Abstract: Systems and techniques are provided for determination of user presence and absence using WiFi connections. Reports may be received from WiFi access points in an environment. The reports may include an identifier of a WiFi device, an indication of a connection to or disconnection from a WiFi access point, a time of the connection or disconnection, and an identifier of the WiFi access point. A connection sequence for the WiFi device may be generated from the reports. Whether the WiFi device is present in or absent from the environment as of a specified time may be determined based on the connection sequence. An indication of presence for a user associated with the WiFi device may generated if the WiFi device is present in the environment. An indication of absence for the user associated with the WiFi device may be generated if the WiFi device is absent from the environment.

Abstract: Systems and techniques are provided for automation and recommendation based on device control protocols. HDMI-CEC device control data may be received from a connected electronic device that may be connected to an electronic display device. The HDMI-CEC device control data may be based on a HDMI-CEC device control signal from the electronic display device. The system may generate a control signal for a device. The control signal may be sent to the device for implementation.

Abstract: Systems and techniques are provided for anomalous path detection within cameras' fields of view. Video of the field of view of a camera in an environment may be received from the camera. A person may be detected in the video. Motion of the person in the video may be tracked to generate a motion path. Contextual data for the motion path may be received. The motion path and contextual data may be stored in a camera training data set. A camera model for the camera and the field of view may be generated by inputting the camera training data set to a machine learning system. The camera model for the camera and the field of view may be stored.

Abstract: A method for detecting a movement path in a monitored environment generates a first movement path record by collecting first node information for each of a first series of nodes including at least one of a sensor ID or a device ID, and a trigger time. The method further determines a first movement path total duration time from a difference between a time of the ending node and a time of the starting node of the first series of nodes. The method further stores the first movement path record and subsequently compares a second movement path record with the first movement path record by comparing the first node information with second node information for each of a second series of nodes of the second movement path record, and the first movement path total duration time with a second movement path total duration time.

Abstract: A method for detecting a movement path in a monitored environment generates a first movement path record by collecting first node information for each of a first series of nodes including at least one of a sensor ID or a device ID, and a trigger time. The method further determines a first movement path total duration time from a difference between a time of the ending node and a time of the starting node of the first series of nodes. The method further stores the first movement path record and subsequently compares a second movement path record with the first movement path record by comparing the first node information with second node information for each of a second series of nodes of the second movement path record, and the first movement path total duration time with a second movement path total duration time.

Abstract: Systems and techniques are provided for automation and recommendation based on device control protocols. HDMI-CEC device control data may be received from a connected electronic device that may be connected to an electronic display device. The HDMI-CEC device control data may be based on a HDMI-CEC device control signal from the electronic display device. The system may generate a control signal for a device. The control signal may be sent to the device for implementation.

Abstract: Systems and techniques are provided for anomalous path detection within cameras' fields of view. Video of the field of view of a camera in an environment may be received from the camera. A person may be detected in the video. Motion of the person in the video may be tracked to generate a motion path. Contextual data for the motion path may be received. The motion path and contextual data may be stored in a camera training data set. A camera model for the camera and the field of view may be generated by inputting the camera training data set to a machine learning system. The camera model for the camera and the field of view may be stored.

Abstract: Systems and techniques are provided for determination of user presence and absence using WiFi connections. Reports may be received from WiFi access points in an environment. The reports may include an identifier of a WiFi device, an indication of a connection to or disconnection from a WiFi access point, a time of the connection or disconnection, and an identifier of the WiFi access point. A connection sequence for the WiFi device may be generated from the reports. Whether the WiFi device is present in or absent from the environment as of a specified time may be determined based on the connection sequence. An indication of presence for a user associated with the WiFi device may generated if the WiFi device is present in the environment. An indication of absence for the user associated with the WiFi device may be generated if the WiFi device is absent from the environment.

Abstract: Systems and techniques are provided for automation and recommendation based on device control protocols. HDMI-CEC device control data may be received from a connected electronic device that may be connected to an electronic display device. The HDMI-CEC device control data may be based on a HDMI-CEC device control signal from the electronic display device. Signals may be received from sensor devices located in a same structure as the electronic display device. The HDMI-CEC device control data and signals from the sensor devices may be input to the machine learning system. The machine learning system may generate a control signal for a device. The control signal may be sent to the device to be implemented by the device.

Abstract: Systems and techniques are provided for anomalous path detection within cameras' fields of view. Video of the field of view of a camera in an environment may be received from the camera. A person may be detected in the video. Motion of the person in the video may be tracked to generate a motion path. Contextual data for the motion path may be received. The motion path and contextual data may be stored in a camera training data set. A camera model for the camera and the field of view may be generated by inputting the camera training data set to a machine learning system. The camera model for the camera and the field of view may be stored.

