Optimizing intelligent systems for cross-industry application:
Intelligent systems, powered by artificial intelligence (AI) and machine learning, offer transformative benefits across diverse sectors, from healthcare and finance to manufacturing and agriculture. By refining these systems to be more adaptable, scalable, and informative, industries can solve compl...
Gespeichert in:
| Weitere Verfasser: | , , , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Hershey, Pennsylvania
IGI Global
2024
|
| Schriftenreihe: | Advances in computational intelligence and robotics (ACIR) book series
|
| Schlagworte: | |
| Online-Zugang: | DE-91 DE-1050 Volltext |
| Zusammenfassung: | Intelligent systems, powered by artificial intelligence (AI) and machine learning, offer transformative benefits across diverse sectors, from healthcare and finance to manufacturing and agriculture. By refining these systems to be more adaptable, scalable, and informative, industries can solve complex business problems and streamline operations. Effective research into technical challenges across intelligent system application is necessary to prioritize their development and impact in industries, such as crop analysis, disease diagnosis, or traffic management. Optimizing Intelligent Systems for Cross-Industry Application explores the challenges and opportunities associated with intelligent technology integration in various sectors, including agriculture, medicine, healthcare, computer engineering, business management, and environmental research. It presents solutions for the effective use of intelligent systems within their respective industries. This book covers topics such as human resources, smart cities, and crop productivity, and is a useful resource for computer engineers, agriculturalists, business owners, healthcare professionals, environmentalists, researchers, scientists, and academicians. |
| Beschreibung: | 1 Online-Ressource (559 Seiten) |
| DOI: | 10.4018/979-8-3693-8659-0 |
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| discipline | Informatik Wirtschaftswissenschaften |
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| indexdate | 2024-12-17T19:01:34Z |
| institution | BVB |
| language | English |
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| publishDate | 2024 |
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| publisher | IGI Global |
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| series2 | Advances in computational intelligence and robotics (ACIR) book series |
| spelling | Optimizing intelligent systems for cross-industry application S. Suman Rajest, Salvatore Moccia, Bhopendra Singh, R. Regin, Joseph Jeganathan, editors Hershey, Pennsylvania IGI Global 2024 1 Online-Ressource (559 Seiten) txt rdacontent c rdamedia cr rdacarrier Advances in computational intelligence and robotics (ACIR) book series Intelligent systems, powered by artificial intelligence (AI) and machine learning, offer transformative benefits across diverse sectors, from healthcare and finance to manufacturing and agriculture. By refining these systems to be more adaptable, scalable, and informative, industries can solve complex business problems and streamline operations. Effective research into technical challenges across intelligent system application is necessary to prioritize their development and impact in industries, such as crop analysis, disease diagnosis, or traffic management. Optimizing Intelligent Systems for Cross-Industry Application explores the challenges and opportunities associated with intelligent technology integration in various sectors, including agriculture, medicine, healthcare, computer engineering, business management, and environmental research. It presents solutions for the effective use of intelligent systems within their respective industries. This book covers topics such as human resources, smart cities, and crop productivity, and is a useful resource for computer engineers, agriculturalists, business owners, healthcare professionals, environmentalists, researchers, scientists, and academicians. Artificial intelligence Industrial applications Machine learning Industrial applications Smart cities Jeganathan, Joseph edt Moccia, Salvatore 1968- edt Rajest, S. Suman 1988- edt Regin, R 1985- edt Singh, Bhopendra 1974- edt Erscheint auch als Druck-Ausgabe 9798369386590 https://doi.org/10.4018/979-8-3693-8659-0 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Optimizing intelligent systems for cross-industry application Artificial intelligence Industrial applications Machine learning Industrial applications Smart cities |
| title | Optimizing intelligent systems for cross-industry application |
| title_auth | Optimizing intelligent systems for cross-industry application |
| title_exact_search | Optimizing intelligent systems for cross-industry application |
| title_full | Optimizing intelligent systems for cross-industry application S. Suman Rajest, Salvatore Moccia, Bhopendra Singh, R. Regin, Joseph Jeganathan, editors |
| title_fullStr | Optimizing intelligent systems for cross-industry application S. Suman Rajest, Salvatore Moccia, Bhopendra Singh, R. Regin, Joseph Jeganathan, editors |
| title_full_unstemmed | Optimizing intelligent systems for cross-industry application S. Suman Rajest, Salvatore Moccia, Bhopendra Singh, R. Regin, Joseph Jeganathan, editors |
| title_short | Optimizing intelligent systems for cross-industry application |
| title_sort | optimizing intelligent systems for cross industry application |
| topic | Artificial intelligence Industrial applications Machine learning Industrial applications Smart cities |
| topic_facet | Artificial intelligence Industrial applications Machine learning Industrial applications Smart cities |
| url | https://doi.org/10.4018/979-8-3693-8659-0 |
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