, le manque de données fiables sur les émissions nuit à la capacité des gouvernements à mettre en œuvre des mesures d'atténuation efficaces à l'échelle et à la vitesse nécessaires pour atteindre les objectifs fixés par le Global Mthane Pledge. Afin

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Lowe, Timothy James. "Constraint techniques applied to teamworking tasks in clothing industry production." Thesis, Manchester Metropolitan University, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.389493.

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Regona, Massimo. "Opportunities and adoption constraints of artificial intelligence in the construction industry: A scoping study." Thesis, Queensland University of Technology, 2022. https://eprints.qut.edu.au/232514/1/Massimo_Regona_Thesis.pdf.

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This MPhil thesis provides an overview of AI technologies and the key opportunities and challenges these technologies bring to the construction industry. The first study was a literature review that identified and explored the theoretical foundations underpinning AI technologies that are currently being used in construction, specifically in the design, planning and construction stages. Secondly, the study used social media analytics to explore AI technology adoption, prospects and constraints in the Australian construction industry. Finally, a sentiment analysis established the opportunities,

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Nystad, Marcus, and Lukas Lindblom. "Artificial Intelligence in the Pulp and Paper Industry : Current State and Future Trends." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279574.

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The advancements in Artificial Intelligence (AI) have received large attention in recent years and increased awareness has led to massive societal benefits and new opportunities for industries able to capitalize on these emerging technologies. The pulp and paper industry is going through one of the most considerable transformations into Industry 4.0. Integrating AI technology in the manufacturing process of the pulp and paper industry has shown great potential, but there are uncertainties which direction companies are heading. This study is an investigation of the pulp and paper industry in co

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Books on the topic "Artificial intelligence in industry"

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Bielicki, Damian M. Regulating Artificial Intelligence in Industry. Routledge, 2021. http://dx.doi.org/10.4324/9781003246503.

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Dingli, Alexiei, Foaad Haddod, and Christina Klüver, eds. Artificial Intelligence in Industry 4.0. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-61045-6.

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Talukdar, Jyotismita, Thipendra P. Singh, and Basanta Barman. Artificial Intelligence in Healthcare Industry. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-3157-6.

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inc, International Resource Development, ed. Artificial intelligence markets. International Resource Development Inc., 1986.

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Vermesan, Ovidiu. Artificial Intelligence for Digitising Industry – Applications. River Publishers, 2022. http://dx.doi.org/10.1201/9781003337232.

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Zahoor, Insha, Sajad Ahmad Wani, and Tariq Ahmad Ganaie. Artificial Intelligence in the Food Industry. CRC Press, 2024. https://doi.org/10.1201/9781032633602.

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Tuovinen, Tero, Jacques Periaux, and Pekka Neittaanmäki, eds. Computational Sciences and Artificial Intelligence in Industry. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-70787-3.

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Awasthi, Shashank, Carlos M. Travieso-González, Goutam Sanyal, and Dinesh Kumar Singh, eds. Artificial Intelligence for a Sustainable Industry 4.0. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77070-9.

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Sharma, Rohit, Rajendra Prasad Mahapatra, and Gwanggil Jeon. Artificial Intelligence and Blockchain in Industry 4.0. CRC Press, 2023. http://dx.doi.org/10.1201/9781003452591.

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J, Hindin Harvey, ed. Artificial intelligence in business, science, and industry. Prentice-Hall, 1985.

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Book chapters on the topic "Artificial intelligence in industry"

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Li, Luo. "Artificial intelligence." In Regulating Artificial Intelligence in Industry. Routledge, 2021. http://dx.doi.org/10.4324/9781003246503-9.

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Lakemeyer, Gerhard. "Artificial Intelligence 4.0." In Handbook Industry 4.0. Springer Berlin Heidelberg, 2022. http://dx.doi.org/10.1007/978-3-662-64448-5_36.

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Dureja, Aman, Aditi, and Payal Pahwa. "Artificial Intelligence." In Industry 4.0, AI, and Data Science. CRC Press, 2021. http://dx.doi.org/10.1201/9781003097181-6.

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Hopmann, Christian, and Mauritius Schmitz. "Models and Artificial Intelligence." In Plastics Industry 4.0. Carl Hanser Verlag GmbH & Co. KG, 2021. http://dx.doi.org/10.1007/978-1-56990-797-9_4.

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Hopmann, Christian, and Mauritius Schmitz. "Models and Artificial Intelligence." In Plastics Industry 4.0. Carl Hanser Verlag GmbH & Co. KG, 2020. http://dx.doi.org/10.3139/9781569907979.004.

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Sheikh, Fazil, and S. Y. Amdani. "Artificial Intelligence in Industry." In Parallel and High-Performance Computing in Artificial Intelligence. Auerbach Publications, 2025. https://doi.org/10.1201/9781003425458-15.

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Jang, Tae Jun, Sang-Hwy Lee, Hye Sun Yun, and Jin Keun Seo. "Artificial Intelligence for Digital Dentistry." In Mathematics in Industry. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1839-3_4.

