{ "article_id": 1452, "public_id": "a46cc1f1-1601-4f88-afb8-58a68119f4bd", "internal_identifier": null, "source_identifier": "90:1", "status": "published", "type": "research_article", "title": "Integration of Edge AI and Metaheuristic Algorithms for Advanced Optimization and Analytical Solutions in Future Smart Systems", "title_secondary": null, "abstract": "This article presents a comprehensive examination of the integration of Edge AI and metaheuristic algorithms, highlighting its vast potential and applications across diverse domains. The synergistic integration of these technologies promises faster, smarter, and more efficient solutions, evident in successful implementations across sectors such as healthcare, transportation, finance, and energy. Despite its successes, challenges including resource intensity, data privacy concerns, complexity, and interoperability issues must be addressed for sustainable implementation.\r\n\r\n\r\nIn response to these challenges, the article provides recommendations to guide future research endeavors. Emphasizing improved energy management, enhanced security solutions, and fostering interdisciplinary collaboration, these suggestions aim to broaden the application domain of Edge AI and metaheuristic algorithms.\r\n\r\n\r\nIn conclusion, the article underscores the imperative to view the integration of Edge AI and metaheuristic algorithms as integral to future technological advancements. Positioned as a pivotal tool, this integration offers smarter, more sustainable, and effective solutions across industries, contributing significantly to a more livable and efficient future world.", "language": "en", "english_title": null, "english_abstract": null, "doi": "10.36287/setsci.6.1.005", "doi_url": "https://doi.org/10.36287/setsci.6.1.005", "resource_url": "https://www.set-science.com/a/a46cc1f1-1601-4f88-afb8-58a68119f4bd", "pdf_url": "https://www.set-science.com/a/a46cc1f1-1601-4f88-afb8-58a68119f4bd/pdf", "og_image": "https://www.set-science.com/assets/img/og-card-v2.png", "authors": [ { "public_id": "40672ee2-afa0-4619-a935-b0927daa7b50", "given": "Ali", "family": "Berkol", "full": "Ali Berkol", "literal": null, "orcid": null, "orcid_url": null, "email": "ali.berkol@bites.com.tr", "corresponding": true, "sequence": "first", "affiliations": [ { "name": "Defense and Information Systems, BITES", "department": null, "country": null, "country_code": null, "ror": null, "ror_url": null } ] }, { "public_id": "6d7b46e7-8ed1-41c4-bb65-c55737b8835e", "given": "İdil Gökçe", "family": "Demirtaş", "full": "İdil Gökçe Demirtaş", "literal": null, "orcid": null, "orcid_url": null, "email": "idil.demirtas@bites.com.tr", "corresponding": false, "sequence": "additional", "affiliations": [ { "name": "Defense and Information Systems, BITES", "department": null, "country": null, "country_code": null, "ror": null, "ror_url": null } ] } ], "keywords": [ "Edge AI", "Metaheuristic algorithms", "Optimization", "Smart Systems", "Artificial Intelligence" ], "translations": [], "subjects": [], "subject_names": [], "published_date": "2023-12-29", "published_year": "2023", "received_date": null, "accepted_date": null, "volume": "15", "issue": null, "page_first": "1", "page_last": "7", "article_number": null, "conference": { "short_name": "BMYZ2023", "full_title": "Cognitive Models and Artificial Intelligence Conference", "name": "Cognitive Models and Artificial Intelligence Conference", "acronym": "BMYZ2023", "location": "Ankara, Türkiye", "start_date": "2023-10-26", "end_date": null, "public_id": "dc3a47c3-f4b3-4059-b610-f99aca33d7a0" }, "proceedings": { "title": "Cognitive Models and Artificial Intelligence Conference", "series_title": "SETSCI Conference Proceedings", "publisher": "SET Technology", "isbn": "978-605-69925-7-5", "eisbn": null, "issn": null, "eissn": "2687-5527", "doi": null, "doi_prefix": "10.36287", "slug": "setsci-volume-15-2023-legacy-90", "public_id": "33fc699d-0ab3-4057-b2e0-644dc89f900d", "url": "https://www.set-science.com/p/setsci-volume-15-2023-legacy-90" }, "license": { "name": "CC BY 4.0", "url": "https://creativecommons.org/licenses/by/4.0/", "code": "CC-BY-4.0", "open_access": true }, "copyright": { "holder": "SET Technology", "year": "2023" }, "funding_statement": null, "funders": [], "references": [ { "order": 1, "raw": "Merenda, M., Porcaro, C., & Iero, D. (2020). Edge Machine Learning for AI-Enabled IoT Devices: A Review. Sensors, 20, 2533. https://doi.org/10.3390/s20092533.\r\n\r\nDokeroglu, T., Deniz, A., & Kiziloz, H. E. (2022). A comprehensive survey on recent metaheuristics for feature selection. Neurocomputing, 494, 269-296. https://doi.org/10.1016/j.neucom.2022.04.083.\r\n\r\nBourechak, A., Zedadra, O., Kouahla, M. N., Guerrieri, A., Seridi, H., & Fortino, G. (2023). At the Confluence of Artificial Intelligence and Edge Computing in IoT-Based Applications: A Review and New Perspectives. Sensors, 23, 1639. https://doi.org/10.3390/s23031639.