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Related Experiment Video

Updated: May 13, 2026

Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults
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Advancing profiling sensors with a wireless approach.

Alex Galvis1, David J Russomanno

  • 1Department of Electrical and Computer Engineering, Purdue School of Engineering and Technology, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46202, USA. agalvis@iupui.edu

Sensors (Basel, Switzerland)
|February 28, 2013
PubMed
Summary
This summary is machine-generated.

A new wireless Near-Infrared (N-IR) profiling sensor uses sensor nodes and a neural network to classify humans, animals, or vehicles with 94% accuracy. This technology enhances deployment options for applications like intelligent fences.

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Area of Science:

  • Sensor Technology
  • Machine Learning
  • Optoelectronics

Background:

  • Early profiling sensors utilized wired Near-Infrared (N-IR) retro-reflective prototypes with vertical detector columns.
  • Limitations in deployment options and application scenarios existed with the wired approach.

Purpose of the Study:

  • To develop a wireless version of the N-IR profiling sensor.
  • To enhance object classification capabilities and improve deployment flexibility.

Main Methods:

  • Implementation of a wireless sensor network with distributed data collection and aggregation.
  • Development of a base station for data pre-processing and re-alignment.
  • Application of a back-propagation neural network for object classification.

Main Results:

  • The wireless N-IR profiling sensor achieved approximately 94% accuracy in classifying objects as human, animal, or vehicle.
  • The wireless architecture offers improved deployment options compared to wired systems.

Conclusions:

  • The wireless N-IR profiling sensor represents a significant advancement over its wired predecessor.
  • Enhanced classification and flexible deployment broaden potential applications, including intelligent fence systems.