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Cho, Hyun Cheol, Siyu Sun, Sung Wook Park, Ja-Young Kwon, and Jin Keun Seo. "Artificial Intelligence for Fetal Ultrasound." In Mathematics in Industry. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1839-3_5.

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Machhan, Rishabh, Rupen Trehan, Perminderjit Singh, and Kuldip Singh Sangwan. "Blockchain, artificial intelligence, and big data." In Industry 4.0. CRC Press, 2023. http://dx.doi.org/10.1201/9781003246466-6.

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Shumskaia, Ekaterina I. "Artificial Intelligence—Reducing the Carbon Footprint?" In Industry 4.0. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-79496-5_33.

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Conference papers on the topic "Artificial intelligence in industry"

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Flores, Fabiola Gabriela Bosmans, Valeria Yolanda Rodríguez Chacón, Ana Cristina Abarca Caqui, Madeleine Lourdes Palacios-Núñez, and Linda Giovanna Pongo Alva. "Artificial Intelligence and Industry: a bibliometrics analysis." In 2024 IEEE XXXI International Conference on Electronics, Electrical Engineering and Computing (INTERCON). IEEE, 2024. https://doi.org/10.1109/intercon63140.2024.10833457.

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Bhatt, Stuti, and Sachin Sharma. "Generative Artificial Intelligence Based Biomedical Applications for Pharmaceutical Industry." In 2025 International Conference on Computational, Communication and Information Technology (ICCCIT). IEEE, 2025. https://doi.org/10.1109/icccit62592.2025.10927855.

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won, Koohee K., Minyoung Lee, and Eunil Park. "Bibliometric Study of Artificial Intelligence and Semiconductor Manufacturing Industry." In 2024 15th International Conference on Information and Communication Technology Convergence (ICTC). IEEE, 2024. https://doi.org/10.1109/ictc62082.2024.10827173.

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Da Rocha, Helbert, Gang Chen, En Li, José A. Salvado, and Antonio Espirito-Santo. "Smart Transducers, Robotics and Artificial Intelligence in Industry 4.0." In 2025 IEEE International Conference on Industrial Technology (ICIT). IEEE, 2025. https://doi.org/10.1109/icit63637.2025.10965221.

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Masod, Muhammad Yusuf Bin, and Siti Farhana Zakaria. "Application of Artificial Intelligence in Printing Industry: Systematic Review." In 2024 IEEE 12th Conference on Systems, Process & Control (ICSPC). IEEE, 2024. https://doi.org/10.1109/icspc63060.2024.10861924.

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Rashidov, Akbar, Dilmurod Mardonov, and Akbar Soliev. "Diagnosis of Diabetes Mellitus Based on Artificial Intelligence Algorithms." In 2025 International Russian Smart Industry Conference (SmartIndustryCon). IEEE, 2025. https://doi.org/10.1109/smartindustrycon65166.2025.10986060.

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Alevizos, Vasileios, George A. Papakostas, Akebu Simasiku, et al. "Integrating Artificial Open Generative Artificial Intelligence into Software Supply Chain Security." In 2024 5th International Conference on Data Analytics for Business and Industry (ICDABI). IEEE, 2024. https://doi.org/10.1109/icdabi63787.2024.10800301.

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Gangdhar, Sangeeta, and S. N. Patil. "Concrete Crack Detection Using Artificial Intelligence." In 2024 2nd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry (IDICAIEI). IEEE, 2024. https://doi.org/10.1109/idicaiei61867.2024.10842855.

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Gorda, Maxim. "On the Use of Artificial Intelligence in Cybersecurity Incident Investigations." In 2025 International Russian Smart Industry Conference (SmartIndustryCon). IEEE, 2025. https://doi.org/10.1109/smartindustrycon65166.2025.10986177.

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Nurmamatov, Mekhriddin, Shokhrukh Sariyev, and Izhar Uddin. "Methods of Using Artificial Intelligence Algorithms in Human Resource Management." In 2025 International Russian Smart Industry Conference (SmartIndustryCon). IEEE, 2025. https://doi.org/10.1109/smartindustrycon65166.2025.10986087.

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Reports on the topic "Artificial intelligence in industry"

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Arnold, Zachary, and Ngor Luong. China’s Artificial Intelligence Industry Alliance. Center for Security and Emerging Technology, 2021. http://dx.doi.org/10.51593/20200094.

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As part of its strategy to achieve global leadership in AI, the Chinese government brings together local governments, academic institutions, and companies to establish collaboration platforms. This data brief examines the role of China’s Artificial Intelligence Industry Alliance in advancing its AI strategy, and the key players in the Chinese AI industry.

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Korinek, Anton, and Jai Vipra. Concentrating Intelligence: Scaling and Market Structure in Artificial Intelligence. Institute for New Economic Thinking Working Paper Series, 2024. http://dx.doi.org/10.36687/inetwp228.

