| dc.description.abstract | Unmanned Aerial Vehicles (UAVs) have recently o ered signi cant technological achievements. The
advancement in related applications predicts an extended need for automated data muling by UAVs, to
explore high risk places, ensure e ciency and reduce the cost of various products and services. Due to
advances in technology, the actual UAVs are not as expensive as they once were. On the other hand,
they are limited in their
ight time especially if they have to use fuel. As a result, it has recently been
proposed that they could be assisted by the ground static sensors which provide information of their
surroundings. Then, the UAVs need only to provide actions depending on information received from
the ground sensors. In addition, UAVs need to cooperate among themselves and work together with
organised ground sensors to achieve an optimal coverage. The system to handle the cooperation of
UAVs, together with the ground sensors, is still an interesting research topic which would bene t both
rural and urban areas.
In this thesis, an e cient ground sensor network for optimal UAVs coverage is rst proposed. This is
done using a clustering scheme wherein, each cluster member transmits its sensor readings to its cluster
head. A more e cient routing scheme for delivering readings to cluster head(s) for collection by UAVs is
also proposed. Furthermore, airborne sensor deployment models are provided for e cient data collection
from a unique sensor/target. The model proposed for this consists of a scheduling technique which
manages the visitation of UAVs to target. Lastly, issues relating to the interplay between both types of
sensor (airborne and ground/underground) networks are addressed by proposing the optimal UAVs task
allocation models; which take caters for both the ground networking and aerial deployment.
Existing network and tra c engineering techniques were adopted in order to handle the internetworking
of the ground sensors. UAVs deployment is addressed by adopting Operational Research techniques
including dynamic assignment and scheduling models. The proposed models were validated by simulations,
experiments and in some cases, formal methods used to formalise and prove the correctness of key
properties. | en_US |
