Human Behavior Recognition & Prediction
Recognizing and evaluating human behavior patterns in order to identify errors and predict future behavior.
Smart environments enable buildings to recognize the residents and their behavior, and to react accordingly. An example would be a smart conference room that decides on its own whether it should close the blinds to make it easier for an audience to see a presentation or to improve energy efficiency.
Networking a wide range of different sensors to produce smart buildings. The iHomeLab's fall sensor is a good example. It includes an accelerometer, an air pressure sensor, and a temperature sensor. Only the combination of the three sensors makes it possible to detect the fall.
All of the sensors in a building can be interconnected to achieve sensor fusion. For example, an outdoor motion sensor that turns on outdoor lighting at night can be linked to a motion sensor in the stairwell so the building knows whether a person is entering or leaving.