A system for sensing and recognizing acoustic anomalies and/or vibrational anomalies associated with a site to be monitored, comprising: - a unit using optical fiber for the distributed acoustic sensing, DAS, and/or for the distributed vibrational sensing, DVS, of at least one acoustic and/or vibrational anomaly associated with said site and for generating an alarm signal (S1) representative of the sensing of said at least one acoustic and/or vibrational anomaly; - one or more acoustic-electric transducers operatively associated with said site to be monitored to sense one or more ambient audio signals associated with said at least one acoustic and/or vibrational anomaly and to convert said ambient audio signals into electrical signals; - an audio classifier module connected to said one or more acoustic-electric transducers and configured to classify said electrical signals generated based on at least one algorithm for data analysis and machine learning of information from the data, to generate a classification signal (S2) indicative of the fact that said at least one sensed acoustic and/or vibrational anomaly is included in a set of recognized anomalies or is an unknown acoustic and/or vibrational anomaly; characterized in that it further comprises - a correlator module configured to receive said alarm signal (S1) and said classification signal (S2) and to compare, during a sensing time interval (T1, T2, T3), said alarm signal (S1) and said classification signal (S2) to generate a qualified alarm signal (S3), said qualified alarm signal being configured to provide coded information indicative of the fact that the alarm signal (S1) represents, in the sensing time interval (T1, T2, T3), a recognized acoustic and/or vibrational anomaly or an unknown acoustic and/or vibrational anomaly. - a unit using optical fiber for the distributed acoustic sensing, DAS, and/or for the distributed vibrational sensing, DVS, of at least one acoustic and/or vibrational anomaly associated with said site and for generating an alarm signal (S1) representative of the sensing of said at least one acoustic and/or vibrational anomaly; - one or more acoustic-electric transducers operatively associated with said site to be monitored to sense one or more ambient audio signals associated with said at least one acoustic and/or vibrational anomaly and to convert said ambient audio signals into electrical signals; - an audio classifier module connected to said one or more acoustic-electric transducers and configured to classify said electrical signals generated based on at least one algorithm for data analysis and machine learning of information from the data, to generate a classification signal (S2) indicative of the fact that said at least one sensed acoustic and/or vibrational anomaly is included in a set of recognized anomalies or is an unknown acoustic and/or vibrational anomaly; characterized in that it further comprises - a correlator module configured to receive said alarm signal (S1) and said classification signal (S2) and to compare, during a sensing time interval (T1, T2, T3), said alarm signal (S1) and said classification signal (S2) to generate a qualified alarm signal (S3), said qualified alarm signal being configured to provide coded information indicative of the fact that the alarm signal (S1) represents, in the sensing time interval (T1, T2, T3), a recognized acoustic and/or vibrational anomaly or an unknown acoustic and/or vibrational anomaly. <EOS>