دورية أكاديمية
Edge Computing and AI: Advancements in Industry 5.0- An Experimental Assessment
العنوان: | Edge Computing and AI: Advancements in Industry 5.0- An Experimental Assessment |
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المؤلفون: | Dmitrieva Ekaterina, Thakur Gaurav, Kumar Prabhakar Pranav, Prakash Anshika, Vyas Anjali, Prasanna Y. Lakshmi |
المصدر: | BIO Web of Conferences, Vol 86, p 01096 (2024) |
بيانات النشر: | EDP Sciences, 2024. |
سنة النشر: | 2024 |
المجموعة: | LCC:Microbiology LCC:Physiology LCC:Zoology |
مصطلحات موضوعية: | industrial performance, edge computing, artificial intelligence, industry 5.0, experimental assessment, Microbiology, QR1-502, Physiology, QP1-981, Zoology, QL1-991 |
الوصف: | This empirical research evaluated, via experimentation, how Edge Computing and Artificial Intelligence (AI) work together in the context of Industry 5.0. With a high satisfaction rating of 88%, participants in the Edge Computing condition saw an astonishing 18% decrease in task completion times. Similarly, in the AI integration scenario, participants rated AI's value at 86%, and they saw a significant 12% reduction in task completion times and a noteworthy 7% drop in mistake rates. Significantly, with an astounding 21% gain in work completion times, the Edge Computing and AI combo had the largest performance boost. These results highlight how Edge Computing and AI may dramatically improve industrial efficiency and performance in the context of Industry 5.0, providing insightful information for businesses looking to use these technologies to streamline processes and spur innovation. |
نوع الوثيقة: | article |
وصف الملف: | electronic resource |
اللغة: | English French |
تدمد: | 2117-4458 20248601 |
Relation: | https://www.bio-conferences.org/articles/bioconf/pdf/2024/05/bioconf_rtbs2024_01096.pdf; https://doaj.org/toc/2117-4458 |
DOI: | 10.1051/bioconf/20248601096 |
URL الوصول: | https://doaj.org/article/73a1f20f20784421881842a2d21a5871 |
رقم الأكسشن: | edsdoj.73a1f20f20784421881842a2d21a5871 |
قاعدة البيانات: | Directory of Open Access Journals |
تدمد: | 21174458 20248601 |
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DOI: | 10.1051/bioconf/20248601096 |