Data and user interaction based on device proximity

#Typically, advertisements on technology devices are presented to the user while the user is already physically engaged in the content of a website, video, game, etc. Since the user focus is the priority for the user at the time, content such as advertisements, in general, may then be an annoyance or distraction from the focus of the user at that time. Thus, the gains hoped to be obtained by advertisers are becoming ever more limited.

#The following presents a simplified summary in order to provide a basic understanding of some novel embodiments described herein. This summary is not an extensive overview, and it is not intended to identify key/critical elements or to delineate the scope thereof. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is presented later.

#The disclosed architecture enables the detection of a user by a user device and interaction with content of the user device by the user before the user physically contacts the device. The detection capability can utilize one or more sensors of the device to identify the user and the proximity (distance) of the user to the device. Based on the user identity and the proximity, the device can be pre-configured/user configured to operate/function in certain ways. Moreover, ongoing interaction can be enabled by recognition of a natural user interface (NUI) gestures, alone or in combination with other recognition techniques (e.g., speech recognition).

#FIG. 1 illustrates a system in accordance with the disclosed architecture.

#FIG. 2 illustrates a personal system of data and user interaction based on personal user device proximity.

#FIG. 3 illustrates a public system of data and user interaction based on public device proximity.

#The disclosed architecture enables the detection of a user and attributes of the user by a device (public and personal) and interaction with content of the device by the user before the user physically contacts the device. The detection capability can utilize one or more sensors of the device or another sensor system to identify the user and the proximity (distance) of the user to the device. Based on the user identity and the proximity, the device can be pre-configured (e.g., by the user) to operate/function in certain ways.

#Moreover, ongoing interaction thereafter can be enabled by recognition of a natural user interface (NUI) gestures, alone or in combination with other recognition techniques (e.g., speech recognition). NUI may be defined as any interface technology that enables a user to interact with a device in a “natural” manner, free from artificial constraints imposed by input devices such as mice, keyboards, remote controls, and the like. Examples of NUI methods include those relying on speech recognition, touch and stylus recognition, gesture recognition both on screen and adjacent to the screen, air gestures, head and eye tracking, voice and speech, vision, touch, gestures, and machine intelligence. Thus, the NUI methods can enable interaction with a computing device that cause the computing device to perform a wide variety of operations, including, but not limited to, program navigation (e.g., dismiss (or close), open, save, browse) and power operations (e.g., sleep, standby, turn off, turn on, etc.).

#Specific categories of NUI technologies include touch sensitive displays, voice and speech recognition, intention and goal understanding, motion gesture detection using depth cameras (such as stereoscopic camera systems, infrared camera systems, RGB (red-green-blue) camera systems and combinations of these), motion gesture detection using accelerometers/gyroscopes, facial recognition, 3D displays, head, eye, and gaze tracking, immersive augmented reality and virtual reality systems, all of which provide a more natural interface, as well as technologies for sensing brain activity using electric field sensing electrodes (EEG (electroencephalogram) and related methods).