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 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 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 and said classification signal and to compare, during a sensing time interval (T1, T2, T3), said alarm signal and said classification signal to generate a qualified alarm signal, said qualified alarm signal being configured to provide coded information indicative of the fact that the alarm signal 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 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 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 and said classification signal and to compare, during a sensing time interval (T1, T2, T3), said alarm signal and said classification signal to generate a qualified alarm signal, said qualified alarm signal being configured to provide coded information indicative of the fact that the alarm signal represents, in the sensing time interval (T1, T2, T3), a recognized acoustic and/or vibrational anomaly or an unknown acoustic and/or vibrational anomaly.