3D spatial evolutionary particle swarm algorithm based emergency communication spatial deployment optimization
Building emergency communication in disaster areas is a key problem that emergency response needs to solve. Ad hoc Network (ANET) can quickly establish communication networks when public communication infrastructure is disrupted. At present, ground emergency communication deployment based on ANET us...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-03-01
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| Series: | Geo-spatial Information Science |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/10095020.2025.2472006 |
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| author | Yumin Chen Xicheng Tan Jinguang Jiang Xiaoliang Meng Zeenat Khadim Hussain Jianguang Tu Huaming Wang You Wan Zongyao Sha |
| author_facet | Yumin Chen Xicheng Tan Jinguang Jiang Xiaoliang Meng Zeenat Khadim Hussain Jianguang Tu Huaming Wang You Wan Zongyao Sha |
| author_sort | Yumin Chen |
| collection | DOAJ |
| description | Building emergency communication in disaster areas is a key problem that emergency response needs to solve. Ad hoc Network (ANET) can quickly establish communication networks when public communication infrastructure is disrupted. At present, ground emergency communication deployment based on ANET usually relies on the operator’s experience, which struggles to ensure high-quality deployment in complex urban environments. This paper proposes an ANET nodes spatial optimization deployment algorithm based on 3D Spatial Evolutionary Particle Swarm Optimization (3DSEPSO). A wireless communication transmission rate model that depends on surface buildings and trees is constructed using ground truth communication data. The algorithm incorporates a fitness evaluation model, particle chromosome structure, and an evolutionary mechanism to intelligently deploy ANET nodes. By considering the spatial distribution of buildings and trees, the algorithm can achieve optimal data transmission quality by using a given number of ANET nodes. Experimental results demonstrate that the proposed algorithm significantly outperforms empirical approaches and traditional methods in terms of data transmission rates and quality. Thus, the algorithm provides better support for emergency rescue teams by facilitating more effective and reliable emergency communication. |
| format | Article |
| id | doaj-art-0647a7ec4e7b46689b3f20802e10890d |
| institution | DOAJ |
| issn | 1009-5020 1993-5153 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Geo-spatial Information Science |
| spelling | doaj-art-0647a7ec4e7b46689b3f20802e10890d2025-08-20T03:12:19ZengTaylor & Francis GroupGeo-spatial Information Science1009-50201993-51532025-03-0111810.1080/10095020.2025.24720063D spatial evolutionary particle swarm algorithm based emergency communication spatial deployment optimizationYumin Chen0Xicheng Tan1Jinguang Jiang2Xiaoliang Meng3Zeenat Khadim Hussain4Jianguang Tu5Huaming Wang6You Wan7Zongyao Sha8School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan, ChinaGNSS Research Center, Wuhan University, Wuhan, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan, ChinaSchool of Resource and Environmental Sciences, Wuhan University, Wuhan, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan, ChinaBuilding emergency communication in disaster areas is a key problem that emergency response needs to solve. Ad hoc Network (ANET) can quickly establish communication networks when public communication infrastructure is disrupted. At present, ground emergency communication deployment based on ANET usually relies on the operator’s experience, which struggles to ensure high-quality deployment in complex urban environments. This paper proposes an ANET nodes spatial optimization deployment algorithm based on 3D Spatial Evolutionary Particle Swarm Optimization (3DSEPSO). A wireless communication transmission rate model that depends on surface buildings and trees is constructed using ground truth communication data. The algorithm incorporates a fitness evaluation model, particle chromosome structure, and an evolutionary mechanism to intelligently deploy ANET nodes. By considering the spatial distribution of buildings and trees, the algorithm can achieve optimal data transmission quality by using a given number of ANET nodes. Experimental results demonstrate that the proposed algorithm significantly outperforms empirical approaches and traditional methods in terms of data transmission rates and quality. Thus, the algorithm provides better support for emergency rescue teams by facilitating more effective and reliable emergency communication.https://www.tandfonline.com/doi/10.1080/10095020.2025.2472006Evolutionary intelligencespatial optimizationParticle Swarm Optimization (PSO)Ad hoc Network (ANET)disaster emergency response |
| spellingShingle | Yumin Chen Xicheng Tan Jinguang Jiang Xiaoliang Meng Zeenat Khadim Hussain Jianguang Tu Huaming Wang You Wan Zongyao Sha 3D spatial evolutionary particle swarm algorithm based emergency communication spatial deployment optimization Geo-spatial Information Science Evolutionary intelligence spatial optimization Particle Swarm Optimization (PSO) Ad hoc Network (ANET) disaster emergency response |
| title | 3D spatial evolutionary particle swarm algorithm based emergency communication spatial deployment optimization |
| title_full | 3D spatial evolutionary particle swarm algorithm based emergency communication spatial deployment optimization |
| title_fullStr | 3D spatial evolutionary particle swarm algorithm based emergency communication spatial deployment optimization |
| title_full_unstemmed | 3D spatial evolutionary particle swarm algorithm based emergency communication spatial deployment optimization |
| title_short | 3D spatial evolutionary particle swarm algorithm based emergency communication spatial deployment optimization |
| title_sort | 3d spatial evolutionary particle swarm algorithm based emergency communication spatial deployment optimization |
| topic | Evolutionary intelligence spatial optimization Particle Swarm Optimization (PSO) Ad hoc Network (ANET) disaster emergency response |
| url | https://www.tandfonline.com/doi/10.1080/10095020.2025.2472006 |
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