Abstract: A cloud computing server includes a memory, a processor, and a communication unit. The memory is configured to store a plurality of activities, a plurality of actions, and an association model that associates the plurality of activities with the plurality of actions. The processor is configured to determine an activity from the plurality of activities by determining a similarity between an upcoming activity and one of the plurality of activities and identify an action based on the activity and the association model. The communication unit is configured to transmit the identified action to a user equipment (UE).

Abstract: A digital handwriting system that includes an electronic device and a method of using the same. The present disclosure teaches a method that includes identifying content stored on the electronic device to be projected onto a surface; identifying occurrence of a touch event of an accessory; capturing an image of the touch event to determine initial position data indicating an initial position of the accessory relative to the projected content; receiving movement tracking data indicating movement of the accessory; and updating the content using the initial position data and the movement tracking data. Various embodiments may further include using an inertial movement unit (IMU) disposed in an electronic accessory for determining movement tracking data of the accessory. Moreover, updating the content may include updating the projected content in real-time.

Abstract: A method for collecting diagnostic data in a wireless communication network. The method comprises storing previously measured results of the diagnostic data for improving quality of the wireless communication network, determining a spatiotemporal correlation model based on the previously measured results of the diagnostic data in accordance with a data collection strategy, and collecting new diagnostic data based on the determined spatiotemporal correlation model and the data collection strategy.

Abstract: A wireless mobile device for personalizing the control and IVI settings of a connected vehicle according to a seat position of a user of the mobile device. The wireless mobile device is configured to: i) receive a radio signal from each of a plurality of beacons in the vehicle; ii) determine a received signal strength indicator (RSSI) value for each received radio signal; iii) apply a seat prediction model M to the RSSI value for each received radio signal to predict a seat position P; and iv) transmit a predicted seat position P to a server. The seat prediction model M is generated by a machine learning process and stored in a server. A beacon array configuration, data collection and generalization procedure optimizes the coverage and accuracy of the model M. The wireless mobile device is further configured to receive an identification (ID) value of the vehicle. The wireless mobile device retrieves the seat prediction model M from the server and caches in memory in the wireless mobile device.

Abstract: An embodiment of this disclosure provides an apparatus including a communications unit and at least one processor. The communications unit is configured to communicate with a client device in the system. The at least one processor is coupled to the communications unit. The at least one processor configured to monitor a rule in the system. The rule controls the client device. The at least one processor is also configured to, responsive to the rule for the client device being triggered, determine whether an anomaly exists in the system. The at least one processor is also configured to, response to the anomaly existing, determine whether an override action is available for the anomaly. The at least one processor is also configured to, responsive to the override action being available, override the rule.

Abstract: A method, system, and vehicle for locating an occupant within the vehicle. The method includes receiving motion data of a seatbelt for a seat in the vehicle and receiving motion data of a wearable device of the occupant. The method also includes comparing the seatbelt motion data with the wearable device motion data from a same period of time and identifying that the occupant is located at the seat in the vehicle based on a result of the comparison. The method may also include associating the occupant with the vehicle based on location information of the vehicle and location information of the wearable device of the occupant. Additionally, the method may include identifying personalization options for the occupant at the seat based on a user profile of the occupant in response to identifying that the occupant is located at the seat.

Abstract: A method, apparatus, and computer readable medium for managing a voice call in a wireless communication network. The method comprises collecting crowd-sourced data for a voice over long-term evolution (VoLTE) call quality metrics and contexts associated with a VoLTE call. The VoLTE call quality metrics and contexts comprise non-device information and device information. The method further comprises identifying accessible information based on the device information and the non-device information, predicting VoLTE call quality using the collected crowd-sourced data and the accessible information, and determining whether to place the voice call as or switch the voice call to a VoLTE call or a circuit-switched voice call based on comparison of the predicted VoLTE quality to a predetermined threshold.

Abstract: A system, apparatus, and method for managing applications as Internet of Things (IoT) objects includes an IoT server, a computing device, and an IoT application. The IoT server and the computing device communicate via a network. The computing device has an IoT interface and an IoT-enabled application with an RPC interface. The IoT interface uses the RPC interface to communicate with the IoT-enabled application. The IoT interface communicates with the IoT server or the IoT application using an IoT protocol. The IoT interface operates the IoT-enabled application as an IoT device in the system.

Abstract: A wireless mobile device for personalizing the control and IVI settings of a connected vehicle according to a seat position of a user of the mobile device. The wireless mobile device is configured to: i) receive a radio signal from each of a plurality of beacons in the vehicle; ii) determine a received signal strength indicator (RSSI) value for each received radio signal; iii) apply a seat prediction model M to the RS SI value for each received radio signal to predict a seat position P; and iv) transmit a predicted seat position P to a server. The seat prediction model M is generated by a machine learning process and stored in a server. A beacon array configuration, data collection and generalization procedure optimizes the coverage and accuracy of the model M. The wireless mobile device is further configured to receive an identification (ID) value of the vehicle. The wireless mobile device retrieves the seat prediction model M from the server and caches in memory in the wireless mobile device.

Abstract: A payment server configured to share payments among occupants of a vehicle. The payment server receives a payment request comprising a payment amount and a vehicle identification, accesses a database record associated with the vehicle identification, the record including an identification and seat position of each vehicle occupant as determined from a mobile device of each occupant, and identifies the vehicle driver. The server transmits to an in-vehicle infotainment (IVI) system a first billing message associated with the payment request, the IVI system displaying the first billing message on a screen of an IVI head unit. The first billing message offers the driver an option to share the payment amount with a second occupant of the vehicle.

Abstract: A wireless mesh network enables multiple devices near each other to transmit simultaneously, thus allowing increased network bandwidth. Prior to transmitting, a device may determine various parameters of the wireless medium on which it desires to transmit. For example, the device may determine whether the intended recipient device is close enough, and verify that any other transmitting and receiving devices are far enough away. If these or any other suitable criteria are met, the device can transmit simultaneously with other devices in the vicinity.

Abstract: An apparatus and method for generating an alert on a mobile terminal based on signal strength of the mobile terminal are provided. The method includes measuring a signal strength with which the mobile terminal communicates with a network, determining whether the measured signal strength is less than a predefined signal strength threshold, and if the measured signal strength is less than the predefined signal strength threshold, generating an alert indicating that the signal strength of the mobile terminal is low.

Abstract: A wireless mesh network enables multiple devices near each other to transmit simultaneously, thus allowing increased network bandwidth. Prior to transmitting, a device may determine various parameters of the wireless medium on which it desires to transmit. For example, the device may determine whether the intended recipient device is close enough, and verify that any other transmitting and receiving devices are far enough away. If these or any other suitable criteria are met, the device can transmit simultaneously with other devices in the vicinity.