Abstract: A behavior detection platform may obtain video data of an environment including a guest and may determine a set of normal guest behaviors associated with the environment. The platform may analyze, using a first machine learning model, the video data to identify features of the guest and analyze, using a second machine learning model, the video data and the features to determine an actual guest behavior of the guest. The platform may predict, using the second machine learning model, a predicted guest behavior of the guest based on the actual guest behavior. The behavior detection platform may determine that at least one of the actual guest behavior or the predicted guest behavior is not included in the set of normal guest behaviors. The platform may cause assistance to be provided to the guest based on determining that the actual guest behavior or the predicted guest behavior are not included.

Abstract: A restraint verification platform may obtain video data video data of a passenger in a passenger seat. The restraint verification platform may analyze the video data using one or more machine learning models trained to detect passengers in passenger seats and passenger restraints of the passenger seats. The restraint verification platform may detect, using the one or more machine learning models and based on analyzing the video data, the passenger in the passenger seat and a passenger restraint of the passenger seat. The restraint verification platform may determine, based on analyzing the video data, that the passenger restraint is not properly securing the passenger. The restraint verification platform may perform an action based on determining that the passenger restraint is not properly securing the passenger.

Abstract: A restraint verification platform may obtain video data video data of a passenger in a passenger seat. The restraint verification platform may analyze the video data using one or more machine learning models trained to detect passengers in passenger seats and passenger restraints of the passenger seats. The restraint verification platform may detect, using the one or more machine learning models and based on analyzing the video data, the passenger in the passenger seat and a passenger restraint of the passenger seat. The restraint verification platform may determine, based on analyzing the video data, that the passenger restraint is not properly securing the passenger. The restraint verification platform may perform an action based on determining that the passenger restraint is not properly securing the passenger.

Abstract: A process improvement platform may receive an indication of a delay in a process and information identifying one or more candidate delay factors associated with the delay; and analyze current video data of the process using a machine learning model trained to identify different candidate delay factors that cause different delays in different processes. The platform may detect, based on analyzing the current video data, the delay and a candidate delay factor of the one or more candidate delay factors and analyze historical video data of the process to determine whether a correlation exists between the candidate delay factor and the delay. The platform may predict, based on analyzing the historical video data, that the candidate delay factor causes delays in the process; and determine, based on predicting that the candidate delay factor causes the delays, an action to be performed to mitigate subsequent delays.

Abstract: An assistance platform may analyze video data of an environment. Based on analyzing the video data, the assistance platform may recognize an individual out of a plurality of objects in the environment and may recognize a plurality of characteristics exhibited by the individual. The recognized characteristics may affect ability of the individual to respond to an event. The assistance platform may store assistance information identifying the plurality of characteristics; detect that an event has occurred in the environment; and retrieve the assistance information in response to detecting that the event has occurred. The assistance platform may determine, based on the assistance information, an action to be performed to assist the individual The assistance platform may cause the action to be performed to assist the individual; and delete the assistance information after causing the action to be performed.

Abstract: A restraint verification platform may obtain video data video data of a passenger in a passenger seat. The restraint verification platform may analyze the video data using one or more machine learning models trained to detect passengers in passenger seats and passenger restraints of the passenger seats. The restraint verification platform may detect, using the one or more machine learning models and based on analyzing the video data, the passenger in the passenger seat and a passenger restraint of the passenger seat. The restraint verification platform may determine, based on analyzing the video data, that the passenger restraint is not properly securing the passenger. The restraint verification platform may perform an action based on determining that the passenger restraint is not properly securing the passenger.

Abstract: A guest assistance platform may analyze video data of an environment that includes a liquid substance. The video data is analyzed using a machine learning model trained to detect objects in the liquid substance. The guest assistance platform may detect an individual in the liquid substance based on analyzing the video data and may determine a measure of confidence associated with detecting the individual in the liquid substance. The guest assistance platform may determine one or more confidence factors associated with detecting the individual in the liquid substance. The guest assistance platform may modify the measure of confidence using the one or more confidence factors and may determine whether the modified measure of confidence satisfies a confidence threshold. The guest assistance platform may selectively cause assistance to be provided to the individual or continue analyzing the video data based on whether the modified measure of confidence satisfies the confidence threshold.

Abstract: A behavior detection platform may obtain video data of an environment including a guest and may determine a set of normal guest behaviors associated with the environment. The platform may analyze, using a first machine learning model, the video data to identify features of the guest and analyze, using a second machine learning model, the video data and the features to determine an actual guest behavior of the guest. The platform may predict, using the second machine learning model, a predicted guest behavior of the guest based on the actual guest behavior. The behavior detection platform may determine that at least one of the actual guest behavior or the predicted guest behavior is not included in the set of normal guest behaviors. The platform may cause assistance to be provided to the guest based on determining that the actual guest behavior or the predicted guest behavior are not included.