Embedded Software for Distributed, Autonomous Smart Sensor Networks

by
Chuanbin Peng

Advised by
Kris Sikorski

The purpose of this research project is to solve one of the fundamental problems in tele-sensing: the interpretation of information and determination of the system state based on noisy and sparse data from sensor grid sources, interconnected with interruptable (wired or wireless) communication channels.

Such situations include medical sensing on ambulatory subjects in situations when sensor signal is frequently dominated by motion artifacts at the interface between the sensor and the body. This project will provide a novel approach in which sensor-level signal processing will be combined with data from multiple sensors to eliminate samples affected by noise/motion artifacts and determine reliability/uncertainty measures for the the entire measurement and data communication process. Non-medical applications of this software system also include management and interpretation of airplane sensor grids where distributed, autonomous sensor ensembles would be essential in increasing reliability and operational safety of aircraft systems.

As an example of a practical application of this research, we will develop embedded software for motion artifact reduction and data interpretation in medical sensors that will enable reliable, low power, adaptive sensing systems which operate autonomously on subjects in motion. This research project is funded by National Science Foundation. The School of Computing and the Center for Engineering Design at the University of Utah will provide mathematical, software and testing expertise, and Sarcos Research Corporation will complete design and engineering implementation of the entire system.