Abstract: This disclosure relates to methods and apparatus for monitoring a remote system. In one arrangement, a plurality of measurement data units are obtained. Each measurement data unit represents a time series of measurements made by a sensor system at the remote system. A first trained machine learning model is used to identify a subset of the measurement data units that have a higher average probability of corresponding to an abnormal state of the remote system than the other measurement data units. Data representing the identified measurement data units is sent over a communications network to a central data processing system. An abnormal state of the remote system is detected by using a second trained machine learning model at the central data processing system to process the data representing the identified measurement data units.

Abstract: A system for monitoring the operation of a surface pump such as a hand-operated water pump or oil pump, which uses an accelerometer mounted to a component of the pump to monitor movement of a pump component, for example the handle, and transmitted via a data connection such as a mobile data communications network to a server. The accelerometer measurements are processed by using a trained model such as a support vector machine to output an indication of the condition of the pump or the level of liquid in the well or borehole served by the pump. The model may be trained using a training data set of sensor measurements associated with liquid level in the well and condition of the pump.

Abstract: A system for monitoring the operation of a surface pump such as a hand-operated water pump or oil pump, which uses an accelerometer mounted to a component of the pump to monitor movement of a pump component, for example the handle, and transmitted via a data connection such as a mobile data communications network to a server. The accelerometer measurements are processed by using a trained model such as a support vector machine to output an indication of the condition of the pump or the level of liquid in the well or borehole served by the pump. The model may be trained using a training data set of sensor measurements associated with liquid level in the well and condition of the pump.