dc.contributor.author | Luo, C | |
dc.contributor.author | Nightingale, J | |
dc.contributor.author | Asemota, E | |
dc.contributor.author | Grecos, C | |
dc.date.accessioned | 2016-04-18T09:10:21Z | |
dc.date.issued | 2015-05-11 | |
dc.description.abstract | The application of small civilian unmanned aerial vehicles (UAVs) has attracted great interest for disaster sensing. However, the limited computational capability and low energy resource of UAVs present a significant challenge to real-time data processing, networking and policy making, which are of vital importance to many disaster related applications such as oil-spill detection and flooding. In order to address the challenges imposed by the sheer volume of captured data, particularly video data, the intermittent and limited network resources, and the limited resources on UAVs, a new cloud-supported UAV application framework has been proposed and a prototype system of such framework has been implemented in this paper. The framework integrates video acquisition, data scheduling, data offloading and processing, and network state measurement to deliver an efficient and scalable system. The prototype of the framework comprises of a client-side set of components hosted on the UAV which selectively offloads the captured data to a cloud-based server. The server provides real-time data processing and information feedback services to the incident control centre and client device/operator. Results of the prototype system are presented to demonstrate the feasibility of such framework. | en_GB |
dc.description.sponsorship | This research is sponsored by the RCUK Digital Economy Theme Sustainable Society Network+ and Royal Society-NSFC Grant No. IE131036. | en_GB |
dc.identifier.citation | 2015 IEEE 81st Vehicular Technology Conference (VTC Spring), 11-14 May 2015, Glasgow | en_GB |
dc.identifier.doi | 10.1109/VTCSpring.2015.7145656 | |
dc.identifier.uri | http://hdl.handle.net/10871/21132 | |
dc.language.iso | en | en_GB |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_GB |
dc.rights | Copyright © 2015 IEEE | en_GB |
dc.subject | autonomous aerial vehicles | en_GB |
dc.subject | cloud computing | en_GB |
dc.subject | video signal processing | en_GB |
dc.title | A UAV-Cloud System for Disaster SensingApplications | en_GB |
dc.type | Conference paper | en_GB |
dc.date.available | 2016-04-18T09:10:21Z | |