# A Collaborative UAV-WSN Network for Monitoring Large Areas
## 2 Materials and Methods
### Monitoring System Architecture  
In [29], the advantages of a general architecture for a heterogeneous monitoring system (UAVs-WSNs) are discussed, tailored for large scale monitoring and information processing, through a decentralized fusion approach. Starting from the same decentralized multilevel architecture, a single UAV serves here as data collector for the on-ground sensing nodes clusters and is used to enhance the connection between ground WSNs and the central gateway (base station). Communication-wise, in this paper, we divide this decentralized architecture into several levels, thus, a multilevel architecture. Top-most, a single UAV serves as a data collector for the ground detection nodes which compose the lower levels. In a multi-level representation, the proposed hybrid UAV-WSN is described as in Figure 1. Starting from the ground level, the monitoring system consists of an extended network of sensors, which can be divided into WSN subsystems, further referred to as clusters. The clustered sensor nodes (Level 2) collect sensory data using specific acquisition equipment (Level 3) and provide efficient data analysis through in-network data processing mechanisms. The fusion of sensor data is optimally established using effective consensus schemes. Typically, under the consensus mechanism, each sensor node performs gross estimation of the global average value and continues to improve its value through local information exchange between cluster neighbors. The UAV (Level 1) exchanges data with each cluster through a single sensor node further referred as cluster head. Cluster heads are marked with red color in Figure 1. The measure of limiting UAV-WSN data exchange to a single node per cluster is adopted in order to substantially reduce the burden on the communication channel. We assume that the power consumption of intra-cluster communication is much less than the power required for direct sensor-UAV communication. The relevant sensory information is transmitted by UAV to ground station (Center gateway--Level 0). Additionally, the UAV contributes to the dynamic clustering of ground sensor nodes and cluster head selection mechanism. Several assumptions about the mission parameters and external environment must be considered:1. The nodes are randomly scattered within the area of interest; either due to the lack of GPS coordination or because of perturbing factors such as wind gusts when doing aerial deployment. 2. The area of interest has restricted regions over which flights are not allowed such as: buildings, roads or other areas where humans are present. The second item in particular raises some interesting operational limitations for the mission: the interdicted areas are ignored by the sensor network, being transparent from the communication viewpoint, but are seen as obstacles to be avoided from the UAV's viewpoint. The overall data gathering problem is divided, due to its complexity and many requirements, into several sequential subproblems:  
1. Assuming that the sensor position is unknown, a preliminary stage in which the UAV(s) gather location data is required. This can be assimilated to a photogrammetry procedure in which the surface of interest is crossed repeatedly to estimate the sensors' position and receive information about cluster grouping, decided at the WSN level. 2. Putting together the information about obstacles, cluster heads and communication restrictions, a list of possible reference trajectories for the UAV(s) is obtained. 3. Lastly, during flight, it is ensured via auto-pilot feedback that the reference trajectories are tracked within prescribed tolerance bounds. While none of the issues mentioned above is completely new, we consider that the reciprocal influences between each stage are of interest and rise challenging theoretical and practical issues. The paper concentrates on the first two items in this classification.