Abstract: In one aspect, an example method includes (a) determining, via a thermal conductivity sensor of an automobile damage detection device, one or more thermal conductivities at one or more locations on an automobile; (b) transmitting, via a network interface of the automobile damage detection device, a request for anticipated thermal conductivity data from an automobile claims system, wherein the anticipated thermal conductivity data corresponds to anticipated thermal conductivities at the one or more locations on the automobile; (c) in response to transmitting the request, receiving, via the network interface from the automobile claims system, the anticipated thermal conductivity data; and (d) in response to receiving, from the automobile claims system, the anticipated thermal conductivity data, displaying, via a graphical user interface, a graphical representation of the determined one or more thermal conductivities and the anticipated thermal conductivity data.

Abstract: The present teaching relates to dynamically generating a card. In one example, a request is received for generating a card to be provided to a user. Dynamic information related to the request is obtained. One or more modules are selected to be put into the card based on the dynamic information. The card is generated based on the selected one or more modules.

Abstract: A device having a voice-based interface activates or “wakes” when it detects an utterance that includes a wakeword; the device may be installed in a vehicle, such as an automobile. The device may distinguish between different wakewords; a different speech processing system may be associated with each wakeword, and each speech processing engine may have its own speech style and associated applications and functions.

Abstract: Techniques for dynamic contact ingestion are described. A system may interpret a voice command received from a first device based on contact data or other information associated with a second device connected to the first device. For example, when a data connection is made between the first device and the second device, the first device may receive the contact data and send the contact data to a remote system. The remote system may temporarily associate the contact data with the first device, enabling the remote system to interpret a voice command received from the first device using the contact data. The remote system may use the contact data to perform disambiguation, enabling the remote system to initiate outbound calls, announce inbound calls, and/or the like. When the second device is disconnected from the first device, the remote system may remove the association between the contact data and the first device.

Abstract: The present invention is generally directed to systems and methods for performing energy disaggregation of appliances in a home. In accordance with some embodiments of the invention, a method may include receiving one or more parameters corresponding to plurality of the appliances installed in home through an energy disaggregation device. The one or more parameters may be associated with the home. The method may further include receiving localized energy consumption data of a region where the home environment is located, selecting a predefined energy disaggregation model from one or more predefined energy disaggregation models based on the localized energy consumption data, adjusting the predefined energy disaggregation model based on the one or more parameters, and/or applying the adjusted predefined energy disaggregation model to the energy consumption data to perform disaggregation of the energy consumption into a plurality of appliance categories.

Abstract: The present invention teaches methods of performing appliance itemization based on consumption data, including: receiving at a processor the data; determining if the data includes active signals and/or inactive signals; upon detection of an active signal: detecting and estimating active water heating consumption and lighting consumption; upon detection of an inactive signal: detecting and estimating passive water heating consumption, refrigerator consumption; and detecting vacation mode.

Abstract: The present teaching relates to dynamically generating a card. In one example, a request is received for generating a card to be provided to a user. Dynamic information related to the request is obtained. One or more modules are selected to be put into the card based on the dynamic information. The card is generated based on the selected one or more modules.

Abstract: The present invention is generally directed to systems and methods for disaggregating an energy profile for one or more appliances installed in a non-smart meter home. Methods may be implemented by one or more processors, and steps may include: retrieving energy consumption data, and a plurality of attributes of a non-smart meter home, retrieving energy consumption data, appliance-level energy consumption data, and a plurality of attributes of a predefined set of smart meter homes, matching the energy consumption data and the attributes of the non-smart meter home with the predefined set to identify a set of peer homes; estimating the appliance disaggregation of the non-smart meter home based on the retrieved data of the identified peer homes, and forecasting and projecting at least one of electricity bill, mid-cycle consumption, end-of-cycle consumption, disaggregation for non-smart homes, and/or combination thereof.

Abstract: The present invention is directed to systems and methods for performing energy disaggregation of a whole-house energy usage waveform, based at least in part on the whole-house energy usage profile, training data, and predetermined generic models, including: a module for pairing impulses identified in the whole-house energy usage waveform to indicate an appliance cycle, pairing impulses with at least one up transition with at least one down transition; a module for bundling impulses that are representative of an appliance cycle; a classification module, which upon determination of a type of appliance associated with bundles, is configured to classify the bundles of transitions in accordance with bundles exhibited by similar appliances with similar characteristics; and utilizing such pairing module and module for bundling to perform energy disaggregation.

Abstract: The present invention is directed to systems and methods of disaggregating and detecting energy usage associated with electric vehicle charging from a whole-house consumption signal. In general, methods of the present invention may include: a method of electronically detecting and disaggregating a consumption signal associated with the charging of an electric vehicle from a whole-house profile, comprising: identifying by an electronic processor potential interval candidates of electric vehicle charging; determining by the electronic processor intervals associated with the charging of an electric vehicle, based at least in part on evaluating each potential interval candidate against factors including amplitude, duration, and time-of-day; and accounting by the electronic processor for feedback of any incorrectly detected signals.

