The last decade has witnessed pioneering efforts in advancing versatile networked architectures that facilitate our interaction with the physical world over Distributed Sensor Networks (DSN). While DSN as gaining prominence as the key enabling technology for addressing significant societal problems, current trends in sensing applications have been facing up to the challenge of moving from episodic sampling to truly pervasive paradigms. As such, the necessity intensifies for transiting from conventional sensor/actuator schemes, which act as transparent gateways between complex physical spaces and sophisticated decision makers, to more dynamic structures that can bring context to the level of front-end sensing. Driving by the respective technical challenges that arise, research conducted at SPL emphasizes on both theoretical, as well as practical aspects related to distributed signal and data processing, networking over limited resources, and context retrieval, while serving the design paradigms of IoT and CPS.