  Internet of Things (IoT) applications combine sensing, wireless
communication, intelligence, and actuation, enabling the interaction among
heterogeneous devices that collect and process considerable amounts of data.
However, the effectiveness of IoT applications needs to face the limitation of
available resources, including spectrum, energy, computing, learning and
inference capabilities. This paper challenges the prevailing approach to IoT
communication, which prioritizes the usage of resources in order to guarantee
perfect recovery, at the bit level, of the data transmitted by the sensors to
the central unit. We propose a novel approach, called goal-oriented (GO) IoT
system design, that transcends traditional bit-related metrics and focuses
directly on the fulfillment of the goal motivating the exchange of data. The
improvement is then achieved through a comprehensive system optimization,
integrating sensing, communication, computation, learning, and control. We
provide numerical results demonstrating the practical applications of our
methodology in compelling use cases such as edge inference, cooperative
sensing, and federated learning. These examples highlight the effectiveness and
real-world implications of our proposed approach, with the potential to
revolutionize IoT systems.
