Arquitectura tecnológica para la asignación de ambulancias en ciudades inteligentes

Abstract

The ambulances assignment to attend patients involved in accidents is one of the biggest problems in many third-world countries. It is a problem due mainly to two factors: mobility and limited resource availability. Traditionally, the problem is addressed by requesting the patient assistance by using radio broadcasting to all ambulance operators. The problem is that some notified ambulances may not be close to the accident, others could be on duty, on their way to attend other accidents, or not available. Nonetheless, it has also been notices that broadcasting generates competition among ambulances, or even lack of assistance to patients when many operators decide to attend the same accident. Furthermore, the competition to assist, has sometime generated new accidents. In other cases, negative impacts have been seen from the economic, ethic, social, politic, and mobility perspectives. Because of this situation, A Technological Architecture for the Assignment of Ambulances in Smart Cities was designed. Additionally, an intuitive and easy-to-use functional prototype was developed, applying the Design Thinking methodology. It is a proposal that puts technology at the service of community and aims to improve citizen quality of life, as proposed in the smart city manifest. This proposal was made under the cloud computational paradigm, which deploy the front-end of a mobile application for medical emergency real-time notifications. Additionally, the back-end manages the business logic to assign ambulances in a intelligent way and taking into account availability and georeferencing. The application was made possible by using technologies such as React JS, React Native, Firebase, Realtime Database, Cloud Functions, Google Maps, and Directions API. The software architecture is completely functional, scalable, and adequate. It has a TRL 4 maturity level, and complies with Jakob Nielsen’s 10 usability principles, giving a solution to the outlined needs. Tests was focused on Emergency logging and ambulance assignment, and in 98% of the cases, the prototype chose the nearest ambulance, the response was lower than 2 seconds, and the system behaved according to the necessary events to give solution to the problem.