Abstract: Target monitoring and alert systems for identifying and tracking targets within radar data. Raw frame data is filtered to remove data relating to reflections from static objects. Moving targets are identified in the filtered data and their location is tracked over time generating target data. Neural networks may process the target data, calculate a fall likelihood score and generate a fall-alert if this is above an alert-threshold. A person identification module may extract the position and motion characteristics of each target from the data and generate a probabilistic identification of the target with a person.

Abstract: Systems and methods for detecting angle of a vehicle using a radar including an array of transmitters, transmitting electromagnetic radiation towards surrounding objects, and receivers detecting reflected electromagnetic signals. Received information includes horizontal coordinates and vertical coordinates for each object detected. A pre-processing unit determines stationary and non-stationary state of objects from the received electromagnetic signals. A processing unit receives the coordinates along with motion characteristics of objects and plots each reflected object in the horizontal-vertical plane perpendicular to the direction of motion of the vehicle. A virtual box is constructed corresponding to each of a series of candidate tilt or roll angles. The angle of the virtual box having the largest number of plotted reflections is selected as the angle of the vehicle.

Abstract: A system including a radar unit, a processor unit and a communication module, the radar unit including a transmitter antenna connected to an oscillator and transmitting electromagnetic waves into a monitored region, and a receiver antenna receiving electromagnetic waves reflected by objects within the monitored region and generating raw data, the communication module communicating alerts to third parties, the processor unit including a moving body isolation processor, a tracker module receiving and processing data from the radar unit to identify and track location of moving targets over time thereby generating target data, an alert-threshold generator generating an alert-threshold, a neural network receiving from the tracker module target data inputs selected from height profiles, signal-to-noise ratio and radial distance to object and generating a fall likelihood score, and a fall identification module receiving the fall likelihood score and detecting a fall event if the likelihood score is above an alert-th

Abstract: Target monitoring and alert systems for identifying and tracking targets within radar data. Raw frame data is filtered to remove data relating to reflections from static objects. Moving targets are identified in the filtered data and their location is tracked over time generating target data. Neural networks may process the target data, calculate a fall likelihood score and generate a fall-alert if this is above an alert-threshold. A person identification module may extract the position and motion characteristics of each target from the data and generate a probabilistic identification of the target with a person.

Abstract: Fall detection systems and methods use radar chips to scan monitored regions such that data obtained by the scanning radar chip are processed to identify targets within the monitored region. Targets are tracked and profiled indicating their posture and fall detection rules are applied. Standard energy profiles and time dependent energy profiles are generated for various segments of the monitored region and compared to the current energy profile for each target segment of the monitored region. Anomalies are detected, false fall alerts filtered out and verified fall alerts are generated.

Abstract: Fall detection systems and methods use radar chips to scan monitored regions such that data obtained by the scanning radar chip are processed to identify targets within the monitored region. Targets are tracked and profiled indicating their posture and fall detection rules are applied. Standard energy profiles and time dependent energy profiles are generated for various segments of the monitored region and compared to the current energy profile for each target segment of the monitored region. Anomalies are detected, false fall alerts filtered out and verified fall alerts are generated.

Abstract: A user-centric cyber security system, comprising: a plurality of DAAs (Data Acquisition Agents) configured to collect data from a plurality of user's OSPs (Online Service Providers) and from a plurality of user devices; and a system server communicating with said plurality of DAAs, said system server configured to receive said collected data from said plurality of DAAs, analyze said data for threats to said user, alert said user accordingly, receiving feedback from said user regarding said alert and improve said threat analysis using said user's feedback.

Abstract: A user-centric cyber security system, comprising: a plurality of DAAs (Data Acquisition Agents) configured to collect data from a plurality of user's OSPs (Online Service Providers) and from a plurality of user devices; and a system server communicating with said plurality of DAAs, said system server configured to receive said collected data from said plurality of DAAs, analyze said data for threats to said user, alert said user accordingly, receiving feedback from said user regarding said alert and improve said threat analysis using said user's feedback.