Multi-constraint smart UAV healthcare transportation path using imperial competition algorithm for smart cities
Abstract In response to the path planning problem of using Unmanned Aerial Vehicle (UAV) for blood transportation, with the objective of minimizing the total distance travelled by the UAV, a multi-constraint drone blood transportation path planning model is established. Taking into account the limit...
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| Format: | Article |
| Language: | English |
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Springer
2025-05-01
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| Series: | Discover Internet of Things |
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| Online Access: | https://doi.org/10.1007/s43926-025-00151-3 |
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| author | Haewon Byeon Janjhyam Venkata Naga Ramesh Azzah AlGhamdi Mukesh Soni Divya Nimma Sridevi Pothumarthi Mohammad Shabaz |
| author_facet | Haewon Byeon Janjhyam Venkata Naga Ramesh Azzah AlGhamdi Mukesh Soni Divya Nimma Sridevi Pothumarthi Mohammad Shabaz |
| author_sort | Haewon Byeon |
| collection | DOAJ |
| description | Abstract In response to the path planning problem of using Unmanned Aerial Vehicle (UAV) for blood transportation, with the objective of minimizing the total distance travelled by the UAV, a multi-constraint drone blood transportation path planning model is established. Taking into account the limited number of drone take-off and landing platforms and the safety time intervals for continuous drone take-off and landing, a drone take-off scheduling strategy is designed to reduce the total time spent by UAV completing transportation tasks. Additionally, an Imperial Competition Algorithm based on Imperialist Competitive Algorithm is proposed to solve this problem. This algorithm introduces a sine disturbance strategy and adds Imperial Reform stages to improve the search accuracy of the algorithm. It utilizes acceptance criteria related to solution quality to maintain the diversity of the population. Validation is conducted using benchmark examples and instances of drone blood transportation. The results indicate that the proposed algorithm can provide transportation solutions for drone blood transportation tasks that meet various constraints without any conflicts in drone take-off and landing. The drone take-off scheduling strategy effectively reduces the total time spent by UAV in completing tasks. |
| format | Article |
| id | doaj-art-62326702edea4e30adf9b6e9cbc2a1b5 |
| institution | OA Journals |
| issn | 2730-7239 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Internet of Things |
| spelling | doaj-art-62326702edea4e30adf9b6e9cbc2a1b52025-08-20T02:33:32ZengSpringerDiscover Internet of Things2730-72392025-05-015111910.1007/s43926-025-00151-3Multi-constraint smart UAV healthcare transportation path using imperial competition algorithm for smart citiesHaewon Byeon0Janjhyam Venkata Naga Ramesh1Azzah AlGhamdi2Mukesh Soni3Divya Nimma4Sridevi Pothumarthi5Mohammad Shabaz6Convergence Department, Korea University of Technology and EducationDepartment of CSE, Graphic Era Hill UniversityComputer Information Systems Department, College of Computer Science and Information Technology, Imam Abdalrhman Bin Faisal UniversityDr. D. Y. Patil Vidyapeeth, Pune, Dr. D. Y. Patil School of Science & TechnologyUniversity of southern Mississippi, Data Analyst in UMMCDepartment of Computer Science and Engineering, Koneru Lakshmaiah Education FoundationModel Institute of Engineering and TechnologyAbstract In response to the path planning problem of using Unmanned Aerial Vehicle (UAV) for blood transportation, with the objective of minimizing the total distance travelled by the UAV, a multi-constraint drone blood transportation path planning model is established. Taking into account the limited number of drone take-off and landing platforms and the safety time intervals for continuous drone take-off and landing, a drone take-off scheduling strategy is designed to reduce the total time spent by UAV completing transportation tasks. Additionally, an Imperial Competition Algorithm based on Imperialist Competitive Algorithm is proposed to solve this problem. This algorithm introduces a sine disturbance strategy and adds Imperial Reform stages to improve the search accuracy of the algorithm. It utilizes acceptance criteria related to solution quality to maintain the diversity of the population. Validation is conducted using benchmark examples and instances of drone blood transportation. The results indicate that the proposed algorithm can provide transportation solutions for drone blood transportation tasks that meet various constraints without any conflicts in drone take-off and landing. The drone take-off scheduling strategy effectively reduces the total time spent by UAV in completing tasks.https://doi.org/10.1007/s43926-025-00151-3UAVHealthcare transportationImperial competition algorithmBlood transportationPath planning model |
| spellingShingle | Haewon Byeon Janjhyam Venkata Naga Ramesh Azzah AlGhamdi Mukesh Soni Divya Nimma Sridevi Pothumarthi Mohammad Shabaz Multi-constraint smart UAV healthcare transportation path using imperial competition algorithm for smart cities Discover Internet of Things UAV Healthcare transportation Imperial competition algorithm Blood transportation Path planning model |
| title | Multi-constraint smart UAV healthcare transportation path using imperial competition algorithm for smart cities |
| title_full | Multi-constraint smart UAV healthcare transportation path using imperial competition algorithm for smart cities |
| title_fullStr | Multi-constraint smart UAV healthcare transportation path using imperial competition algorithm for smart cities |
| title_full_unstemmed | Multi-constraint smart UAV healthcare transportation path using imperial competition algorithm for smart cities |
| title_short | Multi-constraint smart UAV healthcare transportation path using imperial competition algorithm for smart cities |
| title_sort | multi constraint smart uav healthcare transportation path using imperial competition algorithm for smart cities |
| topic | UAV Healthcare transportation Imperial competition algorithm Blood transportation Path planning model |
| url | https://doi.org/10.1007/s43926-025-00151-3 |
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