Abstract: A system and method for artificial intelligence (AI) based skill tracking and non-fungible token (NFT) based skill/behavior representation are provided. The system acquires information associated with a non-tangible asset of a user in an online environment, apply an artificial intelligence (AI) model on the acquired information, wherein the AI model is trained to evaluate the non-tangible asset and track a progress of acquisition of the non-tangible asset in the online environment. The system determines a proficiency level of a plurality of proficiency levels of the non-tangible asset of the user based on the application of the AI model on the acquired information. The system assigns, based on the determined proficiency level of the non-tangible asset of the user, a value to a digital token associated with the user. The digital token may include a non-transferable part unique to the user and a fungible part that may be exchangeable across platforms.

Abstract: A mobility player system including memory and a processor is provided. The memory stores a trained AI model. The processor receives on-board diagnostic (OBD) data associated with a first vehicle registered with a first mobility provider. The processor receives occupant data, different from the OBD data, from plurality of sensors associated with the first vehicle. The processor determines a plurality of parameters based on the received OBD data and the received occupant data. The processor applies the trained AI model on the plurality of parameters. The processor determines one or more events related to the first vehicle, or related to an occupant of the first vehicle, based on the application of the trained AI model on the plurality of parameters. The processor transmits information about the determined one or more events to one or more nodes of a distributed ledger associated with a Mobility-as-a-Service (MaaS) network.

Abstract: A system and method to provide a conversational user experience for a multimodal travel system is provided. The system controls an electronic device associated with a user to render a User Interface (UI). Through the UI, one or more messages that includes a natural language input from the user are acquired. The system also acquires user data. The acquired one or more messages are processed using one or more natural language processing (NLP) models to determine contextual information which indicates an intent of the user to travel to a location and a schedule associated with the travel. Based on the contextual information and the user data, the system generates a travel plan. The system triggers a mobility-as-a-service (MaaS) network to generate booking details for a trip specified in the travel plan and controls the electronic device to display the generated booking details onto the UI.

Abstract: A mobility player system including memory and a processor is provided. The memory stores a trained AI model. The processor receives on-board diagnostic (OBD) data associated with a first vehicle registered with a first mobility provider. The processor receives occupant data, different from the OBD data, from plurality of sensors associated with the first vehicle. The processor determines a plurality of parameters based on the received OBD data and the received occupant data. The processor applies the trained AI model on the plurality of parameters. The processor determines one or more events related to the first vehicle, or related to an occupant of the first vehicle, based on the application of the trained AI model on the plurality of parameters. The processor transmits information about the determined one or more events to one or more nodes of a distributed ledger associated with a Mobility-as-a-Service (MaaS) network.

Abstract: A system and method for playback control of media content across devices in a MaaS transportation network is provided. The system receives, from a MaaS network, trip details of an ongoing trip and determines a first vehicle by which a user is set to complete an active first leg of the ongoing trip. The system generates media content recommendations based on the trip details and controls a first display device in use inside the first vehicle, to display such recommendations. The system receives a selection of a first content recommendation and controls a playback of first media content associated with the selection on the first display device. The system detects an event which requires the playback to pause and controls the playback to resume on a second display device in use inside a second vehicle, within duration of a second leg of the ongoing trip or a different trip.