Abstract: The present disclosure generally relates to systems and methods for creating, publishing, accessing, and sharing AR, VR, and/or XR content. In embodiments, users may collaborate in an XR environment. In embodiments, a system disclosed herein includes a backend module and a user client that permits creation and/or viewing of XR content. Embodiments enable users to create customized XR content that is published to users based on predetermined times and/or locations. Embodiments provide for training and collaborative XR environments accessed by multiple users simultaneously.

Abstract: The present disclosure generally relates to systems and methods for creating, publishing, accessing, and sharing AR, VR, and/or XR content. In embodiments, users may collaborate in an XR environment. In embodiments, a system disclosed herein includes a backend module and a user client that permits creation and/or viewing of XR content. Embodiments enable users to create customized XR content that is published to users based on predetermined times and/or locations. Embodiments provide for training and collaborative XR environments accessed by multiple users simultaneously.

Abstract: Aspects of the present disclosure provide a network control center that coordinates candidate vehicles suited for platooning based at least in part on the hours of service (HOS) requirements, customer constraints, and service time of each candidate vehicle. Further, the network control center may integrate a navigation system that incorporates one or more of the above factors to manage logistics associated with platooning vehicles.

Abstract: Aspects of the present disclosure provide a network control center that coordinates candidate vehicles suited for platooning based at least in part on the hours of service (HOS) requirements, customer constraints, and service time of each candidate vehicle. Further, the network control center may integrate a navigation system that incorporates one or more of the above factors to manage logistics associated with platooning vehicles.

Abstract: The present disclosure generally relates to systems and methods for creating, publishing, accessing, and sharing AR, VR, and/or XR content. In embodiments, users may collaborate in an XR environment. In embodiments, a system disclosed herein includes a backend module and a user client that permits creation and/or viewing of XR content. Embodiments enable users to create customized XR content that is published to users based on predetermined times and/or locations. Embodiments provide for training and collaborative XR environments accessed by multiple users simultaneously.

Abstract: Aspects of the present disclosure provide a network control center that coordinates candidate vehicles suited for platooning based at least in part on the hours of service (HOS) requirements, customer constraints, and service time of each candidate vehicle. Further, the network control center may integrate a navigation system that incorporates one or more of the above factors to manage logistics associated with platooning vehicles.

Abstract: Aspects of the present disclosure provide a network control center that coordinates candidate vehicles suited for platooning based at least in part on the hours of service (HOS) requirements, customer constraints, and service time of each candidate vehicle. Further, the network control center may integrate a navigation system that incorporates one or more of the above factors to manage logistics associated with platooning vehicles.

Abstract: The online tutoring method and system selects a best available tutor and establishes an interactive learning environment for the student. The automated selection process uses a weighting system to incorporate numerous factors from and about the student and tutors. Upon receipt of a request for tutoring from a student, the matching processes is performed and a tutor is selected. Information about the participating tutors, such as proficiency in the subject matter and qualifications with respect to particular age groups, are quantified and associated with competency criteria. Information about the student, such as the type of assistance required and the student's education level are quantified and associated with request criteria that corresponds to the competency criteria. The weighting system combines the quantified information associated with the criteria to select best tutor. The weighting system may further include objective relative weights, input from the student's parent, and/or tutor certifications.