The Internet of Things (IoT) lies at the core of the unprecedented connected era we are currently speeding towards. Both Academia and the Industry strive to push the limits of technology fueled by vertical applications such as: factory 4.0, eHealth, human-centric and tactile IoT, wearable IoT, smart city/building, digital twin, etc., which will shape our future society and significantly impact both economic and societal aspects. Signal Processing (SP) plays an important role in expanding the number of IoT technologies and capitalizing on their applications. This is due to the sophisticated processing of signals and data gathered and shared by connected things. In this context, the unique challenges from the SP point of view are: (i) system design taking into account the applications' practical limitations and requirements, (ii) gather collective intelligence from heterogeneous and inexpensive IoT sensors/devices, (iii) minimize device cost and energy consumption while allowing perpetual monitoring/sensing (iv) grant adaptivity to cope with device mobility use cases, (v) leverage fine-grained "programming" of wireless environments to cope with massive IoT scenarios.