{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T09:13:26Z","timestamp":1772961206726,"version":"3.50.1"},"reference-count":47,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2024,4,15]],"date-time":"2024-04-15T00:00:00Z","timestamp":1713139200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100019286","name":"Ajman University, Ajman, UAE","doi-asserted-by":"publisher","award":["2023-IRG-ENIT-15"],"award-info":[{"award-number":["2023-IRG-ENIT-15"]}],"id":[{"id":"10.13039\/501100019286","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>The pressing need for sustainable development solutions necessitates innovative data-driven tools. Machine learning (ML) offers significant potential, but faces challenges in centralized approaches, particularly concerning data privacy and resource constraints in geographically dispersed settings. Federated learning (FL) emerges as a transformative paradigm for sustainable development by decentralizing ML training to edge devices. However, communication bottlenecks hinder its scalability and sustainability. This paper introduces an innovative FL framework that enhances communication efficiency. The proposed framework addresses the communication bottleneck by harnessing the power of the Lemurs optimizer (LO), a nature-inspired metaheuristic algorithm. Inspired by the cooperative foraging behavior of lemurs, the LO strategically selects the most relevant model updates for communication, significantly reducing communication overhead. The framework was rigorously evaluated on CIFAR-10, MNIST, rice leaf disease, and waste recycling plant datasets representing various areas of sustainable development. Experimental results demonstrate that the proposed framework reduces communication overhead by over 15% on average compared to baseline FL approaches, while maintaining high model accuracy. This breakthrough extends the applicability of FL to resource-constrained environments, paving the way for more scalable and sustainable solutions for real-world initiatives.<\/jats:p>","DOI":"10.3390\/a17040160","type":"journal-article","created":{"date-parts":[[2024,4,15]],"date-time":"2024-04-15T08:08:12Z","timestamp":1713168492000},"page":"160","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["A Communication-Efficient Federated Learning Framework for Sustainable Development Using Lemurs Optimizer"],"prefix":"10.3390","volume":"17","author":[{"given":"Mohammed Azmi","family":"Al-Betar","sequence":"first","affiliation":[{"name":"Artificial Intelligence Research Center (AIRC), College of Engineering and Information Technology, Ajman University, Ajman P.O. Box 346, United Arab Emirates"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0725-6167","authenticated-orcid":false,"given":"Ammar Kamal","family":"Abasi","sequence":"additional","affiliation":[{"name":"Department of Machine Learning, Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI), Abu Dhabi P.O. Box 131818, United Arab Emirates"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4228-9298","authenticated-orcid":false,"given":"Zaid Abdi Alkareem","family":"Alyasseri","sequence":"additional","affiliation":[{"name":"Information Technology Research and Development Center (ITRDC), University of Kufa, Najaf 54001, Iraq"},{"name":"College of Engineering, University of Warith Al-Anbiyaa, Karbala P.O. Box 56001, Iraq"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1025-7868","authenticated-orcid":false,"given":"Salam","family":"Fraihat","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Research Center (AIRC), College of Engineering and Information Technology, Ajman University, Ajman P.O. Box 346, United Arab Emirates"}]},{"given":"Raghad Falih","family":"Mohammed","sequence":"additional","affiliation":[{"name":"Department of Business Administration, College of Administrative and Financial Sciences, Imam Ja\u2019afar Al-Sadiq University, Baghdad P.O. Box 10011, Iraq"}]}],"member":"1968","published-online":{"date-parts":[[2024,4,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"140527","DOI":"10.1016\/j.jclepro.2023.140527","article-title":"Navigating the confluence of artificial intelligence and education for sustainable development in the era of industry 4.0: Challenges, opportunities, and ethical dimensions","volume":"437","author":"Abulibdeh","year":"2024","journal-title":"J. Clean. Prod."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Abasi, A.K., Makhadmeh, S.N., Alomari, O.A., Tubishat, M., and Mohammed, H.J. (2023). Enhancing Rice Leaf Disease Classification: A Customized Convolutional Neural Network Approach. Sustainability, 15.","DOI":"10.3390\/su152015039"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Malik, M., Sharma, S., Uddin, M., Chen, C.L., Wu, C.M., Soni, P., and Chaudhary, S. (2022). 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