Abstract: A system includes vibration sensors coupled to equipment and an edge device arranged between the vibration sensors and a communications network. The edge device detects an abnormality in vibration data from the vibration sensors, performs signal processing on the vibration data to obtain inputs for a machine learning model, determines whether the abnormality is occurring by applying the inputs to the machine learning model, and determines a trend associated with the abnormality based on outputs of the machine learning model. The trend characterizes a change in a degree of the abnormality or a duration of the abnormality. The edge device causes the vibration data to be communicated to a computing system via the communications network in response to the trend satisfying a criterion and compares the trend to the criterion to distinguish new abnormalities or substantial changes in abnormalities from substantially constant abnormalities.

Abstract: A system includes a plurality of vibration sensors configured to be coupled to a unit of building equipment, an edge device arranged between the plurality of vibration sensors and a communications network. The edge device is programmed to detect an abnormality in vibration data from the plurality of vibration sensors by ingesting streams of vibration data from the plurality of vibration sensors, performing signal processing on the streams of vibration data to obtain inputs for a machine learning model, determining whether the abnormality is occurring by applying the inputs to the machine learning model, determining a trend associated with the abnormality based on outputs of the machine learning model, and causing a portion of the vibration data to be communicated to a first computing system via the communications network in response to the trend satisfying a criterion.

Abstract: A method includes generating a mixed air temperature value using a reinforcement learning model running on the edge controller. A temperature setpoint and a weather forecast are inputs to the reinforcement learning model. The method also includes controlling damper positions of an air handling unit to achieve the mixed air temperature value.

Abstract: A system includes a plurality of vibration sensors configured to be coupled to a unit of building equipment, an edge device arranged between the plurality of vibration sensors and a communications network. The edge device is programmed to detect an abnormality in vibration data from the plurality of vibration sensors by ingesting streams of vibration data from the plurality of vibration sensors, performing signal processing on the streams of vibration data to obtain inputs for a machine learning model, determining whether the abnormality is occurring by applying the inputs to the machine learning model, determining a trend associated with the abnormality based on outputs of the machine learning model, and causing a portion of the vibration data to be communicated to a first computing system via the communications network in response to the trend satisfying a criterion.