This paper presents new approaches for dynamically integrating sensors into a surrounding computing infrastructure. Our work is based on small programs - called Senslets - that are stored on sensor nodes. Senslets are written using a programming model based on a high-level programming language such as C# or Java, but they do not assume a virtual execution environment on the sensors. Instead, they are downloaded to a mobile device or stationary computer, where they are hosted and executed. In this paper, we present (1) a programming framework for developing Senslets, (2) the tools necessary for deploying Senslets on resource-constrained sensor nodes, and (3) a hosting environment for executing Senslets on mobile phones. The paper also contains an evaluation and a description of example applications.

This paper presents novel text input methods for mobile devices. In particular, it shows how users can capture text from books, newspapers, and other objects by using the digital cameras that are integrated into an increasing number of smartphones. The idea is to select text from a live video stream generated by these digital cameras. Different interaction patterns are discussed that allow users to select text: (1) automatic detection of the word closest to a fixed position on the mobile device's screen, (2) delayed movement of the text selection to improve the precision of the selection procedure, and (3) using the stylus to select words and word groups. The proposed interaction patterns are evaluated based on the results of a user study, and their application is shown in an example scenario. The presented research has practical relevance because it can improve the usability of mobile applications such as online searching

Passive RFID technology and unobtrusive Bluetooth-enabled active tags are means to augment products and everyday objects with information technology invisible to human users. This paper analyzes general interaction patterns in such pervasive computing settings where information about the user's context is derived by a combination of active and passive tags present in the user's environment. The concept of invisible preselection of interaction partners based on the user's context is introduced It enables unobtrusive interaction with smart objects in that it combines different forms of association, e.g. implicit and user initiated association, by transferring interaction stubs to mobile devices based on the user's current situation. Invisible preselection can also be used for remote interaction. By assigning phone numbers to smart objects, we propose making this remote user interaction with everyday items as easy as making a phone call. We evaluate the suitability of the proposed concepts on the basis of three concrete examples: a product monitoring system, a smart medicine cabinet, and a remote interaction application.