Abstract: A system for utilizing digital forensics, artificial intelligence, and machine learning models to prevent suicidal behavior is disclosed. In particular, the system extracts data from devices associated with individuals that have died by suicide. The system applies intelligence techniques to collect additional data from third-party data aggregators and to collect online identities associated with the deceased individuals. The system may process the data from the devices, the additional data, and the online identities into datasets to be combined into a data lake. By utilizing artificial intelligence and/or machine learning algorithms on the data lake, the system generates a model associated with predictive behavior and patterns correlated with suicide. The system identifies individuals having characteristics and/or behaviors correlated with the model, and initiates services to reduce the risk for suicide for such individuals. The effectiveness of such services may also be determined by the system.

Abstract: Image recording apparatuses that permit the recording of multiple images in different directions are generally disclosed herein. In some embodiments, such apparatuses have two or more image sensors that can be disposed at disparate locations from each other and from the controller and the power supply, thereby allowing for a more distributed physical configuration and a lower profile when disposed on a hat, helmet, or other headgear. In some such embodiments, the image sensors of the recording apparatus are configured to be disposed at disparate locations on a head covering device, such as a hat or helmet. In some aspects, the image recording apparatuses can be incorporated into a system for panoramic (e.g., 360°) image recording. Uses of such apparatuses and systems are also disclosed herein.