Advancing Profiling Sensors with a Wireless Approach

Sensors

Alex Galvis¹ 

[1] Department of Electrical and Computer Engineering, Purdue School of Engineering and Technology, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46202, USA; E-Mail

关键词: wireless profiling sensor;    neural network;    object classification;    sparse detector array;   

DOI  :  10.3390/s121216144

来源: mdpi

【 摘 要 】

The notion of a profiling sensor was first realized by a Near-Infrared (N-IR) retro-reflective prototype consisting of a vertical column of wired sparse detectors. This paper extends that prior work and presents a wireless version of a profiling sensor as a collection of sensor nodes. The sensor incorporates wireless sensing elements, a distributed data collection and aggregation scheme, and an enhanced classification technique. In this novel approach, a base station pre-processes the data collected from the sensor nodes and performs data re-alignment. A back-propagation neural network was also developed for the wireless version of the N-IR profiling sensor that classifies objects into the broad categories of human, animal or vehicle with an accuracy of approximately 94%. These enhancements improve deployment options as compared with the first generation of wired profiling sensors, possibly increasing the application scenarios for such sensors, including intelligent fence applications.

【 授权许可】

CC BY   
© 2012 by the authors; licensee MDPI, Basel, Switzerland