Abstract: A system for controlling operation of a vehicle includes a controller having a processor and tangible, non-transitory memory on which instructions are recorded. The vehicle includes an aerodynamic assembly with a wing. A passive deployment mechanism is adapted to control a respective position of the wing. The controller is adapted to trigger an actuator in the passive deployment mechanism to move the wing from a deployed position to a retracted position based in part on sensor data. The controller is adapted to determine an actual value of a designated parameter and an expected value of the designated parameter. The controller is adapted to determine an offset factor between the actual value and the expected value and whether the offset factor exceeds a first error threshold. Operation of the vehicle is controlled when the first error threshold is exceeded, including selective execution of a remedial action.

Abstract: Methods, devices, and systems for providing a centralized access control system. A method includes receiving, at a control policy database, control policies for devices registered with the system. A machine learning engine updates the control policies to include websites identified by the machine learning engine as malicious. The system receives a request for access by a registered device using one of the multiple access platforms, determines a control policy for the registered device based on a variety of parameters including an access platform type of the multiple access platforms, and sends an access decision based on the determined control policy to an access device associated with the access platform type.

Abstract: Data is collected at access points about mobile communications systems, e.g., vehicles, use of access points and the quality of the connections that are provided. The collected information is provided to a machine learning access point (MLAP) model training device that generates one or more MLAP prediction models with each model corresponding to a geographic area in which access points are located. Vehicles provide location, acceleration and/or other information, such as a user entered destination. A vehicle request for an AP recommendation includes this information which allows the AP prediction engine to predict a path of travel. The MLAP prediction engine uses the stored models and/or information about AP loading, to predict what AP a vehicle requesting an AP recommendation should attach to next. The predicted AP is returned as a handoff recommendation along with the location and/or time the vehicle should initiate the handoff to the recommended AP.

Abstract: A wireless system as discussed herein includes a communication management resource configured to control flows of data through a first wireless access point to a remote network. To control the flows of data, the communication management resource receives a schedule indicating a pattern of multiple mobile communication devices associated with a subscriber domain. The schedule may indicate a respective pattern associated with the multiple mobile communication devices. For example, the respective pattern may indicate times when the multiple mobile communication devices are present in the subscriber domain and/or times when the communication devices communicate through the first wireless access point to one or more destination in a remote network. The communication management resource utilizes the schedule to control priority of conveying communications from the multiple mobile communication devices through the first wireless access point to the remote network.

Abstract: A communication management resource associated with a mobile communication device establishes wireless connectivity between the mobile communication device and multiple wireless networks. The wireless connectivity includes multiple wireless communication links. The communication management resource determines a respective latency associated with conveyance of communications over the multiple wireless communication links. Based on the respective latencies, the communication management resource or other suitable entity selects a wireless communication link from the multiple wireless communication links in which to support communications between the mobile communication device and a remote management entity.

Abstract: A mobile device determines that the mobile device is in a wireless off mode, the wireless off mode comprising a mode wherein the mobile device does not automatically connect to a wireless access point (WAP) to which the mobile device has previously connected. The mobile device determines that the mobile device is in proximity to a first WAP to which the mobile device has previously connected. The mobile device connects to the first WAP. The mobile device discovers a first output device connected to the first WAP, and establishes with the first output device a peer-to-peer wireless connection.

Abstract: A head-mounted display device (HMDD) operable to provide extended-reality (XR) services is provided. The HMDD includes a display, adjustable lenses that include an active medium proximate the display, a memory, and a processor device coupled to the memory. The processor device is operable to determine a visual acuity metric associated with a user and, based on the visual acuity metric associated with the user, adjust an optical characteristic of the adjustable lenses, such as refractive index, lens curvature, and/or the like. In some examples, the adjustable lenses are electro-optical lenses comprising an active liquid crystal medium that is operable to adjust an optical characteristic associated therewith in response to applied electrical stimuli. In some examples, the adjustable lenses are opto-mechanical lenses comprising an active fluid medium within a flexible membrane that is operable to adjust an optical characteristic associated therewith in response to applied mechanical stimuli.

Abstract: A method for selectively providing Internet service to UEs by a company that functions as both a cellular service provider and an Internet service provider (ISP). In some embodiments, a request from a UE is received for Internet access via a non-cellular (e.g., WiFi) network, wherein the request identifies the UE's MAC address. If the UE has a SIM module, then the UE's IMEI/IMSI number is requested, received, and used to determine whether the UE is associated with a cellular service subscriber of the company. If so, then the Internet access via the non-cellular network is permitted; otherwise, the Internet access is denied. In this way, the company's ISP service can be restricted to its cellular service subscribers.

Abstract: Vehicles having WiFi and Bluetooth capabilities, e.g., parked in a garage, establish a wireless network architecture in which a first vehicle has access to the outside world via a direct WiFi connection to a WiFi access point (AP) and one or more other vehicles have access to the outside world via one or more vehicle-to-vehicle Bluetooth connections and the first vehicle's direct WiFi connection. In this way, all of the vehicles have outside-world access even when most of the vehicles have no direct WiFi access, thereby enabling all of the vehicles to access the outside world using WiFi instead of their cellular capabilities. The WiFi equipment can orchestrate the vehicles' compute capabilities to function as individual processors of a multi-processor computer system.

Abstract: User equipment (e.g., a cell phone) assists in establishing a non-cellular wireless (e.g., WiFi) connection for a vehicle. In some embodiments, the UE provides information about the network (e.g., SSID and credential/certificate) to the vehicle for use in establishing the connection. In other embodiments, the UE secures, retains, and uses a network certificate for the vehicle to establish the connection without providing the certificate to the vehicle. The embodiments facilitate and encourage the use of non-cellular wireless connections instead of possibly more-expensive and/or resource-limited cellular connections.

