| Title |
An Optimization Approach for Emergency Vehicles Dispatching and Traffic Lights Adjustments in Response to Emergencies in Smart Cities |
| ID_Doc |
44352 |
| Authors |
Rangel, EO; Costa, DG; Peixoto, MML |
| Title |
An Optimization Approach for Emergency Vehicles Dispatching and Traffic Lights Adjustments in Response to Emergencies in Smart Cities |
| Year |
2021 |
| Published |
|
| DOI |
10.1109/SBESC53686.2021.9628243 |
| Abstract |
The adoption of sensors-based monitoring approaches has opened up a range of possibilities for data recovery, distributed processing, and quality evaluations in urban scenarios. In this evolving scenario, efficient emergency management systems provides a fundamental service for modern cities, exploiting different sensing and processing technologies for the real-time handling of critical situations. Actually, such systems are expected to implement emergency detection, alerting and mitigation services in order to avoid or relieve the negative impacts of critical events on the inhabitants' perceived quality of life. In this sense, after a critical event is properly detected, emergency vehicles may be dispatched as quickly as possible to respond to such detected situations, potentially reducing the probability of deaths and injuries. Therefore, this paper proposes a selection algorithm to dispatch emergency vehicles in smart cities, assuming that emergency alerts are dynamically released exploiting any support system. Then, dispatched vehicles are prioritized as they move on a city, by optimizing the operation of traffic lights. Such an optimization approach is implemented and evaluated using different simulation tools and programming libraries, providing important contributions to emergency management in smart cities. |
| Author Keywords |
Emergency Vehicles; Emergency Management Systems; IoT; Smart City; Traffic lights |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000853885000005 |
| WoS Category |
Computer Science, Theory & Methods |
| Research Area |
Computer Science |
| PDF |
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