Abstract: Internet of Things (IoT) systems and related methods are disclosed. A method comprises determining whether a first condition holds, the first condition being a condition of the IoT system, performing a function of the IoT system in response to a trigger, wherein the trigger is a determination that the first condition holds, recognizing a gesture based on image data received from an image sensor, and reconfiguring the IoT system for a future performance of the function based on the user feedback data.

Abstract: Systems and methods are disclosed for recognizing a multi-component gesture within a sequence of image frames. A method comprises selecting a first object model as the selected object model, wherein the first object model corresponds to a first component of the multi-component gesture, receiving a frame in the sequence of frames and analyzing the frame to determine whether the frame includes a first object that matches the selected first object model, selecting a second object model as the selected object model, wherein the second object model corresponds to a second component of the multi-component gesture, receiving at least one subsequent frame and analyzing the at least one subsequent frame to determine whether the at least one subsequent frame includes a second object that matches the selected second object model, and recognizing that the multi-component gesture is present in the sequence of image frames.

Abstract: Methods, systems, and devices for wireless communication are provided for mobility management for wireless communications systems that utilize a flexible bandwidth carrier. Some embodiments include approaches for determining bandwidth information, such as one or more bandwidth scaling factors N and/or flexible bandwidths, at a user equipment (UE), where the bandwidth information may not be signaled to the UE. Embodiments for determining bandwidth information include: random ordered bandwidth scaling factor approaches, delay ordered bandwidth scaling factor approaches, storing bandwidth scaling factor value in UE Neighbor Record approaches, spectrum measurement approaches, spectrum calculation approaches, and/or a priori approaches. Flexible bandwidth carrier systems may utilize spectrum portions that may not be big enough to fit a normal waveform.

Abstract: Techniques are presented for detecting a visual marker. A first image containing the visual marker may be captured at a first time under a first lighting condition. A first image-based detection for the visual marker may be performed based on the first image, using a first detector, to produce a first set of results. A second image containing the visual marker may be captured at a second time under a second lighting condition different from the first lighting condition. Based on the first set of results, a second image-based detection for the visual marker may be performed based on the second image, using a second detector different from the first detector, to produce a second set of results.

Abstract: Systems and methods are described herein for pairing at least one smart ring with a primary device. The primary device receives one or more identification signals having information relating to an identity of one or more smart rings. Each identification signal received from an associated one of the one or more smart rings based on motion of the associated one of the one or more smart rings with respect to the primary device. The processor of the primary device identifies the one or more smart rings based on the one or more identification signal.

Abstract: Systems and methods may enable a user who may not have any experience in machine learning to effectively train new models for use in object recognition applications of a device. Embodiments can include, for example, analyzing training data comprising a set of images to determine a set of metrics indicative of a suitability of the training data in machine-learning training for object recognition, and providing an indication of the set of metrics to a user. Additionally or alternatively, an intermediate model can be used, after a first portion of the machine-learning training is conducted, to determine the effectiveness of a remaining portion of negative samples (images without the object) in the training data or to find other negative samples outside of the training data. Identifying and utilizing effective negative samples in this manner can improve the effectiveness of the training.

Abstract: Systems and methods may enable a user who may not have any experience in machine learning to effectively train new models for use in object recognition applications of a device. Embodiments can include, for example, analyzing training data comprising a set of images to determine a set of metrics indicative of a suitability of the training data in machine-learning training for object recognition, and providing an indication of the set of metrics to a user. Additionally or alternatively, an intermediate model can be used, after a first portion of the machine-learning training is conducted, to determine the effectiveness of a remaining portion of negative samples (images without the object) in the training data or to find other negative samples outside of the training data. Identifying and utilizing effective negative samples in this manner can improve the effectiveness of the training.

Abstract: Sector-based iris authentication is disclosed. One example involves (a) capturing an image of an eye of the user, the image including an iris region, (b) identifying a plurality of sectors of the iris region within the image, (c) determining a measure of distinctiveness for each sector of the iris region, (d) selecting one or more sectors from the plurality of sectors of the iris region based on the determined measure of distinctiveness for the each sector of the iris region, the selected one or more sectors being fewer in number than the plurality of sectors of the iris region, and (e) comparing the selected one or more sectors to one or more registered iris data records.

Abstract: Use of pupillary response to visible light for iris authentication is disclosed. One example involves (a) capturing an initial image of an eye including an inner circular boundary between a pupil region and an iris region and an outer circular boundary between the iris region and a sclera region, (b) determining a first size measurement indicative of the inner circular boundary, (c) responsive to at least the first size measurement, modulating one or more visible light sources to output visible light toward the eye of the user, (d) capturing a subsequent image of the eye of the user during a period of pupillary response, (e) obtaining an iris data record of the user, and (f) comparing the iris data record of the user to one or more registered iris data records to authenticate the user.

Abstract: Sensing of scene-based occurrences is disclosed. In one example, a vision sensor system comprises (1) dedicated computer vision (CV) computation hardware configured to receive sensor data from at least one sensor array and capable of computing CV features using readings from multiple neighboring sensor pixels and (2) a first processing unit communicatively coupled with the dedicated CV computation hardware. The vision sensor system is configured to, in response to processing of the one or more computed CV features indicating a presence of one or more irises in a scene captured by the at least one sensor array, generate data in support of iris-related operations to be performed by a second processing unit and send the generated data to the second processing unit.

