Abstract: Methods and systems are provided for monitoring a physical asset, which includes receiving or collecting time-series data related to operation or status of the physical asset; identifying a time period when the physical asset is experiencing a change in operational state; extracting time-series data corresponding to the time period as event data; generating label data that classifies or characterizes the event data as pertaining to a particular type of event; saving the event data and the corresponding label data in a data repository; and using the event data and label data stored in the data repository to train or update a machine learning system to detect the occurrence of events that are similar to the event types of the labeled event data stored in the data repository from time-series data generated by the physical asset or by another physical asset that operates in a similar manner to the physical asset.

Abstract: A method includes determining where to place one or more devices at a site. Each device includes a first sensor configured to measure a concentration of a greenhouse gas (GHG). The method also includes measuring the concentration of the GHG with the first sensors. The method also includes quantifying a rate that the GHG is emitted based at least partially upon the measured concentration of the GHG. The method also includes determining a location of a GHG-emitting source at the site that is emitting the GHG that is measured by the first sensors. The location is determined based at least partially upon the measured concentration, the quantified rate, or both. The method also includes identifying the GHG-emitting source at the determined location by comparing the determined location with a list of a plurality of GHG-emitting sources at the site and locations thereof.