Abstract: A system described herein may provide a technique for determining a measure of wear and tear on a vehicle as well as one or more actions to take, such as increased maintenance and/or particular types of maintenance or repairs. The system may maintain models associating vehicle input information with respective vehicle wear classifications, and may receive vehicle input information associated with a particular vehicle, including sensor data measured by a User Equipment (“UE”), and/or vehicle information provided by the particular vehicle. The system may compare the received particular set of vehicle input to the models and may determine, based on the comparing, a vehicle wear classification associated with the particular vehicle. The system may identify one or more actions associated with the determined one or more vehicle wear classifications; and may output, to the UE, information indicating the identified one or more actions.

Abstract: A system described herein may provide techniques for using machine learning and/or other techniques to monitor a conversation between two or more conversation participants through a messaging program. The system may utilize natural language processing (“NLP”) to determine the intent of phrases and/or words sent between mediation participants. The system may determine to take remedial measures, such as modifying, delaying, and/or rejecting a message from one of the participants when a score for the message exceeds a dynamic score threshold determined by the system based on one or more factors, such as the demographic information of the mediation participants, nature of the mediation, length of mediation, communications among mediation participants, and/or other factors.

Abstract: A system described herein may provide techniques for using machine learning and/or other techniques to monitor a conversation between two or more conversation participants through a messaging program. The system may utilize natural language processing (“NLP”) to determine the intent of phrases and/or words sent between mediation participants. The system may determine to take remedial measures, such as modifying, delaying, and/or rejecting a message from one of the participants when a score for the message exceeds a dynamic score threshold determined by the system based on one or more factors, such as the demographic information of the mediation participants, nature of the mediation, length of mediation, communications among mediation participants, and/or other factors.

Abstract: A system described herein may provide techniques for using machine learning and/or other techniques to monitor a conversation between two or more conversation participants through a messaging program. The system may utilize natural language processing (“NLP”) to determine the intent of phrases and/or words sent between mediation participants. The system may determine to take remedial measures, such as modifying, delaying, and/or rejecting a message from one of the participants when a score for the message exceeds a dynamic score threshold determined by the system based on one or more factors, such as the demographic information of the mediation participants, nature of the mediation, length of mediation, communications among mediation participants, and/or other factors.

Abstract: A system described herein may provide techniques for using machine learning and/or other techniques to monitor a conversation between two or more conversation participants through a messaging program. The system may utilize natural language processing (“NLP”) to determine the intent of phrases and/or words sent between mediation participants. The system may determine to take remedial measures, such as modifying, delaying, and/or rejecting a message from one of the participants when a score for the message exceeds a dynamic score threshold determined by the system based on one or more factors, such as the demographic information of the mediation participants, nature of the mediation, length of mediation, communications among mediation participants, and/or other factors.