{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T13:45:58Z","timestamp":1784036758173,"version":"3.55.0"},"reference-count":47,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2020,5,6]],"date-time":"2020-05-06T00:00:00Z","timestamp":1588723200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Wireless Sensor Networks (WSNs) are key elements of Internet of Things (IoT) networks which provide sensing and wireless connectivity. Disaster management in smart cities is classified as a safety-critical application. Thus, it is important to ensure system availability by increasing the lifetime of WSNs. Clustering is one of the routing techniques that benefits energy efficiency in WSNs. This paper provides an evolutionary clustering and routing method which is capable of managing the energy consumption of nodes while considering the characteristics of a disaster area. The proposed method consists of two phases. First, we present a model with improved hybrid Particle Swarm Optimization (PSO) and Harmony Search Algorithm (HSA) for cluster head (CH) selection. Second, we design a PSO-based multi-hop routing system with enhanced tree encoding and a modified data packet format. The simulation results for disaster scenarios prove the efficiency of the proposed method in comparison with the state-of-the-art approaches in terms of the overall residual energy, number of live nodes, network coverage, and the packet delivery ratio.<\/jats:p>","DOI":"10.3390\/s20092647","type":"journal-article","created":{"date-parts":[[2020,5,7]],"date-time":"2020-05-07T03:10:38Z","timestamp":1588821038000},"page":"2647","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":45,"title":["An Energy-Efficient Evolutionary Clustering Technique for Disaster Management in IoT Networks"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1480-7820","authenticated-orcid":false,"given":"Morteza","family":"Biabani","sequence":"first","affiliation":[{"name":"School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran 14395-515, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5590-0784","authenticated-orcid":false,"given":"Hossein","family":"Fotouhi","sequence":"additional","affiliation":[{"name":"School of Innovation, Design and Engineering, M\u00e4lardalen University, 721 23 V\u00e4ster\u00e5s, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nasser","family":"Yazdani","sequence":"additional","affiliation":[{"name":"School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran 14395-515, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,5,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/j.comnet.2019.03.006","article-title":"Internet of Things: A survey of enabling technologies in healthcare and its applications","volume":"153","author":"Dhanvijay","year":"2019","journal-title":"Comput. 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