  Large scale monitoring systems enable efficient field level data collection
at high temporal and spatial resolutions. One example is the deployment of such
systems in pipeline infrastructure applications which have to be monitored for
leaks and protected from unauthorized access, with the potential of causing
significant environmental and economic damage. The paper discusses a
multi-level system architecture for data collection and processing based on the
collaborative integration of wireless sensor networks and unmanned aerial
vehicles. Three sensor fusion methods: Kalman filtering, Fuzzy Sensor
Validation and Fusion (FUSVAF) and Consensus-based processing, are considered
for intelligent data reduction and situational awareness while alleviating
communication bottlenecks across the multi-level network. Simulation and
experimental results are presented.
