Smart Ambulance: Mobile Solutions for Emergency Booking and Real-Time Tracking
In emergencies, vehicles play a crucial role in managing critical situations, and ambulances are essential assets for mitigating the risk of worsening conditions. Given their importance, effective ambulance booking mechanisms are vital. Efficiency in ambulance booking can be improved through real-time tracking of ambulances by both requesters and hospitals. This research aims to develop a booking application system to assist patients in emergencies and aid medical personnel in managing emergency service requests. The iterative incremental method is a methodology that combines elements of the waterfall method in an iterative approach. The system is created using this approach, starting with data collection and analysis to understand business processes and define system requirements, followed by system development based on these insights. The result is a mobile-based ambulance booking and tracking application with two types of users: requesters and drivers. Requesters have features for registration, login, booking an ambulance, tracking its location, viewing available ambulances and their details, checking booking history, managing profiles, and updating information. Drivers have access to features such as login, a dashboard with booking information assigned to them, and tracking of patient pickup locations. The testing results using System Usability Scale indicate that from the three testing respondents, the system received an overall grade of A with an average score of 88.3. This application aims to enhance the quality of emergency medical services and save lives by improving response times.
Authors
- Edi Triono Nuryatno (ORCID: https://orcid.org/0000-0002-8815-1764)
- M. Fahmi
- Sinung Suakanto (ORCID: https://orcid.org/0000-0001-8071-4473)
- Ilham Perdana
Institutions
- The University of Western Australia (AU)
- Telkom University (ID)
Publication Details
- Published
- 2024-12-17
- DOI
- https://doi.org/10.1109/icicyta64807.2024.10913033
- Citations
- 4
- Primary Topic
- IoT and GPS-based Vehicle Safety Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.85