{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,8]],"date-time":"2026-02-08T06:27:59Z","timestamp":1770532079389,"version":"3.49.0"},"reference-count":48,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2023,11,1]],"date-time":"2023-11-01T00:00:00Z","timestamp":1698796800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Recently, the precise location of sensor nodes has emerged as a significant challenge in the realm of Internet of Things (IoT) applications, including Wireless Sensor Networks (WSNs). The accurate determination of geographical coordinates for detected events holds pivotal importance in these applications. Despite DV-Hop gaining popularity due to its cost-effectiveness, feasibility, and lack of additional hardware requirements, it remains hindered by a relatively notable localization error. To overcome this limitation, our study introduces three new localization approaches that combine DV-Hop with Chicken Swarm Optimization (CSO). The primary objective is to improve the precision of DV-Hop-based approaches. In this paper, we compare the efficiency of the proposed localization algorithms with other existing approaches, including several algorithms based on Particle Swarm Optimization (PSO), while considering random network topologies. The simulation results validate the efficiency of our proposed algorithms. The proposed HW-DV-HopCSO algorithm achieves a considerable improvement in positioning accuracy compared to those of existing models.<\/jats:p>","DOI":"10.3390\/info14110592","type":"journal-article","created":{"date-parts":[[2023,11,1]],"date-time":"2023-11-01T03:29:33Z","timestamp":1698809373000},"page":"592","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Range-Free Localization Approaches Based on Intelligent Swarm Optimization for Internet of Things"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2626-738X","authenticated-orcid":false,"given":"Abdelali","family":"Hadir","sequence":"first","affiliation":[{"name":"National School of Commerce and Management, Hassan II University, Casablanca 20250, Morocco"}]},{"given":"Naima","family":"Kaabouch","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering and Computer Science, University of North Dakota, Grand Forks, ND 58202, USA"}]},{"given":"Mohammed-Alamine","family":"El Houssaini","sequence":"additional","affiliation":[{"name":"Higher School of Education and Training, Chouaib Doukkali University, El Jadida 24000, Morocco"}]},{"given":"Jamal","family":"El Kafi","sequence":"additional","affiliation":[{"name":"Faculty of Sciences, Chouaib Doukkali University, El Jadida 24000, Morocco"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3889","DOI":"10.1007\/s11277-021-09116-5","article-title":"Hardware, software platforms, operating systems and routing protocols for Internet of Things applications","volume":"122","author":"Zrelli","year":"2022","journal-title":"Wirel. 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