Abstract: Methods and systems for optimizing data offloading in electric vehicles are described. A method includes estimating an amount of data that can be collected and generated for a route generated for a destination entered into the electric vehicle, categorizing, by a data offloading device in an electric vehicle, the estimated data into real-time, near real-time, and non-real-time data categories, determining one or more offloading stop and time based on the categorized estimated data and service provider access device information for the route; collecting real data generated by and for the electric vehicle as the electric vehicle traverses the route; categorizing the real data into the real-time, the near real-time, and the non-real-time data categories; and updating the one or more offloading stop and time based on the categorized real data and updated service provider access device information for the route.

Abstract: A system as discussed herein includes communication management hardware. The communication management hardware: receives a first data packet including a first data payload, the first data packet transmitted for delivery to a destination network address; determines a first latency classification assigned to the first data packet; assigns a second latency classification to the first data packet as a substitute to the first latency classification; and forwards the first data packet for delivery to the destination network address in accordance with the second latency classification.

Abstract: Methods and systems for smart reattachment of mobile devices to service provider networks such as WiFi networks.

Abstract: Methods and systems for optimizing data offloading in electric vehicles are described. A method includes estimating an amount of data that can be collected and generated for a route generated for a destination entered into the electric vehicle, categorizing, by a data offloading device in an electric vehicle, the estimated data into real-time, near real-time, and non-real-time data categories, determining one or more offloading stop and time based on the categorized estimated data and service provider access device information for the route; collecting real data generated by and for the electric vehicle as the electric vehicle traverses the route; categorizing the real data into the real-time, the near real-time, and the non-real-time data categories; and updating the one or more offloading stop and time based on the categorized real data and updated service provider access device information for the route.

Abstract: Methods and systems for optimizing data offloading in electric vehicles are described. A method includes estimating an amount of data that can be collected and generated for a route generated for a destination entered into the electric vehicle, categorizing, by a data offloading device in an electric vehicle, the estimated data into real-time, near real-time, and non-real-time data categories, determining one or more offloading stop and time based on the categorized estimated data and service provider access device information for the route; collecting real data generated by and for the electric vehicle as the electric vehicle traverses the route; categorizing the real data into the real-time, the near real-time, and the non-real-time data categories; and updating the one or more offloading stop and time based on the categorized real data and updated service provider access device information for the route.

Abstract: Methods and systems for train detection apparatus angle alignment is described. A train detection system includes a train detection apparatus configured for installation at an installation site at a defined angle with respect to railroad tracks and a processor configured to execute a method for aligning the train detection apparatus to the defined angle. The processor configured to determine a railroad tracks angle with respect to a reference angle based on an image captured of the installation site, obtain, from a sensor, a train detection apparatus angle with respect to the reference angle, determine an alignment angle based on the railroad tracks angle and the train detection apparatus angle, and send the alignment angle to substantially align the train detection apparatus to the railroad tracks in accordance with the defined angle.

Abstract: Data is collected at access points about mobile communications systems, e.g., vehicles, use of access points and the quality of the connections that are provided. The collected information is provided to a machine learning access point (MLAP) model training device that generates one or more MLAP prediction models with each model corresponding to a geographic area in which access points are located. Vehicles provide location, acceleration and/or other information, such as a user entered destination. A vehicle request for an AP recommendation includes this information which allows the AP prediction engine to predict a path of travel. The MLAP prediction engine uses the stored models and/or information about AP loading, to predict what AP a vehicle requesting an AP recommendation should attach to next. The predicted AP is returned as a handoff recommendation along with the location and/or time the vehicle should initiate the handoff to the recommended AP.

Abstract: Methods and apparatus for managing frequency reassignment within wireless access nodes so as to minimize data session disruption. In one embodiment, the frequency reassignments occur within a quasi-licensed system utilizing 3.5 GHz CBRS (Citizens Broadband Radio Service) spectrum, and a reassignment of wireless spectrum that mitigates disruption or loss of continuity to existing data sessions of users of devices associated with a CBSD/xNB is provided via notification of the associated devices (e.g., Category B Consumer Premises Equipment or CPE, such as an FWA) of the reassignment by the CBSD/xNB. In one variant, the associated devices are instructed by the CBSD/xNB to invoke a “wait and re-establish” protocol that obviates a full frequency band rescan in favor of a designated target frequency provided to the CBSD/xNB by the cognizant SAS or DP.

Abstract: According to one configuration, a communication management resource such as a SIM provisioning platform receives input from a mobile communication device to activate use of the mobile communication device in a private wireless network. The communication management resource authenticates use of the mobile communication device in the private wireless network. Subsequent to authentication, the communication management resource populates an access file such as private SIM (Subscriber Identity Module) information for use by the mobile communication device to access the private wireless network. The access file is populated with information such as a unique cell identifier value, encryption information, identification of supported services, etc. The communication management resource communicates the newly generated access file (such as SIM information) to the mobile communication device, enabling the mobile communication device use of the private wireless network.

Abstract: A wireless system as discussed herein includes a communication management resource configured to control flows of data through a first wireless access point to a remote network. To control the flows of data, the communication management resource receives a schedule indicating a pattern of multiple mobile communication devices associated with a subscriber domain. The schedule may indicate a respective pattern associated with the multiple mobile communication devices. For example, the respective pattern may indicate times when the multiple mobile communication devices are present in the subscriber domain and/or times when the communication devices communicate through the first wireless access point to one or more destination in a remote network. The communication management resource utilizes the schedule to control priority of conveying communications from the multiple mobile communication devices through the first wireless access point to the remote network.