Abstract: Method and device for fall prevention and detection, specifically for the elderly care based on digital image analysis using an intelligent optical sensor. The fall detection is divided into two main steps; finding the person on the floor, and examining the way in which the person ended up on the floor. When the first step indicates that the person is on the floor, data for a time period of a few seconds before and after the indication is analyzed in the second step. If this indicates a fall, a countdown state is initiated in order to reduce the risk of false alarms, before sending an alarm. The fall prevention is also divided into two main steps: identifying a person entering a bed; and identifying the person leaving the bed to end up standing beside it.

Abstract: A sensor arrangement controls opening and closing of a door device. The sensor arrangement is arranged to be mounted in the vicinity of the door device. The sensor arrangement comprises an image-acquiring means, which monitors and acquires images of a field of view that encompasses at least an approach area located adjacent said door device, and a movement detector, which is arranged to process the acquired images in order to detect a movement, which is to result in an opening of the door device. The sensor arrangement also comprises an event generator, which is arranged to process information regarding the door device and said field of view in order to identify at least one event according to predetermined criteria, wherein the event generator in response to an identification of an event creates a recording of the event.

Abstract: Method and device for fall prevention and detection, specially for the elderly care based on digital image analysis using an intelligent optical sensor. The fall detection is divided into two main steps; finding the person on the floor, and examining the way in which the person ended up on the floor. The first step is further divided into algorithms investigating the percentage share of the body on the floor, the inclination of the body and the apparent length of the person. The second step includes algorithms examining the velocity and acceleration of the person. When the first step indicates that the person is on the floor, data for a time period of a few seconds before and after the indication is analysed in the second step. If this indicates fall, a countdown state is initiated in order to reduce the risk of false alarms, before sending an alarm.

Abstract: A method and system for installation of a monitoring unit. The monitoring unit comprises a photosensitive sensor for recording images of a monitored location. The system further comprises a light emitting element. The monitoring unit is arranged to detect the position of the light emitting element in a recorded image and by means of said position specify a sub-location within the monitored location.

Abstract: A sensor arrangement controls opening and closing of a door device. The sensor arrangement is arranged to be mounted in the vicinity of the door device. The sensor arrangement comprises an image-acquiring means, which monitors and acquires images of a field of view that encompasses at least an approach area located adjacent said door device, and a movement detector, which is arranged to process the acquired images in order to detect a movement, which is to result in an opening of the door device. The sensor arrangement also comprises an event generator, which is arranged to process information regarding said door device and said field of view in order to identify at least one event according to predetermined criteria, wherein the event generator in response to an identification of an event creates a recording of the event. An event-based system for managing a plurality of sensor arrangements is also provided.

Abstract: Method and device for fall prevention and detection, specially for the elderly care based on digital image analysis using an intelligent optical sensor. The fall detection is divided into two main steps; finding the person on the floor, and examining the way in which the person ended up on the floor. The first step is further divided into algorithms investigating the percentage share of the body on the floor, the inclination of the body and the apparent length of the person. The second step includes algorithms examining the velocity and acceleration of the person. When the first step indicates that the person is on the floor, data for a time period of a few seconds before and after the indication is analysed in the second step. If this indicates fall, a countdown state is initiated in order to reduce the risk of false alarms, before sending an alarm.