Abstract: A method, computer program, and computer system are provided for resource allocation for sensor-based neural networks. One or more nodes associated with an edge computing environment are identified. Data corresponding to a classification dataset is received from the identified nodes. The dataset includes a reference classification and confidence value data. A node is selected from among the identified nodes based on the selected node having a greatest confidence interval associated with the reference classification within the confidence value data. The selected node is assigned to process the classification dataset.

Abstract: An embodiment includes generating, by a first edge computing device having a sensor, a dataset based on sensor data from the sensor. The embodiment generates, by an analytics engine hosted by the first edge computing device, a classification dataset comprising a classification for the dataset and a confidence value associated with the classification. The embodiment calculates a confidence difference between the confidence value and a reference confidence value received with a reference classification from a second edge computing device. The embodiment compares the confidence difference to a difference threshold value and generates, in a case in which the confidence difference is greater than the difference threshold value, a replacement dataset as an output replacement for the classification dataset, where the replacement dataset comprises the reference classification and an indication that the confidence value is less than the reference confidence value.

Abstract: A method, apparatus, system, and computer program product for detecting and obscuring references that inadvertently disclose key events according to a user's progress through a media. A computer system ingests data from the media and conceptualizes events from the data. The computer system identifies the key events in the media based on the conceptualized events. The computer system assigns a value to each identified key event. The computer system intakes the data that tracks a progression through the media. The computer system identifies references in related content data that are associated with the key events having values that exceeds a threshold. The computer system obscures the references to the key events displayed in the related content data according to the progression through the media.

Abstract: A method, apparatus, system, and computer program product for detecting and obscuring references that inadvertently disclose key events according to a user's progress through a media. A computer system ingests data from the media and conceptualizes events from the data. The computer system identifies the key events in the media based on the conceptualized events. The computer system assigns a value to each identified key event. The computer system intakes the data that tracks a progression through the media. The computer system identifies references in related content data that are associated with the key events having values that exceeds a threshold. The computer system obscures the references to the key events displayed in the related content data according to the progression through the media.