  Networked embedded systems endowed with sensing, computing, control and
communication capabilities allow the development of various application
scenarios and represent the building blocks of the Internet of Things (IoT)
paradigm. Traditional data collection methods include multiple field level IoT
systems that can relay data stemming from a network of distributed ground
sensors directly to a cloud platform for storage, analysis and processing. In
such applications however, rapid sensor deployment in unstructured environments
represents a challenge to the overall robustness of the system. We discuss the
fog and mist computing approaches to hierarchically process data along its path
from source to destination. The several stages of intermediate data processing
reduce the computational and communication effort in a gradual manner. A
three-layer topology for smart data monitoring and processing is thus proposed
and illustrated to improve the information to noise ratio in a reference
scenario.
