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Artificial intelligence-driven ensemble deep learning models for smart monitoring of indoor activities in IoT environment for people with disabilities.

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第一作者： Munya A,Arasi

第一单位： Department of Computer Science, Applied College at RijalAlmaa, King Khalid University, Abha, Saudi Arabia. marasi@kku.edu.sa.

作者： Munya A,Arasi ^[1] ; Hussah Nasser,AlEisa ^[2] ; Amani A,Alneil ^[3] ; Radwa,Marzouk ^[4]

作者单位： Department of Computer Science, Applied College at RijalAlmaa, King Khalid University, Abha, Saudi Arabia. marasi@kku.edu.sa. ^[1] Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia. ^[2] Department of Computer and Self Development, Preparatory Year Deanship, Prince Sattam bin Abdulaziz University, AlKharj, Saudi Arabia.;King Salman Center for Disability Research, 11614, Riyadh, Saudi Arabia. ^[3] Department of Mathematics, Faculty of Science, Cairo University, Giza, 12613, Egypt. ^[4]

关键词 Disabled persons Ensemble models Improved coati optimization algorithm Indoor activity detection Internet of Things

医学主题词人类(Humans);人工智能(Artificial Intelligence);算法(Algorithms)

DOI 10.1038/s41598-025-88450-1

PMID 39910242

发布时间 2026-05-26

基金项目

KSRG-2024- 426/King Salman Center for Disability Research

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