Apparatuses, methods and storage medium associated with computer-assisted or autonomous driving (CA/AD) vehicles are disclosed herein. In embodiments, CA/AD vehicles are members of a CA/AD vehicle social network (CASN) in which various CA/AD vehicles may form connections or relationships with one another. CA/AD vehicles that have an existing relationship or connection may share CASN information with one another. The CASN information may include authenticated and/or proprietary information. Other embodiments are also described and claimed.

A container, such as a suitcase, bag, cart, valise, or trunk includes various only one of its kind wheel sets combinations, including a wheel set combining both spinner wheels and inline skate wheels in the same article, wheels that extends and retracts for ultimate maneuverability in different scenarios, and utilizing powered wheels incase located at the corner or back side to provided added stability and control when tilting the container or transporting it up stairs. The container also may include advanced convenience features to include other than power assisted motion, may include telescopic handle with electronic components and various additional “high tech” options, such as built-in communication, navigation, navigation and/or direction indication capabilities, mobile phone, WiFi capabilities, USB outlet, rechargeable batteries, electronic power bank charging ports, smart locking, identification and/or tracking, and various safety features.

Disclosed are methods, systems and non-transitory computer readable memory for gesture control. For instance, a system may include a wearable device configured to be worn on a portion of an arm of a user. The wearable device may include a plurality of electrodes disposed on an interior of the wearable device and configured to obtain biopotential signals from the user's arm; and a biopotential chip. The biopotential microchip may be configured to output, directly or indirectly, biopotential data, acceleration data, and/or angular rate data, or derivatives thereof (“gesture data”), to a machine learning classifier. The machine learning classifier may be configured to generate, based on the gesture data, a gesture output indicating a gesture performed by the user. In some cases, the plurality of electrodes may include one or more wristband electrodes and/or a plurality of hub electrodes in a hub. In some cases, the hub may be curved.

Methods and devices useful in performing precise indoor localization and tracking are provided. By way of example, a method includes locating and tracking, via a first wireless electronic device, a plurality of other wireless electronic devices within an indoor environment. Location ambiguity mitigation is performed using characteristics of signals received by a reference node used to generate a radio frequency map of electronic devices.

A method for communication between autonomous vehicles and personnel can include receiving a signal from a remote computing system, the signal based upon a position of an autonomous vehicle and a first position of a mobile device, wherein the signal identifies that the mobile device is located in a path of the autonomous vehicle, responsive to receipt of the signal from the remote computing system, stopping the autonomous vehicle, receiving an updated signal from the remote computing system, the updated signal based upon a second position of the mobile device, the second position effective to facilitate a determination that the mobile device is no longer within the path of the autonomous vehicle, and responsive to receiving the updated position of the mobile device, resuming operation of the autonomous vehicle along the path. An autonomous vehicle and non-transitory computer-readable medium is also provided.

Methods for providing track condition information include receiving, at a first mobile track control station, a track condition notification. Such methods further include transmitting, from the first mobile track control station to a second mobile track control station in a network of mobile track control stations, the track condition notification. Such methods further include receiving, at the first mobile track control station from a third mobile track control station, affected track sector data regarding an affected track sector. Such methods further include transmitting, from the first mobile track control station to a first mobile track information station within a first vehicle, the affected track sector data, wherein the affected track sector data is configured to be used by the first mobile track information station to determine whether the first vehicle is within the affected track sector.

In aspects of environment dead zone determination based on UWB ranging, a system includes ultra-wideband (UWB) radios associated with respective devices in an environment. An automation controller receives UWB ranging data from the UWB radios, and can monitor locations of the respective devices in the environment. The automation controller can detect a loss of coverage by a device connected in the environment, and determine a coverage dead zone within the environment at the location of the loss of coverage by the device based on the UWB ranging data. A computing device can implement the automation controller that receives the UWB ranging data from the UWB radios, and monitors the locations of the respective devices in the environment. The automation controller can detect the loss of coverage by the device, and determine the coverage dead zone within the environment at the location of the loss of coverage by the device.

Creating and using device orientation fingerprints can include detecting a request to create an orientation fingerprint for a user device, where the orientation fingerprint defines an orientation of the user device and includes a machine learning model that models, for the user device and a known user of the user device, multiple orientations of the device for multiple activities. Operational data that includes orientation data, identity data, and activity data can be obtained. The operational data can be provided to machine learning to output the orientation fingerprint and the orientation fingerprint can be stored with data that associates the orientation fingerprint with the known user.

A verification system implements technical solutions for verifying the delivery of messages transmitted by mobile communication systems and the processing of those messages. The message verification system includes a model database and verification processing circuitry configured to receive transmitter route data, receive receiver route data, determine a viewshed for a message, and compare the viewshed to the receiver route data.

Embodiments of the present invention utilize mobile devices to provide information on a user's behaviors during transportation. For example, a mobile device carried by a user can be used to detect and analyze driving behavior. The mobile device can further be used to provide alerts based on driving behavior and to encourage and track modification of driving behavior.