A safety system for the localization of at least one spatially variable object having at least one control and evaluation unit, having at least one radio location system, having at least one spatially resolving sensor for the detection of an object in a detection zone of the spatially resolving sensor, wherein the radio location system has at least three arranged radio stations, wherein at least one radio transponder is arranged at the object, wherein position data of the radio transponder and thus position data of the object can be determined by means of the radio location system, wherein the position data can be transmitted from the radio station of the radio location system to the control and evaluation unit, wherein the control and evaluation unit is configured to cyclically detect the position data of the radio transponder and information on the object in the detection zone can be determined by means of the spatially resolving sensor.

An acoustic array system for anomaly detection is provided. The acoustic array system (100) performs a scan (or a progressive scan of frequencies) of a given volume by transmitting one or more signals, and receives one or more reflected signals from objects within the volume. The reflected signals are then amplified and converted to a set of digital signals. Features of the set of digital signals are extracted both in time and frequency domains. The acoustic array system (100) further performs a comparison of these set of digital extracted features with the reflected signals via machine learning techniques. Based on the comparison, the acoustic array system detects one or more anomalies.

An acoustic array system for anomaly detection is provided. The acoustic array system (100) performs a scan (or a progressive scan of frequencies) of a given volume by transmitting one or more signals, and receives one or more reflected signals from objects within the volume. The reflected signals are then amplified and converted to a set of digital signals. Features of the set of digital signals are extracted both in time and frequency domains. The acoustic array system (100) further performs a comparison of these set of digital extracted features with the reflected signals via machine learning techniques. Based on the comparison, the acoustic array system detects one or more anomalies.