This course is designed to introduce to you the world of current and future drones, as well as the design of a novel first response drone paradigm for
This paper proposes an autonomous first response drone-based (Auto-FRD) smart rescue system. Auto-FRD paradigm uses drones to provide quick response to critical situations in a smart city setting. The system comprises three main sections: sensor network, intelligent drones, & ...
Numerous problems have been experienced due to the current exponential rise in urban population. Such challenges include insecurity and disaster management. It is therefore critical that new and efficient ways of disaster management are realized. Drone technology has been used in many applications due to their flexibility and cost-effectiveness in executing tasks. Such applications include goods delivery, data collection, surveillance, and tracking. This paper proposes an autonomous first response drone-based (Auto-FRD) smart rescue system. Auto-FRD paradigm uses drones to provide quick response to critical situations in a smart city setting. The system comprises three main sections: sensor network, intelligent drones, and the command center. The Auto-FRD system is designed such that the drones automatically deploy to a specific location upon receiving an alert signal from the smart sensors, as opposed to people sending the signal. Moreover, the system is implemented using cheap LoRa technology. Experimental results show that the proposed system drastically reduces the response time compared to conventional critical situation response systems. Additionally, the data collected by the drones prove to be extra valuable when analyzing the critical situation.
Drones, UAV, Smart city, IoT, Wireless sensors, Emergency response, Disaster.
The codes used to implement the proposed system and generate the results in this article can be found at https://researcherstore.com/.
A quick, and short training course description the research conducted in this article can be found here.
J. P. LEMAYIAN, and J. M. Hamamreh are with WISLAB-TELENG for Wireless Research at the Department of Electrical-Electronics Engineering, Antalya Bilim University, Antalya, Turkey. (web: https://sites.google.com/view/wislab)
Corresponding author: Joel P. Lemayian (e-mail: firstname.lastname@example.org).
Part of this research has been presented at the 2019 ASYU conference.
JOEL P. LEMAYIAN received the B.Sc. degree in electrical and electronics engineering from Middle East Technical University Turkey, in 2017. He is presently pursuing the master’s (M.Sc.) degree in electrical and computer engineering. He is currently with Antalya Bilim University, Turkey. He has worked as a research assistant in both Middle East Technical University and Antalya Bilim University in IoT lab and Neuroscience lab respectively. He is an author of numerus journals, conference papers and book chapters. His research interests include UAVs, 5G Communication networks, Artificial Intelligence, Machine Learning, and the Internet of Things (IoT) applications.
JEHAD M. HAMAMREH received the B.Sc. degree in electrical and telecommunication engineering from An-Najah University, Nablus, in 2013, and the Ph.D. degree in electricalelectronics engineering and cyber systems from Istanbul Medipol University, Turkey, in 2018. He was a Researcher with the Department of Electrical and Computer Engineering, Texas A and M University at Qatar. He is currently an Assistant Professor with the Electrical and Electronics Engineering Department, Antalya International (Bilim) University, Turkey. His current research interests include wireless physical and MAC layers security, orthogonal frequency-division multiplexing multipleinput multiple-output systems, advanced waveforms design, multidimensional modulation techniques, IoT, 5G & 6G and orthogonal/nonorthogonal multiple access schemes for future wireless systems. He is a Regular Reviewer for various refereed journals as well as a TPC Member for several international conferences.
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