Abstract: A method for anonymizing images for use in training learning models used in healthcare observation, wherein the images can be used as input data for the learning models, includes steps of collecting a real-time image from an image capturing device, analyzing the real-time image to identify specific regions of the real-time image that contain identifying information, determining physical characteristics of the specific regions, anonymizing the specific regions to obfuscate the identifying information to define an anonymized savable image that includes anonymized replicas of the physical characteristics of the specific regions, and storing the anonymized savable image within a database.

Abstract: A patient monitoring system includes a camera that selectively delivers a video feed to a monitoring station. A processor evaluates the video feed, and converts the video feed into a plurality of data points for an elopement detection system. The plurality of data points correspond at least to a combination of facial features and components of clothing for each person within the video feed. The processor is further configured to associate the combination of facial features and the components of clothing for each person to define a confirmed association, to identify whether the person is a patient or a non-patient, to verify the confirmed association of the patient by comparing updated data points from the video feed with the confirmed association, and to activate an alert when the confirmed association of the patient is unverified based upon a comparison with the updated data points.

Abstract: A patient monitoring system includes a camera that selectively delivers a video feed to a monitoring station. A processor evaluates the video feed, and converts the video feed into a plurality of data points for an elopement detection system. The plurality of data points correspond at least to a combination of facial features and components of clothing for each person within the video feed. The processor is further configured to associate the combination of facial features and the components of clothing for each person to define a confirmed association, to identify whether the person is a patient or a non-patient, to verify the confirmed association of the patient by comparing updated data points from the video feed with the confirmed association, and to activate an alert when the confirmed association of the patient is unverified based upon a comparison with the updated data points.

Abstract: A patient monitoring system includes a camera that selectively delivers a video feed to a monitoring station. A processor evaluates the video feed, and converts the video feed into a plurality of data points for an elopement detection system. The plurality of data points correspond at least to a combination of facial features and components of clothing for each person within the video feed. The processor is further configured to associate the combination of facial features and the components of clothing for each person to define a confirmed association, to identify whether the person is a patient or a non-patient, to verify the confirmed association of the patient by comparing updated data points from the video feed with the confirmed association, and to activate an alert when the confirmed association of the patient is unverified based upon a comparison with the updated data points.

Abstract: A live-feed video balancing system includes a peer-to-peer server network wherein each server communicates with the remaining servers of the peer-to-peer server network and each monitors corresponding performance criteria of a dedicated server of the peer-to-peer server network to define a hosting capacity for the dedicated server. The hosting capacity is communicated to the remaining servers and the servers cooperatively assess the corresponding hosting capacities from the monitoring servers to determine a potential hosting server having a first hosting capacity and the remaining servers have a range of second hosting capacities. The potential hosting server, in response to a hosting request, is placed in communication with an image capturing device that delivers the live video feed. The hosting server places the image capturing device in selective communication with the potential hosting server to deliver the live video feed to the customer terminal to define an active hosting server.