Learning and acting through sensors

We are living in a world that includes both digital and real objects. Sensors provide a bridge between these two spaces. Is it possible to use machine learning to acquire the sensor signals and turn them into useful knowledge about people¿s locations, actions and behavior? Is it possible to then guide people in the physical world through intelligent inference using the knowledge learned? In this paper the author discusses advances in machine learning and automated planning through wireless sensor networks.