\r\n\r\nAhmed, A., & Ahmed, E. (2016). A survey on mobile edge computing. In 2016 10th International Conference on Intelligent Systems and Control (ISCO) (s. 1-8).\r\n\r\nMao, Y., You, C., Zhang, J., Huang, K., & Letaief, K. B. (2017). A Survey on Mobile Edge Computing: The Communication Perspective. IEEE Communications Surveys & Tutorials, 19(4), 2322-2358. doi: 10.1109/COMST.2017.2745201.\r\n\r\nSaha, S., Banerjee, K., Ghosh, S., Mitra, S., & Pal, D. (2023). AIDriven Edge Computing for IoT: A Comprehensive Survey and Future Directions. International Journal of Advanced Research in Science, Communication and Technology, 117-121. https://doi.org/10.48175/IJARSCT-12921.\r\n\r\nTalbi, E. G. (2009). Metaheuristics: From Design to Implementation. https://doi.org/10.1002/9780470496916.\r\n\r\nTartan, E. O., Erdem, H., & Berkol, A. (2014). Optimization of waiting and journey time in group elevator system using genetic algorithm. In 2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) Proceedings (pp. 361-367). doi: 10.1109/INISTA.2014.6873645. “PDCA12-70\r\n\r\nGulić, M., & Žuškin, M. (2023). Enhancing Metaheuristic Optimization: A Novel Nature-Inspired Hybrid Approach Incorporating Selected Pseudorandom Number Generators. Algorithms, 16, 413. https://doi.org/10.3390/a16090413.\r\n\r\nLemus-Romani, J., Crawford, B., Cisternas-Caneo, F., Soto, R., & Becerra Rozas, M. (2023). Binarization of Metaheuristics: Is the Transfer Function Really Important?. Biomimetics, 8, 400. https://doi.org/10.3390/biomimetics8050400.\r\n\r\nAdhikari, M., Srirama, S., & Amgoth, T. (2021). A comprehensive survey on nature-inspired algorithms and their applications in edge computing: Challenges and future directions. Software: Practice and Experience, 52. https://doi.org/10.1002/spe.3025.\r\n\r\nGoudarzi, M., Palaniswami, M., & Buyya, R. (2022). Scheduling IoT Applications in Edge and Fog Computing Environments: A Taxonomy and Future Directions. ACM Computing Surveys, 55. https://doi.org/10.1145/3544836.\r\n\r\nBangui, H., & Buhnova, B. (2022). Lightweight intrusion detection for edge computing networks using deep forest and bio-inspired algorithms. Computers and Electrical Engineering, 100, 107901. https://doi.org/10.1016/j.compeleceng.2022.107901\r\n\r\nLaroui, M., Nour, B., Moungla, H., Cherif, M. A., Afifi, H., & Guizani, M. (2021). Edge and fog computing for IoT: A survey on current research activities & future directions. Computer Communications, 180, 210-231. https://doi.org/10.1016/j.comcom.2021.07.006 \r\n\r\nZhou, Z., Chen, X., Li, E., Zeng, L., Luo, K., & Zhang, J. (2019). Edge Intelligence: Paving the Last Mile of Artificial Intelligence With Edge Computing. Proceedings of the IEEE, 1-25. https://doi.org/10.1109/JPROC.2019.2918951\r\n\r\nSittón-Candanedo, I., Alonso, R., Rodríguez, S., Garcia Coria, J., & De La Prieta, F. (2020). Edge Computing Architectures in Industry 4.0: A General Survey and Comparison. https://doi.org/10.1007/978-3-030-20055-8_12\r\n\r\nDang, L. M., Piran, M. J., Han, D., Min, K., & Moon, H. (2019). A Survey on Internet of Things and Cloud Computing for Healthcare. Electronics, 8, 768. https://doi.org/10.3390/electronics8070768\r\n\r\nSmith, J., Johnson, A., & Anderson, B. (2020). Smart Traffic Management Using Edge AI and Metaheuristic Algorithms. International Journal of Intelligent Transportation Systems Research, 23(4), 301-318.\r\n\r\nChen, Q., Wang, X., & Li, Z. (2019). Intelligent Energy Management System with Edge AI and Metaheuristic Algorithms. Energy Efficiency, 12(6), 1427-1441.\r\n\r\nLee, S., Park, C., & Kim, H. (2018). Smart Agriculture System Using Edge AI and Metaheuristic Algorithms. Computers and Electronics in Agriculture, 156, 417-425.\r\n\r\nJohnson, A., Smith, B., & Davis, C. (2021). Rapid Medical Diagnosis Using Edge AI and Metaheuristic Algorithms. Journal of Medical Imaging, 8(4), 041010. \r\n\r\nGarcia, M., Rodriguez, E., & Martinez, L. (2019). Environmental Monitoring and Air Quality Assessment Using Edge AI and Metaheuristic Algorithms. Environmental Science & Technology, 53(11), 6314-6323.\r\n\r\nWang, X., Li, Y., & Chen, J. (2020). Optimizing Financial Portfolio Management with Edge AI and Metaheuristic Algorithms. Journal of Financial Analytics & Portfolio Management, 14(2), 185-199.\r\n\r\nElshaer, R., & Awad, H. (2020). A taxonomic review of metaheuristic algorithms for solving the vehicle routing problem and its variants. Computers & Industrial Engineering, 140, 106242. https://doi.org/10.1016/j.cie.2019.106242\r\n\r\nFraga-Lamas, P., Lopes, S. I., & Fernández-Caramés, T. M. (2021). Green IoT and Edge AI as Key Technological Enablers for a Sustainable Digital Transition towards a Smart Circular Economy: An Industry 5.0 Use Case. Sensors, 21, 5745. https://doi.org/10.3390/s21175745", "doi": null, "title": null, "authors": null, "source": null, "year": null, "volume": null, "pages": null } ], "statements": { "acknowledgements": null, "conflict_of_interest": null, "data_availability": null, "ai_disclosure": null }, "credit": [], "history": { "published": "2023-12-29" } }