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dc.contributor.authorAmiri, Zahra
dc.contributor.authorHeidari, Arash
dc.contributor.authorZavvar, Mohammad
dc.contributor.authorNavimipour, Nima Jafari
dc.contributor.authorEsmaeilpour, Mansour
dc.date.accessioned2024-09-04T11:50:54Z
dc.date.available2024-09-04T11:50:54Z
dc.date.issued2024en_US
dc.identifier.citationAmiri, Z., Heidari, A., Zavvar, M., Navimipour, N. J., & Esmaeilpour, M. (2024). The applications of nature‐inspired algorithms in Internet of Things‐based healthcare service: A systematic literature review. Transactions on Emerging Telecommunications Technologies, 35(6). https://doi.org/10.1002/ett.4969en_US
dc.identifier.issn2161-3915
dc.identifier.urihttps://hdl.handle.net/20.500.12900/389
dc.description.abstractNature-inspired algorithms revolve around the intersection of nature-inspired algorithms and the IoT within the healthcare domain. This domain addresses the emerging trends and potential synergies between nature-inspired computational approaches and IoT technologies for advancing healthcare services. Our research aims to fill gaps in addressing algorithmic integration challenges, real-world implementation issues, and the efficacy of nature-inspired algorithms in IoT-based healthcare. We provide insights into the practical aspects and limitations of such applications through a systematic literature review. Specifically, we address the need for a comprehensive understanding of the applications of nature-inspired algorithms in IoT-based healthcare, identifying gaps such as the lack of standardized evaluation metrics and studies on integration challenges and security considerations. By bridging these gaps, our paper offers insights and directions for future research in this domain, exploring the diverse landscape of nature-inspired algorithms in healthcare. Our chosen methodology is a Systematic Literature Review (SLR) to investigate related papers rigorously. Categorizing these algorithms into groups such as genetic algorithms, particle swarm optimization, cuckoo algorithms, ant colony optimization, other approaches, and hybrid methods, we employ meticulous classification based on critical criteria. MATLAB emerges as the predominant programming language, constituting 37.9% of cases, showcasing a prevalent choice among researchers. Our evaluation emphasizes adaptability as the paramount parameter, accounting for 18.4% of considerations. By shedding light on attributes, limitations, and potential directions for future research and development, this review aims to contribute to a comprehensive understanding of nature-inspired algorithms in the dynamic landscape of IoT-based healthcare services. Providing a complete overview of the current issues associated with nature-inspired algorithms in IoT-based healthcare services. Providing a thorough overview of present methodologies for IoT-based healthcare services in research studies; Evaluating each region that tailored nature-inspired algorithms with many perspectives such as advantages, restrictions, datasets, security involvement, and simulation stings; Outlining the critical aspects that motivate the cited approaches to enhance future research; Illustrating descriptions of certain IoT-based healthcare services used in various studies. imageen_US
dc.language.isoengen_US
dc.publisherWILEYen_US
dc.relation.isversionof10.1002/ett.4969en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectOptimizationen_US
dc.subjectFrameworken_US
dc.titleThe applications of nature-inspired algorithms in Internet of Things-based healthcare service: A systematic literature reviewen_US
dc.typearticleen_US
dc.departmentİstanbul Atlas Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.authoridhttps://orcid.org/0000-0003-4279-8551en_US
dc.contributor.institutionauthorHeidari, Arash
dc.identifier.volume35en_US
dc.identifier.issue6en_US
dc.relation.journalTRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIESen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


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