Abstract: Systems and techniques are provided for determination of user presence and absence using WiFi connections. Reports may be received from WiFi access points in an environment. The reports may include an identifier of a WiFi device, an indication of a connection to or disconnection from a WiFi access point, a time of the connection or disconnection, and an identifier of the WiFi access point. A connection sequence for the WiFi device may be generated from the reports. Whether the WiFi device is present in or absent from the environment as of a specified time may be determined based on the connection sequence. An indication of presence for a user associated with the WiFi device may generated if the WiFi device is present in the environment. An indication of absence for the user associated with the WiFi device may be generated if the WiFi device is absent from the environment.

Abstract: A radar-enabled device that manages radar interference. In particular, the radar-enabled device detects a radar signal transmitted by a second radar-enabled device, transmits a notification of the detected radar signal, receives localization information associated with the second radar-enabled device, and sets a device location based on the received localization information. Additionally, the radar-enabled device may adjust a timing of radar signal transmissions to avoid subsequent detections of radar signals transmitted by the second radar-enabled device.

Abstract: Systems and techniques are provided for automation and recommendation based on device control protocols. HDMI-CEC device control data may be received from a connected electronic device that may be connected to an electronic display device. The HDMI-CEC device control data may be based on a HDMI-CEC device control signal from the electronic display device. Signals may be received from sensor devices located in a same structure as the electronic display device. The HDMI-CEC device control data and signals from the sensor devices may be input to the machine learning system. The machine learning system may generate a control signal for a device. The control signal may be sent to the device to be implemented by the device.

Abstract: Systems and techniques are provided for determination of user presence and absence using WiFi connections. Reports may be received from WiFi access points in an environment. The reports may include an identifier of a WiFi device, an indication of a connection to or disconnection from a WiFi access point, a time of the connection or disconnection, and an identifier of the WiFi access point. A connection sequence for the WiFi device may be generated from the reports. Whether the WiFi device is present in or absent from the environment as of a specified time may be determined based on the connection sequence. An indication of presence for a user associated with the WiFi device may generated if the WiFi device is present in the environment. An indication of absence for the user associated with the WiFi device may be generated if the WiFi device is absent from the environment.

Abstract: Systems and techniques are provided for determining arrival and departure latency for WiFi devices. Reports may be received from WiFi access points in an environment. The reports include an indication of a connection to or disconnection from one of the WiFi access points, a time of the connection or disconnection, and an identifier of the one of the WiFi access points. Data including connect times and disconnect times may be generated from the reports. Sensor and device data may be received from one or more sensors or devices in the environment. Data indicating a length of an arrival latency and a length of a departure latency for the environment may be generated with a machine learning system, where the data including connect times and disconnect times and the sensor and device data is input to the machine learning system.

Abstract: Systems and techniques are provided for presence and directional motion detection. Signals may be received from a sensor positioned in a structure. An indication of directional motion may be generated based on the signals from the sensor. The indication of directional motion may be generated without using signals from additional sensors. A control signal for a device in the structure may be generated in response to the indication of directional motion. The control signal may be sent to the device in the structure to be implemented by the device.

Abstract: Systems and techniques are provided for presence and directional motion detection. Signals may be received from a sensor positioned in a structure. An indication of directional motion may be generated based on the signals from the sensor. The indication of directional motion may be generated without using signals from additional sensors. A control signal for a device in the structure may be generated in response to the indication of directional motion. The control signal may be sent to the device in the structure to be implemented by the device.

Abstract: Embodiments of techniques and systems associated with device-to-device (D2D) resource sharing are described. In some embodiments, a D2D communication channel between a first device and a second device is established and a sharing request is received at the first device, from the second device, including a credential identifying the second device. Data representative of a first resource locally available to the first device, but not locally available to the second device, is provided to the second device by the first device. Use of the first resource may be controlled in accordance with an instruction transmitted to the first device from the second device. Other embodiments may be described and/or claimed.

Abstract: Technologies for automated cropping and sharing of images include an imaging device configured to capture a digital image, recognize one or more subjects represented in the image, determine the social network groups associated with the subjects of the digital image, and crop the digital image to generate one or more sub-images. Each of the sub-images includes subjects associated with a particular social network group. Each of the sub-images may be shared with the relevant social network group. Subjects may include persons, objects, or events, and may be recognized through computer vision techniques as well as using contextual data. The imaging device may receive social network data from one or more social network servers, which may be used to determine the relevant social network groups. The imaging device may also exclude subjects from the cropped sub-images based on one or more content policies. Other embodiments are described and claimed.

Abstract: Technologies for automated cropping and sharing of images include an imaging device configured to capture a digital image, recognize one or more subjects represented in the image, determine the social network groups associated with the subjects of the digital image, and crop the digital image to generate one or more sub-images. Each of the sub-images includes subjects associated with a particular social network group. Each of the sub-images may be shared with the relevant social network group. Subjects may include persons, objects, or events, and may be recognized through computer vision techniques as well as using contextual data. The imaging device may receive social network data from one or more social network servers, which may be used to determine the relevant social network groups. The imaging device may also exclude subjects from the cropped sub-images based on one or more content policies. Other embodiments are described and claimed.