Methods and systems for mapping boundaries of a given environment by a processor of a computer system, the method comprising: determining a trajectory of the body in the given environment over the given time period; and determining, based on the trajectory of the body in the given environment, one or more of an outer boundary of the given environment, and an inner boundary of the given environment. Methods and systems for mapping functionalities of a given environment executable by a processor of a computer system, the method comprising determining a pattern of movement of a body in the given environment in a given time period; and determining a functional identity of at least one zone in the given environment based on the pattern of movement of the body to obtain a mapped given environment.

A notification control device for controlling notification based on subject information is disclosed. The subject information including temperature image data, which indicates temperature of a subject captured within a predetermined capturing range, is received. A predetermined destination of notification information, which represents a state of the subject based on the subject information, is notified. A process of notifying the notification information to the predetermined destination is stopped depending on whether or not the subject information includes predetermined identification information.

A system and method for automatically requesting assistance for a user experiencing a medical emergency is disclosed. The system includes a user device with a sensor to detect sensed information. Based on the sensed information the user device can determine if the user is experiencing a medical emergency. The user device can communicate with nearby devices over one or more networks and send information about the medical emergency to the nearby devices. The information can include the type of medical emergency, the location of the user experiencing the medical emergency, and any instructions for providing the user with assistance.

Embodiments relate to using an active reflected wave detector to classify the state of a person in an environment and optionally respond accordingly. In one embodiment there is provided a computer implemented method of determining a state of a person comprising: receiving an output of an active reflected wave detector; classifying a state of the person as being in a safe supported state based on the output using measurements of reflections associated with the person, wherein said classifying is based at least on: a height metric associated with at least one reflection from the person conveyed in the output of the active reflected wave detector; and a plurality of velocity magnitude measurements of the person corresponding to different times, each of said velocity magnitude measurements determined using the reflections associated with the person conveyed in the output of the active reflected wave detector.

Systems and methods are provided for worker protection system with ultra-wideband (UWB) based anchors. One or more wayside units placed on or near a track may be configured to form a work zone network, based on ultra-wideband (UWB) communications, corresponding to a work zone in an area surrounding or in proximity to the one or more wayside units. When the work zone network is formed, at least one wayside unit of the one or more wayside units may be configured to obtain ranging information to a train traversing the track, based on communications of UWB signals with at least one train-mounted unit deployed on the train, and the one or more wayside units are configured to generate, based on the ranging information, notifications relating to the train and/or the work zone.

Various embodiments concern a system for monitoring a patient in a bed, the system comprising a camera, a user interface comprising a screen, and a computing system. The computing system can be configured to monitor, with the camera, for motion within each of a plurality of zones, the plurality of zones comprising a one or more inner zones extending adjacent along the bed, one or more outer zones extending adjacent along the one or more inner zones, and one or more end zones. Motion within the inner zones can trigger a fall alert while motion within the outer or end zones can suspend one or more functions to prevent the fall alert from being issued. The end zones can comprise a bottom zone and one or more top zones.

A method and system for detecting a person falling, confirming a potential fall, and taking action to mitigate the effects of a fall.

A disclosed method includes receiving at least an indication of audio data generated based on sound captured by a microphone of a monitoring device. A set of audio event labels are generated by processing the received audio data with a model that includes audio recognition patterns. Each audio event label is generated by matching an audio pattern in the received audio data with an audio pattern of the audio recognition patterns. The method further includes identifying a hazard event type occurring within a time window of the time period by processing the set of audio event labels with a hazard detection model. In response to detecting the hazard event type, a hazard alert is generated and at least an indication of the hazard alert is communicated to an electronic device other than the monitoring device, which is authorized to receive communications from the monitoring device.

An embodiment in accordance with the present invention includes a technology to continuously measure patient mobility automatically, using sensors that capture color and depth images along with algorithms that process the data and analyze the activities of the patients and providers to assess the highest level of mobility of the patient. An algorithm according to the present invention employs the following five steps: 1) analyze individual images to locate the regions containing every person in the scene (Person Localization), 2) for each person region, assign an identity to distinguish ‘patient’ vs. ‘not patient’ (Patient Identification), 3) determine the pose of the patient, with the help of contextual information (Patient Pose Classification and Context Detection), 4) measure the degree of motion of the patient (Motion Analysis), and 5) infer the highest mobility level of the patient using the combination of pose and motion characteristics (Mobility Classification).

System and method of deploying a trained machine learning neural network (MLNN) in generating a fall injury condition of a subject. The method comprises receiving, at input layers of the trained MLNN, millimeter wave (mmWave) radar point cloud data representing fall attributes from monitoring the subject via mmWave radar sensing device, the input layers associated with the fall attributes, receiving, at a second set of input layers, personal attributes of the subject associated with ones of the second set of input layers, the first and second sets of input layers interconnected with an output layer of the trained MLNN via intermediate layers, the trained MLNN produced by establishing a correlation between an injury condition of prior subjects and mmWave point cloud data and personal attributes associated with the prior subjects, and generating, at the output layer, the fall injury condition attributable to the subject.