Abstract: A system comprises an automation network including a gateway at a premises coupled to a remote server. Premises devices are coupled to the gateway and form at least one device network in the premises. An automation user interface (AUI) application is configured to access the plurality of premises devices via at least one of the gateway and the remote server. The AUI application is configured to run on each of a plurality of remote devices, and the plurality of remote devices comprises a plurality of device types. An application program interface (API) is configured to execute on at least one of the gateway and the remote server and to serve normalized data including state data of the plurality of premises devices to the AUI application on the plurality of remote devices. A normalized data model is configured to generate the normalized data including the state data of the plurality of premises devices agnostically to the plurality of remote devices.

Abstract: The present invention is generally directed to systems and methods for performing energy disaggregation of appliances in a home. In accordance with some embodiments of the invention, a method may include receiving one or more parameters corresponding to plurality of the appliances installed in home through an energy disaggregation device. The one or more parameters may be associated with the home. The method may further include receiving localized energy consumption data of a region where the home environment is located, selecting a predefined energy disaggregation model from one or more predefined energy disaggregation models based on the localized energy consumption data, adjusting the predefined energy disaggregation model based on the one or more parameters, and/or applying the adjusted predefined energy disaggregation model to the energy consumption data to perform disaggregation of the energy consumption into a plurality of appliance categories.

Abstract: The present invention is directed to systems and methods of disaggregating and detecting energy usage associated with electric vehicle charging from a whole-house consumption signal. In general, methods of the present invention may include: identifying by an electronic processor potential interval candidates of electric vehicle charging, based at least in part upon long and decreasing patterns; determining by the electronic processor intervals associated with the charging of an electric vehicle, based at least in part on evaluating each potential interval candidate; determining by the electronic processor an initial point of charging for each interval associated with the charging of an electric vehicle; and accounting by the electronic processor for feedback of any incorrectly detected signals.

Abstract: The present invention is generally directed to methods of disaggregating low resolution whole-house energy consumption data. In accordance with some embodiments of the present invention, methods may include steps of: receiving at a processor the low resolution whole house profile; selectively communicating with a first database including non-electrical information; selectively communicating with a second database including training data; and determining by the processor based on the low resolution whole house profile, the non-electrical information and the training data, individual appliance load profiles for one or more appliances.

Abstract: The present invention is generally directed to methods of disaggregating low resolution whole-house energy consumption data. In accordance with some embodiments of the present invention, methods may include steps of: receiving at a processor the low resolution whole house profile; selectively communicating with a first database including non-electrical information; selectively communicating with a second database including training data; and determining by the processor based on the low resolution whole house profile, the non-electrical information and the training data, individual appliance load profiles for one or more appliances.

Abstract: The invention is directed to systems and methods for detecting occurrence of at least one event in a household environment. In one embodiment, the method includes receiving energy profile data determined for the household environment. The method may further include analyzing the energy profile data to obtain operation parameters for appliances being used in the household environment. The method may further include comparing the operation parameters with steady state parameters for each of the appliance based one or more deviation rules. The method may further include detecting occurrence of the at least one event in the household environment based on the comparing.

Abstract: The present invention is generally directed to systems and methods for performing energy disaggregation of appliances in a home. In accordance with some embodiments of the invention, a method may include receiving one or more parameters corresponding to plurality of the appliances installed in home through an energy disaggregation device. The one or more parameters may be associated with the home. The method may further include receiving localized energy consumption data of a region where the home environment is located, selecting a predefined energy disaggregation model from one or more predefined energy disaggregation models based on the localized energy consumption data, adjusting the predefined energy disaggregation model based on the one or more parameters, and/or applying the adjusted predefined energy disaggregation model to the energy consumption data to perform disaggregation of the energy consumption into a plurality of appliance categories.

Abstract: The present invention teaches methods of performing appliance itemization based on consumption data, including: receiving at a processor the data; determining if the data includes active signals and/or inactive signals; upon detection of an active signal: detecting and estimating active water heating consumption and lighting consumption; upon detection of an inactive signal: detecting and estimating passive water heating consumption, refrigerator consumption; and detecting vacation mode.

Abstract: Packets or data units and their related credit returns each include an assigned phase value. When a credit test is desired, the phase value of outgoing data units is changed, for example from 0 to 1, and a new counter is set to a value of the outstanding credits having the original phase value. With each original phase credit received, the counter value is decremented. When a credit having the new phase value is received, the counter value indicates the amount of any credit error and appropriate corrections may be made.

Abstract: Systems and methods for managing inventory in an online advertising system are described herein. The inventory may comprise advertisement (“ad”) impressions. In accordance with certain implementations, the systems and methods enable advertisers to target groups of inventory (e.g., “run of” inventory groups) made available by publishers and sold at a non-premium rate, while also enabling the publishers to selectively designate certain inventory within a given inventory group as premium. Inventory so designated is automatically excluded from an inventory group to which it would normally belong both during a booking process as well as during an ad serving process.