Abstract: A method of monitoring drainage of a washing appliance such as a dishwasher or washing machine having a pump for draining a washing chamber is disclosed. The method includes receiving a time series of power consumption data relating to the operation of the washing appliance over a monitored period of operation including pumped draining of the washing chamber. A measure of the duration of a portion of the monitored period comprising said pumped draining is derived from the time series of power consumption data. The measure of duration is then compared to a reference value and an indicator of a drainage condition is determined based on the comparison. The method may be used to detect scaling or blockages in drainage flow paths.

Abstract: A method of detecting a fault in a device is described. The method comprises receiving an energy consumption signal for the device, the energy consumption signal indicating a varying energy consumption of the device over time during operation of the device. A basis function is selected, the basis function defining a signal pattern associated with a known fault type. A correlation between the basis function and the energy consumption signal is evaluated. Presence of an operating fault in the device is determined in dependence on the correlation, and an output is generated based on the determination.

Abstract: A method is disclosed for controlling one or more appliances in a user environment, the one or more appliances in operation capable of causing environmental stimuli disruptive to a user's sleep. The method comprises receiving from one or more sensors data indicative of a sleep state of the user; analysing the received data to determine one or more control actions for controlling the one or more appliances to reduce sleep disruption due to the environmental stimuli caused by the appliances; and controlling the one or more appliances in dependence on the determined control actions. The method may involve determining, based on sleep state data for a first sleep period, an appliance control schedule for a second, later, time period.

Abstract: A method of detecting a fault in a device is described. The method comprises receiving an energy consumption signal for the device, the energy consumption signal indicating a varying energy consumption of the device over time during operation of the device. A basis function is selected, the basis function defining a signal pattern associated with a known fault type. A correlation between the basis function and the energy consumption signal is evaluated. Presence of an operating fault in the device is determined in dependence on the correlation, and an output is generated based on the determination.

Abstract: In one example, there is provided a computer-implemented method for estimating, at a given time, a fluid flow state in a conduit of a property, comprising: obtaining historical data associated with at least one fluid flow state in the conduit, wherein the historical data comprises a history of the probability of the at least one fluid flow state in the conduit; obtaining a probability model for the at least one fluid flow state, wherein a probability for the at least one fluid flow state is a function of the historical data associated with the at least one fluid flow state; obtaining observed data associated with the property, the observed data including a measure representative of fluid flow in the conduit; and estimating a fluid flow state in the conduit of the property at the given time, based on the historical data associated with the at least one fluid flow state, the probability model and the observed data.

Abstract: Disclosed is a control system for a smart home environment comprising one or more devices connected to the control system via a communications network. The control system receives a plurality of data records from the one or more devices and transmits data from the data records to a remote processing system for analysis. The system receives cluster specification data from the remote processing system-defining a plurality of data clusters relating to the data records, the data clusters derived by the remote processing system at least in part based on the transmitted data. The control system subsequently receives additional data records from the one or more devices and classifies the additional data records by allocating the data records to one or more clusters of the data clusters based on the cluster specification data. The control system controls at least one device in the smart home environment by cluster allocation.

Abstract: Methods and devices for detecting inefficiencies in environmental control systems and for building a model for detecting the same. The model building method may comprise: receiving training data sets for one or more environmental control systems, identifying a category for each training data set indicative of the efficiency of the environmental control system over the training time period, computing one or more numerical features for each training data set based on setpoint data and sensor data, determining a measure of dependence between the identified category and the computed one or more numerical features, and creating a model based on the determined measure of dependence. The detection method may involve receiving a monitored data set, computing numerical features for the monitored data, and assigning a category indicative of the efficiency of a monitored environmental control system based on the model and the numerical features.

Abstract: A method is disclosed for controlling one or more appliances in a user environment, the one or more appliances in operation capable of causing environmental stimuli disruptive to a user's sleep. The method comprises receiving from one or more sensors data indicative of a sleep state of the user; analysing the received data to determine one or more control actions for controlling the one or more appliances to reduce sleep disruption due to the environmental stimuli caused by the appliances; and controlling the one or more appliances in dependence on the determined control actions. The method may involve determining, based on sleep state data for a first sleep period, an appliance control schedule for a second, later, time period.

Abstract: A method for monitoring and controlling device activity is disclosed. The method comprises collecting device activity data relating to a first media consumer, wherein the device activity data corresponds to activity of one or more devices in an environment of the first media consumer during playback of a given media asset by the first media consumer. The method then determines, based on the device activity data, at least one action performable by a device in an environment of a second media consumer. Playback of the given media asset by the second media consumer is detected; and in response to detecting playback of the given media asset, one or more devices in an environment of the second media consumer are controlled to perform the determined actions.