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Objective

Ubiquitous Computing Infrastructure. Sensor Node. User. Java Virtual Machine. TOSBase Transceiver. SA-1110 Board. Base Station. Intel SA-110. Crossbow Mica-2. WIRELESS SENSOR NETWORKS, WEARABLE COMPUTING AND THE COMING ERA OF UBIQUITOUS EMBEDDED INTELLIGENCE. Objective

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Objective

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  1. Ubiquitous Computing Infrastructure Sensor Node User Java Virtual Machine TOSBase Transceiver SA-1110 Board Base Station Intel SA-110 Crossbow Mica-2 WIRELESS SENSOR NETWORKS, WEARABLE COMPUTING AND THE COMING ERA OF UBIQUITOUS EMBEDDED INTELLIGENCE Objective • To facilitate novel means of human-computer interaction by leveraging the impending paradigm shift in embedded systems technology • To introduce innovative conduits for entertainment technologies • To exploit opportunities in the realm of synergistic interactions between industrial-strength programming technology and full-custom design methodologies • To demonstrate the advantages of just-in-time design methodologies Research Results • Discovered novel means of interaction which foster jocular response in 93% of subjects • Developed custom Linux, Java and TinyOS infrastructure to support ubiquitious computing applications • Breakthroughs in novelty and innovation for previously stagnant entertainment application domains • Enhanced wearable computing system interoperability for distracted and disabled operators Implementation Specifications • Intel StrongARM SA-1110 Microprocessor Development Board • MPR400CB Crossbow Mica-2 Wireless Sensor Node • Analog Devices ADXL 2302 2-Axis Accelerometer • Custom Linux 2.6.16 Kernel • Custom Tetris Experience Potential Applications • Cranially-activated vehicular systems controls • Enriched input modalities for disabled users • Highly-integrated wireless personal area networks • Engendering alternate perceptions of reality with minimal psychophysical impact • Broad spectrum human-computer feedback control • Environmental stimulus data mining • Novel handicap realization in experimental game theory frameworks Sample Unfiltered Accelerometer Plot • In early development, sensor readings are streamed to the base station for real-time data analysis • For improved performance and power efficiency, filter processing is pushed down to embedded devices • Results in power savings of over 32x ACM – SIGEmbedded http://www.acm.uiuc.edu/sigembedded/

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