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Edge-Based Live Video Analytics for Drones

delete2019-07-01
delete14
PRE
AI
J
Junjue Wang *
Z
Ziqiang Feng
Z
Zhuo Chen
S
Shilpa George
M
Mihir Bala
P
Padmanabhan Pillai
M
Mahadev Satyanarayanan
DOI：10.1109/MIC.2019.2909713delete
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Abstract

Abstract

En 中文
Real-time video analytics on small autonomous drones poses several difficult challenges at the intersection of wireless bandwidth, processing capacity, energy consumption, result accuracy, and timeliness of results. In response to these challenges, this paper describes four strategies to build adaptive computer vision pipelines for domains such as search-and-rescue, surveillance, and wildlife conservation. Our experimental results show that a judicious combination of drone-based processing and edge-based processing can save substantial wireless bandwidth and thus improve scalability, without compromising result accuracy or latency.
Keywords:
Photonics
Edge computing
Hall effect
Steady-state
Optical losses
Nonhomogeneous media
Perturbation methods
Visual analytics
Edge Computing
Live Video Analytics
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Journal

IEEE Internet Computing cover
IEEE Internet Computing
IF:
4.4
Papers:
2.0K
Citations:
2.0K

Organization

C
Carnegie Mellon University
Scholars:
1.4W
Papers: 1.4W
Citations: 2.7W
U
University of Michigan
Scholars:
6.4W
Papers: 5.3W
Citations: 124
U
university of michigan system
Scholars:
9.1W
Papers: 8.6W
Citations: 133
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