Towards goal-oriented semantic signal processing: Applications and future challenges

Advances in machine learning technology have enabled real-time extraction of semantic information signals which can revolutionize signal processing techniques and improve their performance significantly for the next generation applications. With objective a concrete representation efficient information, we propose demonstrate formal graph-based language goal filtering method that enables goal-oriented processing. The proposed framework easily be tailored specific applications goals diverse range To illustrate its wide applicability, investigate several use cases provide details on how customized. We also communications where sensor data is semantically processed exchanged across network.