Abstract: An example method may include receiving, by a computing device, control plane signaling associated with a first service to be performed by a first communication device, wherein the computing device is within a radio access network (RAN) and is in limited communication with a core network via a backhaul connection that is constrained due to a backhaul bottleneck condition. The example method may include conditionally permitting, by the computing device, a first feature of the first service based at least in part on the backhaul bottleneck condition. Another example method may include receiving, by a computing device, control plane signaling associated with a service to be performed by a first communication device, wherein the computing device is within a RAN and is in limited communication with a core network via a backhaul connection that is constrained due to a backhaul bottleneck condition.

Abstract: An example method includes determining an operating context of a small cell, wherein a base station of the small cell is co-located with an edge computing device. The method may further retrieving content from a network to the edge computing device based at least in part on the operating context and storing the content at the edge computing device for subsequent access by a mobile device in the small cell.

Abstract: Methods, systems, computer-readable media, and apparatuses for image processing and utilization are presented. In some embodiments, an image containing at a face of a user may be obtained using a mobile device. An orientation of the face of the user within the image may be determined using the mobile device. The orientation of the face of the user may be determined using multiple stages: (a) a rotation stage for controlling a rotation applied to a portion of the image, to generate a portion of rotated image, and (b) an orientation stage for controlling an orientation applied to orientation-specific feature detection performed on the portion of rotated image. The determined orientation of the face of the user may be utilized as a control input to modify a display rotation of the mobile device.

Abstract: Certain aspects of the present disclosure generally relate to determining proximity based on image blurriness. In some aspects, a device may analyze an image sensed by an image sensor of the device. The device may determine a metric based on analyzing the image. The metric may provide an indication of a blurriness or a sharpness of the image. The device may determine, based on the metric, a measure of proximity associated with the image.

Abstract: The present disclosure describes various techniques to provide network access to a user equipment by using network infrastructure and/or wireless spectrum from an asset operator. In an aspect, a network device associated with the asset operator may receive a request for wireless wide area network (WWAN) access for a UE. The network device may identify the UE as a subscriber of an operator based at least in part on the request, where the operator is different from the asset operator, and where the network device is configured to provide WWAN access to subscribers of the operator via a core network associated with the operator based at least in part on a services agreement between the operator and the asset operator. The network device may then provide WWAN access to the UE in response to identifying that the UE is a subscriber of the operator.

Abstract: The disclosure provides various methods and apparatus useful for mapping wireless nodes using a drone and aligning the body of the drone with an antenna of the wireless node. A method includes mapping, by an apparatus, a space including one or more locations of one or more wireless nodes, determining whether the apparatus is in proximity to a first wireless node of the one or more wireless nodes, determining an orientation of an antenna of the first wireless node, and in response to determining that the apparatus is in proximity to the first wireless node and determining the orientation of the antenna of the first wireless node, adjusting a six-degree-of-freedom (6DoF) orientation of the apparatus based on the determined orientation of the antenna of the first wireless node. The apparatus may be an autonomous drone.

Abstract: A small cell may include a base station that may be co-located with an edge computing device. The edge computing device may be integrated within a small cell base station or be a physically separate module communicatively coupled to and in close proximity with the small cell base station that provides edge computing resources at the small cell. The edge computing device may communicate with input/output devices that are in hyper proximity to the small cell base station. The input/output devices may be capable of sensing aspects of the environment (e.g., via microphones, light sensors, cameras, thermometers, etc.) and providing a stimulus to an individual within hyper proximity to the input-output devices. The stimulus may be in response to or based on the environmental information gathered by the input-output devices.

Abstract: The present disclosure describes various techniques to provide network access to a user equipment by using network infrastructure and/or wireless spectrum from an asset operator. In an aspect, a network device associated with the asset operator may receive a request for wireless wide area network (WWAN) access for a UE. The network device may identify the UE as a subscriber of an operator based at least in part on the request, where the operator is different from the asset operator, and where the network device is configured to provide WWAN access to subscribers of the operator via a core network associated with the operator based at least in part on a services agreement between the operator and the asset operator. The network device may then provide WWAN access to the UE in response to identifying that the UE is a subscriber of the operator.

Abstract: Aspects of the present disclosure provide a scheduling entity and methods of operating the scheduling entity such that the scheduling entity reconfigures/allocates its resources based on device capabilities of the wireless devices. The scheduling entity utilizes a first resource configuration to provide communications service to one or more wireless devices associated with the scheduling entity. The scheduling entity determines a change of the one or more wireless devices, wherein the change include at least one of a capability change of a wireless device, a quality of service (QoS) requirement change of a wireless device, an addition of a wireless device, or a removal of a wireless device. Based on at least one of a predetermined time of a day or the determined change, the scheduling entity reconfigures to a second resource configuration to facilitate resource utilization of the first wireless cell.

Abstract: Apparatuses, methods, and systems are presented for reacting to scene-based occurrences. Such an apparatus may comprise dedicated computer vision (CV) computation hardware configured to receive sensor data from a sensor array comprising a plurality of sensor pixels and capable of computing one or more CV features using readings from neighboring sensor pixels of the sensor array. The apparatus may further comprise a first processing unit configured to control operation of the dedicated CV computation hardware. The first processing unit may be further configured to execute one or more application programs and, in conjunction with execution of the one or more application programs, communicate with at least one input/output (I/O) device controller, to effectuate an I/O operation in reaction to an event generated based on operations performed on the one or more computed CV features.