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This paper examines the evolving structure and competition dynamics of the rapidly growing market for foundation models, focusing on large language models (LLMs). We describe the technological characteristics that shape the industry and have given rise to fierce competition among the leading players. The paper analyzes the cost structure of foundation models, emphasizing the importance of key inputs such as computational resources, data, and talent, and identifies significant economies of scale and scope that may create a tendency towards greater market concentration in the future. We explore

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Sylvester, Prem, Wendy Hui Kyong Chun, Anikó Hannák, et al. Global Approaches to Auditing Artificial Intelligence: A Literature Review. Edited by Danaë Metaxa, Jack Bandy, Luis Adrián Castro-Quiroa, et al. International Panel on the Information Environment (IPIE), 2024. https://doi.org/10.61452/bwym7397.

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This Synthesis Report is a literature review outlining the regulatory, industry, and academic approaches to AI audits. We review 78 articles published in peer-reviewed journals and as preprints, 21 documents from industry associations and standard-setting organizations, and national policy documents and regulations from 20 countries. Based on this review, we identify three key takeaways about the landscape of AI auditing: 1. To accurately assess the potential risks, and impacts of AI systems, we need a trustworthy audit ecosystem with complementary approaches from internal, external, and commu

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Fedasiuk, Ryan, Jennifer Melot, and Ben Murphy. Harnessed Lightning: How the Chinese Military is Adopting Artificial Intelligence. Center for Security and Emerging Technology, 2021. http://dx.doi.org/10.51593/20200089.

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This report examines nearly 350 artificial intelligence-related equipment contracts awarded by the People’s Liberation Army and state-owned defense enterprises in 2020 to assess how the Chinese military is adopting AI. The report identifies China’s key AI defense industry suppliers, highlights gaps in U.S. export control policies, and contextualizes the PLA’s AI investments within China’s broader strategy to compete militarily with the United States.

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Doo, Johnny. Beyond Aviation: Embedded Gaming, Artificial Intelligence, Training, and Recruitment for the Advanced Air Mobility Industry. SAE International, 2024. https://doi.org/10.4271/epr2024028.

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<div class="section abstract"><div class="htmlview paragraph">Recent advancements in electric vertical take-off and landing (eVTOL) aircraft and the broader advanced air mobility (AAM) movement have generated significant interest within and beyond the traditional aviation industry. Many new applications have been identified and are under development, with considerable potential for market growth and exciting potential. However, talent resources are the most critical parameters to make or break the AAM vision, and significantly more talent is needed than the traditional aviation ind

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Szladow, A. J. Application of artificial intelligence technology to increase productivity, quality and energy efficiency in heavy industry. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1995. http://dx.doi.org/10.4095/315015.

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Smith, Curtis, Ahmad Al Rashdan, and Vivek Agarwal. Using 'The New Math' - Artificial Intelligence and Machine Learning Applications in the Nuclear Power Industry. Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/1968441.

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King, Wayne. Barriers to Adoption of Artificial Intelligence in Metal Additive Manufacturing. SAE International, 2025. https://doi.org/10.4271/epr2025001.

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<div class="section abstract"><div class="htmlview paragraph">Artificial intelligence (AI) is poised to significantly impact metal additive manufacturing (AM). Understanding how one might use AI in AM is challenging because AM experts are not AI experts, nor the other way around. This document introduces AI in AM and guides researchers in accessing relevant literature. It also discusses the hype surrounding AI in AM, the rush to publish peer-reviewed papers that use AI in AM, and the resulting uneven quality of the literature. Conclusions regarding the application of AI in both lar

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Liu, Tong, and Hadi Meidani. Artificial Intelligence for Optimal Truck Platooning: Impact on Autonomous Freight Delivery. Illinois Center for Transportation, 2023. http://dx.doi.org/10.36501/0197-9191/23-017.

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The advancements in autonomous- and connected-vehicle technologies bring drastic changes in freight delivery. Vehicle-to-vehicle and vehicle-to-infrastructure communication has become a reality with the help of autonomous and connected vehicles. One of the most notable changes is the formation of truck platoons. Despite the numerous benefits of truck platooning, such as reduced fuel consumption and increased traffic efficiency, this approach requires a significant amount of computational resources to obtain aerodynamic performance under different scenarios. To overcome this challenge, a data-d

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Li, Richard. DeepSeek: Revolutionising the AI industry. LegalOne Global Limited, 2025. https://doi.org/10.62436/a-1740063218021.

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Recently, DeepSeek, a Chinese artificial intelligence (AI) startup, has made headlines with its groundbreaking advancements in AI technology. Founded in 2023 by entrepreneur Liang Wenfeng, DeepSeek has quickly risen to prominence, challenging established AI giants like OpenAI and Google. DeepSeek, headquartered in Hangzhou, China, is known for its cost-efficient AI models and open-source approach, making advanced AI technology accessible to a wider range of businesses and developers. Open-source AI refers to systems whose source code, datasets, and model parameters are freely available for any

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