The paper describes a system level design approach to the wearable computers project at Carnegie Mellon University (CMU). The project is an unique example of a cross-disciplinary effort, drawing students from mechanical engineering, electrical and computer engineering, computer science, and industrial design. Over the last six and half years that the course has been taught, teams of undergraduate and graduate students have designed and fabricated sixteen new generations of wearable computers, using an evolving artifact-specific, multidisciplinary design methodology. The complexity of their architectures has increased by a factor of over 200, and the complexity of the application has also increased significantly. We introduce a metric to compare wearable computers and show that their performances have increased by several orders of magnitude. A system-level approach to power / performance optimization is going to be a crucial catalyst for making wearable computers an everyday tool for the general public.

Carnegie Mellon's Wearable ComputersLaboratory has built four generations of real -time speech translation wearable computers, culminating in the Speech Translator Smart Module. Smart Modules are a family of interoperable modules supporting real-time speech recognition, language translation, and speech synthesis. In this paper, we examine the effect of various design factors on performance with emphasis on modularity and scalability. A system-level approach to power / performance optimization is described that improved the metric of (performance / (weight * volume * power)) by over a factor of 300 through the four generations.