Please use this identifier to cite or link to this item: https://idr.l2.nitk.ac.in/jspui/handle/123456789/14585
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dc.contributor.authorShahzad Alam M.
dc.contributor.authorGupta S.K.
dc.date.accessioned2021-05-05T09:23:30Z-
dc.date.available2021-05-05T09:23:30Z-
dc.date.issued2020
dc.identifier.citationLecture Notes in Civil Engineering , Vol. 51 , , p. 289 - 299en_US
dc.identifier.uri10.1007/978-3-030-37393-1_25
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/14585-
dc.description.abstractNowadays there is an emerging need for surveillance in order to maintain the public places more secure and ensure the safety and security of the people. Many government agencies require some autonomous system for surveillance of the large areas which can give them precise and real-time information like number of vehicles, people, and other objects. An aerial surveillance system will be very effective in this scenario and platform like Unmanned Aerial vehicle (UAV) will be very reliable and cost-effective option for this task. To make the system fully autonomous, we require real-time object detection that is computationally complex and time consuming due to the heavy load on the limited processing and payload capacity of low-cost UAV. In this paper, we propose a cost-effective approach for aerial surveillance in which we move the heavy computation tasks to the cloud while keeping limited computation on-board of UAV system using Edge computing technique. Further this will maintain the minimum communication between UAV and the cloud thus proposed system will reduce the network traffic and also delay. Proposed system is based on the state-of-art technique YOLO (You Look Only Once) for real time object detection. © Springer Nature Switzerland AG 2020.en_US
dc.titleCost-effective real-time aerial surveillance system using edge computingen_US
dc.typeBook Chapteren_US
Appears in Collections:3. Book Chapters

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