Unmanned aerial vehicles (UAVs), widely known as drones, are used in various domains for tasks including geological prospecting, e-commerce business, and emergencies. Because of the necessity for fast and efficient delivery for emergency medicine distribution, drones can play crucially important roles by their ability to pass through complex urban environments. Drones might therefore aid people living under strict lockdown conditions during surges cases of COVID-19 or other communicable diseases. Nevertheless, distribution routes are usually planned in two-dimensional space. Moreover, restricted areas in urban aerial domains might be overlooked because of complex environmental considerations. To boost the feasibility of drone use, three-dimensional (3D) path routing can be applied when planning aerial distribution routes for drones, such as those used for delivering emergency medicines. This study specifically examines a more reliable method of using heuristic algorithms and software ArcGIS. After collecting location data of chronic patients in lockdown areas from the Shanghai official information system database, 3D visualization of the terrain and complex airspace was done using ArcGIS. Secondly, UAV routing constraints are summarized according to current laws and regulations for UAV operation at low altitudes. Furthermore, feasible solutions are incorporated into this model. Finally, after improved ant colony optimization (ACO) application to 3D route planning problems, programming was done using MATLAB (ver. 2017b). Assuming guaranteed safety and compliance with regulations, the solutions demonstrate the algorithmic efficiency and provide a satisfactory route plan for emergency medicine delivery that might guide emergency delivery system routing design in similarly complex urban environments.
3D route planning emergency geographic information system heuristic algorithm medical emergency; unmanned aerial vehicle
Unmanned aerial vehicles (UAVs), widely known as drones, are used in various domains for tasks including geological prospecting, e-commerce business, and emergencies. Because of the necessity for fast and efficient delivery for emergency medicine distribution, drones can play crucially important roles by their ability to pass through complex urban environments. Drones might therefore aid people living under strict lockdown conditions during surges cases of COVID-19 or other communicable diseases. Nevertheless, distribution routes are usually planned in two-dimensional space. Moreover, restricted areas in urban aerial domains might be overlooked because of complex environmental considerations. To boost the feasibility of drone use, three-dimensional (3D) path routing can be applied when planning aerial distribution routes for drones, such as those used for delivering emergency medicines. This study specifically examines a more reliable method of using heuristic algorithms and software ArcGIS. After collecting location data of chronic patients in lockdown areas from the Shanghai official information system database, 3D visualization of the terrain and complex airspace was done using ArcGIS. Secondly, UAV routing constraints are summarized according to current laws and regulations for UAV operation at low altitudes. Furthermore, feasible solutions are incorporated into this model. Finally, after improved ant colony optimization (ACO) application to 3D route planning problems, programming was done using MATLAB (ver. 2017b). Assuming guaranteed safety and compliance with regulations, the solutions demonstrate the algorithmic efficiency and provide a satisfactory route plan for emergency medicine delivery that might guide emergency delivery system routing design in similarly complex urban environments.
emergency geographic information system heuristic algorithm 3D route planning unmanned aerial vehicle
Primary Language | English |
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Journal Section | Makaleler |
Authors | |
Early Pub Date | December 9, 2022 |
Publication Date | December 9, 2022 |
Acceptance Date | October 31, 2022 |
Published in Issue | Year 2022 Volume: 9 Issue: Special Issue 2nd International Symposium of Sustainable Logistics “Circular Economy” |