Ambulance route optimization in a mobile ambulance dispatch system using deep neural network (DNN)
Abstract The ambulance dispatch system plays a crucial role in emergency medical care by ensuring efficient communication, reducing response times, and ultimately saving lives. Delays in ambulance arrival can have serious consequences for patient health and survival. To enhance emergency preparednes...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-04-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-95048-0 |
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| author | C. Selvan Basha H. Anwar Soumyalatha Naveen Shaik Thasleem Bhanu |
| author_facet | C. Selvan Basha H. Anwar Soumyalatha Naveen Shaik Thasleem Bhanu |
| author_sort | C. Selvan |
| collection | DOAJ |
| description | Abstract The ambulance dispatch system plays a crucial role in emergency medical care by ensuring efficient communication, reducing response times, and ultimately saving lives. Delays in ambulance arrival can have serious consequences for patient health and survival. To enhance emergency preparedness, decision trees are used to analyze historical data and predict ambulance demand in specific locations over time. This helps in planning the necessary number of ambulances in advance. In situations where ambulance resources are limited, a support vector machine (SVM) evaluates patient data to optimize the distribution of available ambulances, ensuring that the most critical patients receive timely medical attention. For real-time route optimization, a convolutional neural network (CNN)-based deep learning model is used to adjust ambulance routes based on current traffic and road conditions, achieving an accuracy of 99.15%. By improving dispatch efficiency and communication, the proposed machine learning-based ambulance system reduces the burden on emergency services, enhancing overall effectiveness, particularly during peak demand periods. |
| format | Article |
| id | doaj-art-9f1d0488753a4b87a3c9d72b254366da |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-9f1d0488753a4b87a3c9d72b254366da2025-08-20T03:13:55ZengNature PortfolioScientific Reports2045-23222025-04-0115111210.1038/s41598-025-95048-0Ambulance route optimization in a mobile ambulance dispatch system using deep neural network (DNN)C. Selvan0Basha H. Anwar1Soumyalatha Naveen2Shaik Thasleem Bhanu3School of Computer Science and Engineering, REVA UniversityDepartment of Computer Science and Engineering, Rajalakshmi Institute of TechnologyDepartment of Computer Science and Engineering, Manipal Institute of Technology Bengaluru, Manipal Academy of Higher EducationDepartment of Electronics and Communications Engineering, Rajalakshmi Engineering CollegeAbstract The ambulance dispatch system plays a crucial role in emergency medical care by ensuring efficient communication, reducing response times, and ultimately saving lives. Delays in ambulance arrival can have serious consequences for patient health and survival. To enhance emergency preparedness, decision trees are used to analyze historical data and predict ambulance demand in specific locations over time. This helps in planning the necessary number of ambulances in advance. In situations where ambulance resources are limited, a support vector machine (SVM) evaluates patient data to optimize the distribution of available ambulances, ensuring that the most critical patients receive timely medical attention. For real-time route optimization, a convolutional neural network (CNN)-based deep learning model is used to adjust ambulance routes based on current traffic and road conditions, achieving an accuracy of 99.15%. By improving dispatch efficiency and communication, the proposed machine learning-based ambulance system reduces the burden on emergency services, enhancing overall effectiveness, particularly during peak demand periods.https://doi.org/10.1038/s41598-025-95048-0 |
| spellingShingle | C. Selvan Basha H. Anwar Soumyalatha Naveen Shaik Thasleem Bhanu Ambulance route optimization in a mobile ambulance dispatch system using deep neural network (DNN) Scientific Reports |
| title | Ambulance route optimization in a mobile ambulance dispatch system using deep neural network (DNN) |
| title_full | Ambulance route optimization in a mobile ambulance dispatch system using deep neural network (DNN) |
| title_fullStr | Ambulance route optimization in a mobile ambulance dispatch system using deep neural network (DNN) |
| title_full_unstemmed | Ambulance route optimization in a mobile ambulance dispatch system using deep neural network (DNN) |
| title_short | Ambulance route optimization in a mobile ambulance dispatch system using deep neural network (DNN) |
| title_sort | ambulance route optimization in a mobile ambulance dispatch system using deep neural network dnn |
| url | https://doi.org/10.1038/s41598-025-95048-0 |
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