Abstract.A hardware and software platform has been designed and implemented for modeling, testing, and deploying distributed peer-to-peer sensor networks comprised of many identical nodes. Each node possesses the tangible affordances of a commonplace pushpin to meet ease-of-use and power considerations. The sensing, computational, and communication abilities of a "Pushpin", as well as a "Pushpin" operating system supporting mobile computational processes are treated in detail. Example applications and future work are discussed.
This paper describes four different systems that we have developed for capturing various manners of gesture near interactive surfaces. The first is a low-cost scanning laser rangefinder adapted to accurately track the position of bare hands in a plane just above a large projection display. The second is an acoustic system that detects the position of taps on a large, continuous surface (such as a table, wall, or window) by measuring the differential time-ofarrival of the acoustic shock impulse at several discrete locations. The third is a sensate carpet that uses a grid of piezoelectric wire to measure the dynamic location and pressure of footfalls. The fourth is a swept radio frequency (RF) tag reader that measures the height, approximate location, and other properties (orientation or a control variable like pressure) of objects containing passive, magnetically coupled resonant tags, and updates the continuous parameters of all tagged objects at 30 Hz. In addition to discussing the technologies and surveying different approaches, sample applications are given for each system.
Abstract. This paper proposes the convergence of sensor networks and virtual worlds not only as a possible solution to their respective limitations, but also as the beginning of a new creative medium. In such a "dual reality," both real and virtual worlds are complete unto themselves, but also enhanced by the ability to mutually reflect, influence, and merge by means of sensor/actuator networks deeply embedded in everyday environments. This paper describes a full implementation of a dual reality system using a popular online virtual world and a humancentric sensor network designed around a common electrical power strip. Example applications (e.g., browsing sensor networks in online virtual worlds), interaction techniques, and design strategies for the dual reality domain are demonstrated and discussed.
Abstract-In order for nodes in a sensor network to meaningfully correlate their sensor readings, they must first determine their position in a globally shared coordinate system. Though there are many approaches which are suitable for achieving localization in the general case, sensor nodes are uniquely suited to use their sensing capabilities to aid them in this task. Global events which are detected in the environment surrounding the sensor network can serve as points of correspondence which, through collaborative processing on the network, provide nodes with sufficient information to compute their position.We have implemented an algorithm based on this approach in the Pushpin Computing sensor network: a dense, 55 node network which is spread over an area of 0.5 square meters. By queuing off of the minimum number of ultrasound pulses and light flashes needed to determine 2D coordinates using a simple lateration approach, we show that nodes in the Pushpin network can compute their position with an average error of 5-cm and a error standard deviation of 3-cm. In this paper we present this localization system and characterize its accuracy in our hardware testbed.
Abstract-Over the last three years we have built and experimented with the Pushpin Computing wireless sensor network platform. The Pushpin platform is a tabletop multihop wireless sensor network testbed comprised of 100 nodes arbitrarily placed within a one-square-meter area. The Pushpin platform's concise form factor and extreme node density allow for fine-grained control of its environment and immediate user interaction, thereby uniquely situating it between simulated and real world sensor networks. This paper details our salient successes and lessons learned along the way. We also discuss how these experiences have shaped our vision of the future of wireless sensor networks and some concrete research directions to follow.
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