Some embodiments provide a non-transitory machine-readable medium that stores a program. The program may receive a set of data from a data source. The program may generate a plurality of time series data based on the set of data. The program may determine a subset of the plurality of time series data as anomalies. The program may provide notifications indicating that the subset of the plurality of time series data are anomalies.

A computer-implemented method for recognizing an event. The method includes: receiving sensor data from at least one sensor unit using an event recognition unit, wherein the sensor data are in the form of time series data and depict the event; filtering the sensor data using a matched filter arrangement of the event recognition unit and generating filtered sensor data; and recognizing the event based on the filtered sensor data using the event recognition unit. A method for generating a matched filter arrangement is also described.

A method and system for prediction based on asynchronous and heterogeneous time-series data streams is provided. The asynchronous and heterogeneous time-series data streams are aligned onto a unified temporal grid. The aligned time-series data streams are synchronous, and sampling frequencies of the aligned time-series data streams are identical. Cross-attention is executed on the aligned time-series data streams across multiple attention windows. Each attention window is associated with a different time duration. A cross-attention output is generated based on the execution of the cross-attention for each attention window. Fused embeddings are generated based on the cross-attention outputs generated for the multiple attention windows. A prediction output is generated based on the plurality of fused embeddings for the time-series data streams.

Machine-learning-based methods and systems for vegetation treatment project design. The approach autonomously creates, evaluates, and optimizes wildfire risk mitigation activities to intelligently reduce wildfire risk to communities in a resource-constrained environment. The methods and/or systems are accompanied by a cloud-enabled user interface that provides decision support to vegetation management specialists charged with implementing wildfire risk reduction measures.

An information processing method includes acquiring, by an information processing apparatus, a time-series measurement signal of the acoustic emission of an object; calculating, by the information processing apparatus, energy of the acoustic emission of the object based on the measurement signal; extracting, by the information processing apparatus, either (i) a time-series signal of a first component obtained by removing a second component having periodicity from a time-series energy signal, or (ii) a time-series signal of the second component, as first extraction; and calculating, by the information processing apparatus, an index value relating to variation of the time-series signal of the first component or of the time-series signal of the second component.