Abstract: Monitoring a premises may comprise receiving signals from a plurality of devices. One or more spatially static devices of the plurality of devices may be determined based on strengths of the received signals. A user activity pattern may be determined based on changes in strengths of signals received from the spatially static devices. Abnormal user activity may be determined based on the user activity pattern and a strength of at least one signal received from at least one of the spatially static devices.

Abstract: Methods, systems, and apparatuses are described for identifying highlights of a content item, and identifying times, within the content item, to indicate as a beginning of a chapter within the content item. A second content item that corresponds to a portion of the first content item may be identified. The portion of the first content item may be determined to be a highlight of the first content item. Shot boundaries of the content item may be determined, and chapter information corresponding to a different version of the content item may be mapped to the content item.

Abstract: A voice enabled device can assist a computing device, such as a server, in processing/analyzing a voice input. The voice enabled device can initiate a network communication session and transmit the voice input to the computing device. The computing device can classify the voice input as a type of communication session (e.g., conversation, etc. . . . ). Based on the type of communication session, the computing device can either remain in communication with the voice enabled device and continue to process voice input or terminate the communication after instructing the voice enabled device to process the voice input.

Abstract: An audio file associated with a user voice query may be received at a user device. The audio file may be compared to a plurality of references, such as cache entries, corresponding to a plurality of other voice queries. Based on a determination that the voice query corresponds to one of the references, an operation associated with the voice query may be executed. An indication may be received that the operation was not an intended operation associated with the voice query. Based on receiving this indication, the incorrectly identified operation, associated reference, e.g., voice query, may be disabled for the user or the device. However, the cache entry may remain enabled for one or more of a plurality of other devices.

Abstract: Monitoring a premises may comprise receiving signals from a plurality of devices. One or more spatially static devices of the plurality of devices may be determined based on strengths of the received signals. A user activity pattern may be determined based on changes in strengths of signals received from the spatially static devices. Abnormal user activity may be determined based on the user activity pattern and a strength of at least one signal received from at least one of the spatially static devices.

Abstract: Methods and systems for more efficient analyses of and response to voice commands and queries are provided. The system may be configured to receive one or more of audio files corresponding to a voice query and determine, for each of the audio files, whether the audio file is a first type of audio file capable of being processed based on a characteristic of the audio file or a second type of audio file that cannot, and may require further processing in order to recognize the voice query associated with the audio file. The system may process each of the first type of audio files and respond to the associated voice queries. The system may also determine a priority for each of the second type of audio files for further processing of the second type of audio files.

Abstract: Methods, systems, and apparatuses for managing a wireless network are described herein. A wireless network may include a gateway device, an access point, and a group of client devices. An analytics engine may receive network performance data for the wireless network, which may indicate network telemetry data for each of the client devices or associated locations during a time period. The analytics engine may utilize a trained classifier to determine that a performance metric indicated by the network performance data for a client device falls below a desired level of performance. The analytics engine may provide a recommendation regarding an addition or placement of a network device in order to improve the performance metric.

Abstract: Methods, systems, and/or apparatuses are described for detecting relevant motion of objects of interest (e.g., persons and vehicles) in surveillance videos. As described herein input data based on a plurality of captured images and/or video is received. The input data may then be pre-processed and used as an input into a convolution network that may, in some instances, have elements that perform both spatial-wise max pooling and temporal-wise max pooling. Based on The convolution network may be used to generate a plurality of prediction results of relevant motion of the objects of interest.

Abstract: A device may be configured to determine whether an audio file is a first type of audio file that is capable of being processed to recognize the voice query based on a characteristic of the audio file itself or a second type of audio file that may require speech recognition processing in order to recognize the voice query associated with the audio file. In determining whether the audio file is a first type of audio file or a second type of audio file, a query filter associated with the device may be configured to access one or more guidance queries. Using the one or more guidance queries, the device may classify the audio file as a first type of audio file or a second type of audio file based on receiving only a portion of the audio file, thereby improving the speed at which the audio file can be processed.

Abstract: A sewage/wastewater biological treatment system—sewage (wastewater) synergistic treatment acceleration device, which includes four components of a reaction assembly, a signal transmission assembly, a control assembly, and a housing carrying assembly. The reaction assembly can realize the colonization/proliferation of functional microorganisms, participate in the interface electron transfer between the electrode-microbe-sewage as an electron donor/receptor and electrode interface of the (bio)electrochemical reaction, and optimize the flow characteristics in the sewage/wastewater treatment system. The signal transmission assembly enables the conduction of applied voltage and real-time signal acquisition and transmission of key parameters. The monitoring assembly implements intelligent controllability of the present invention. The housing carrying assembly enables integrated assembly of single device and multi-device serial/parallel operation assembly.

Abstract: A voice enabled device can assist a computing device, such as a server, in processing/analyzing a voice input. The voice enabled device can initiate a network communication session and transmit the voice input to the computing device. The computing device can classify the voice input as a type of communication session (e.g., conversation, etc . . . ). Based on the type of communication session, the computing device can either remain in communication with the voice enabled device and continue to process voice input or terminate the communication after instructing the voice enabled device to process the voice input.

