  Wireless sensor networks (WSNs) have been adopted as merely data producers
for years. However, the data collected by WSNs can also be used to manage their
operation and avoid unnecessary measurements that do not provide any new
knowledge about the environment. The benefits are twofold because wireless
sensor nodes may save their limited energy resources and also reduce the
wireless medium occupancy. We present a self-managed platform that collects and
stores data from sensor nodes, analyzes its contents and uses the built
knowledge to adjust the operation of the entire network. The system
architecture facilitates the incorporation of traditional WSNs into the
Internet of Things by abstracting the lower communication layers and allowing
decisions based on the data relevance. Finally, we demonstrate the platform
optimizing a WSN's operation at runtime, based on different real-time data
analysis.
