1 research outputs found
UAV-aided urban target tracking system based on edge computing
Target tracking is an important issue of social security. In order to track a
target, traditionally a large amount of surveillance video data need to be
uploaded into the cloud for processing and analysis, which put stremendous
bandwidth pressure on communication links in access networks and core networks.
At the same time, the long delay in wide area network is very likely to cause a
tracking system to lose its target. Often, unmanned aerial vehicle (UAV) has
been adopted for target tracking due to its flexibility, but its limited flight
time due to battery constraint and the blocking by various obstacles in the
field pose two major challenges to its target tracking task, which also very
likely results in the loss of target. A novel target tracking model that
coordinates the tracking by UAV and ground nodes in an edge computing
environment is proposed in this study. The model can effectively reduce the
communication cost and the long delay of the traditional surveillance camera
system that relies on cloud computing, and it can improve the probability of
finding a target again after an UAV loses the tracing of that target. It has
been demonstrated that the proposed system achieved a significantly better
performance in terms of low latency, high reliability, and optimal quality of
experience (QoE)