Abstract: Provided are methods and systems for intelligent content controls. A command may be received during presentation of content. The command may be time-driven, context-driven, or a combination of both. An end boundary may be determined based on a duration of time and/or one or more words of the command. Presentation of the content may be terminated at a nearest content transition with respect to the end boundary.

Abstract: An in-situ photocatalysis monitoring system based on surface-enhanced Raman Scattering (SERS) spectroscopy. The monitoring system may include a Raman excitation light source, a laser coupling lens, a narrow band filter, a total reflection mirror, a dichroic mirror, a focusing coupling lens, a SERS optical fiber probe, a liquid phase photocatalysis reactor, a photocatalytic light source, a Raman collection lens, and a spectrometer. A first furcation part and a second furcation part each extend from one end of a common detection part of the SERS optical fiber probe; an extending end of the first furcation part is coupled with the focusing coupling lens; an extending end of the second furcation part is coupled with the photocatalytic light source; and the other end of the common detection part is arranged inside the liquid phase photocatalysis reactor. Raman excitation light and photocatalytic light may be transmitted on a common channel.

Abstract: An in-situ photocatalysis monitoring system based on surface-enhanced Raman Scattering (SERS) spectroscopy. The monitoring system may include a Raman excitation light source, a laser coupling lens, a narrow band filter, a total reflection mirror, a dichroic mirror, a focusing coupling lens, a SERS optical fiber probe, a liquid phase photocatalysis reactor, a photocatalytic light source, a Raman collection lens, and a spectrometer. A first furcation part and a second furcation part each extend from one end of a common detection part of the SERS optical fiber probe; an extending end of the first furcation part is coupled with the focusing coupling lens; an extending end of the second furcation part is coupled with the photocatalytic light source; and the other end of the common detection part is arranged inside the liquid phase photocatalysis reactor. Raman excitation light and photocatalytic light may be transmitted on a common channel.

Abstract: A remote SERS spectrum detection system and a method thereof. The system includes: a pulsed laser light source, configured to emit Raman excitation light; an optical fiber Raman coupling module, configured to couple the Raman excitation light; the optical fiber Raman probe, configured to transmit the Raman excitation light to an object to be measured to generate a SERS signal light, a backscattered SERS signal light being coupled to a monochromator through the optical fiber Raman coupling module; the monochromator, configured to split the backscattered SERS signal light, to obtain backscattered SERS signal lights at different wavelengths; a high-speed photodetector, configured to convert the backscattered SERS signal lights into time-resolved electrical signals; a processor, for analyzing electrical signals, retrieving a SERS spectrum of the remote object to be measured, and controlling automatic scanning of a grating in the monochromator to achieve clock synchronization.

Abstract: Methods, systems, and/or apparatuses are described for detecting relevant motion of objects of interest (e.g., persons and vehicles) in surveillance videos. As described herein input data based on a plurality of captured images and/or video is received. The input data may then be pre-processed and used as an input into a convolution network that may, in some instances, have elements that perform both spatial-wise max pooling and temporal-wise max pooling. Based on The convolution network may be used to generate a plurality of prediction results of relevant motion of the objects of interest.

Abstract: A method for detecting structural defects includes generating a first probabilistic map of a critical location of a structural component based on a physics model of the critical location, capturing data of the critical location, generating a second probabilistic map based on an analysis of the captured data of the critical location, aligning the first probabilistic map and the second probabilistic map, combining the aligned first and second probabilistic maps, and determining if the structural component includes a structural defect based on the combined probabilistic maps.

Abstract: A method of performing context-based autonomous perception is provided. The method includes acquiring perception sensor data as an image by an autonomous perception system that includes a processing system coupled to a perception sensor system. Feature extraction is performed on the image by the autonomous perception system. The feature extraction identifies one or more features in the image. Contextual information associated with one or more conditions present upon acquiring the perception sensor data is determined. One or more labeled reference images are retrieved from at least one of a contextually-indexed database based on the contextual information, a feature-indexed database based on at least one of the features extracted, and a combined contextually- and feature-indexed database. The image is parsed, and one or more semantic labels are transferred from the one or more labeled reference images to form a semantically labeled version of the image.

Abstract: A cache associated with a voice recognition engine may be configured to receive an audio file corresponding to a voice query. The voice query may be received by the voice recognition engine from a user device in response to receipt of the voice query by the user device at the user device. The cache may be configured to determine an audio fingerprint based on the audio file and to determine whether the audio fingerprint corresponds to one of a plurality of audio transcriptions stored in the cache. The audio transcriptions may correspond to popular voice queries received at the voice recognition engine and processed by a server capable of performing automated speech recognition. In response to determining that the audio fingerprint corresponds to a given one of the stored audio transcriptions, the audio file may be processed based on the stored audio transcription.

Abstract: Methods, systems, and apparatuses for predicting an end of a command in a voice recognition input are described herein. The system may receive data comprising a voice input. The system may receive a signal comprising a voice input. The system may detect, in the voice input, data that is associated with a first portion of a command. The system may predict, based on the first portion and while the voice input is being received, a second portion of the command. The prediction may be generated by a machine learning algorithm that is trained based at least in part on historical data comprising user input data. The system may cause execution of the command, based on the first portion and the predicted second portion, prior to an end of the voice input.