| Title |
First Responder Drones for Critical Situation Management |
| ID_Doc |
43007 |
| Authors |
Lemayian, JP; Hamamreh, JM |
| Title |
First Responder Drones for Critical Situation Management |
| Year |
2019 |
| Published |
|
| DOI |
10.1109/asyu48272.2019.8946353 |
| Abstract |
The rapid exponential increase in current urban area population has brought about numerous problems. Different kinds of accidents caused by natural or artificial reasons are some of the leading challenges experienced in the overcrowded cities. This calls for the use of rapid response techniques to save lives in such emergency situations. These emergency responses need not only be intelligent, but also have the ability to adapt to individual environments so as to manage an emergency situation more effectively. An appropriate and effective response can only be delivered if accurate and sufficient information about the critical situation is obtained. This information can be promptly acquired using airborne sensory systems known as First Responder Drones (FRDs). This paper proposes a paradigm for deploying drones as first responders to a disaster or an accident scene. The system comprises of three important sections. The first is the sensory system, which comprises of alert sensors deployed on unique places such as streetlights and traffic cameras. The second part is the intelligent drones, which have the ability to autonomously take off and maneuver through obstacles. The final section is the control station, where the drones send live data from the critical environment. This system is implemented using LoRa with GPS capabilities and ESP32 modules. A detailed study of the system was performed, and the results show that the response time for FRDs is much shorter compared to the conventional response systems. Moreover, the data collected by the drones proved to be extra valuable when analyzing the critical situation. |
| Author Keywords |
Drones; UAV; Smart city; IoT; Wireless |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000631252400068 |
| WoS Category |
Computer Science, Artificial Intelligence; Computer Science, Hardware & Architecture; Computer Science, Information Systems |
| Research Area |
Computer Science |
| PDF |
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